A system and method for a community ecosystem infrastructure

Abstract

A system (100) and method for a community ecosystem infrastructure (110) are provided, which may include providing an association of an asset (115) to an entity (102). The method includes receiving asset data (171A, 171B) relating to an asset (115), as well as geographical information associated with the asset data (171 A, 171B), from a geographical information service (138). The method includes transmitting, to a plurality of verifying entities, a request to verify an association of the asset (115) to the entity (102), and receiving, from at least one of the pluralities of verifying entities, a response indicating an approval or rejection of an association between the asset (115) and the entity (102). The method includes determining, based on the responses received, a certification of association of the asset (115) to the entity (102).

Description

[0001] A SYSTEM AND METHOD FOR A COMMUNITY ECOSYSTEM INFRASTRUCTURE

[0002] CROSS-REFERENCES TO RELATED APPLICATIONS

[0003] This application claims priority from South African provisional patent application number 2024 / 07574 filed on 7 October 2024, which is incorporated by reference herein.

[0004] FIELD

[0005] This disclosure relates to a system and method for providing a computer-based community ecosystem infrastructure.

[0006] BACKGROUND

[0007] In many developing countries, the struggle to secure and authenticate property ownership is a reality for many people. For those living in informal settlements or rural areas, the lack of proper documentation and formal land titles creates significant barriers to claiming their rights. Without reliable records or a transparent legal framework, disputes over land are common, often resulting in lengthy, and costly disputes.

[0008] The administrative process associated with validating property can be overwhelming. Many people lack access to the necessary resources or education to navigate complex legal systems. Corruption and inefficient administration further complicate the process, making it nearly impossible for ordinary citizens to secure proof of ownership. This lack of documentation leaves properties vulnerable to disputes and at risk of being seized by more powerful entities.

[0009] For those struggling to get their property validated, the consequences are far-reaching. Without proof of ownership, families are unable to use their land as collateral for loans, preventing them from investing in businesses or improving their living conditions. Additionally, they are excluded from government programs and services that require legal documentation of residence. This cycle of uncertainty and exclusion deepens poverty and slows down economic growth. In such an environment, securing property rights is a crucial step towards empowerment and economic opportunity.

[0010] The preceding discussion of the background is intended only to facilitate an understanding of the present disclosure. It should be appreciated that the discussion is not an acknowledgment or admission that any of the material referred to was part of the common general knowledge in the art as at the priority date of the application.

[0011] SUMMARY

[0012] In accordance with an aspect of the disclosure there is provided a computer-implemented method, conducted at a community ecosystem infrastructure, for providing an association of an asset to an entity, comprising: receiving asset data relating to the asset; receiving geographical information associated with the asset data from a geographical information service; transmitting, to a plurality of verifying entities, a request to verify an association of the asset to the entity; receiving, from at least one of the plurality of verifying entities, a response indicating an approval or rejection of an association between the asset and the entity; and, determining, based on the received responses, a certification of association of the asset to the entity.

[0013] The asset data may be received from an entity device. The entity device may be related to the entity.

[0014] The method may include, in response to determining an approval of the certification of association between the asset and the entity, issuing a certificate indicating an approval of association of the asset. The certificate may be usable on the community ecosystem infrastructure as proof-of- ownership of the asset with services.

[0015] The method may include receiving, from the entity device, a transfer request including asset data and an identifier of a receiving entity for transferring the certification of association of the asset to the receiving entity. The method may include receiving, from the entity device, a utilisation request permitting a utilising entity to utilise the asset.

[0016] Determining the certification of association of the asset may include inputting the received responses into a trust model. The trust model may be configured to output an approval or rejection of the certification of association based on the received response.

[0017] The trust model may be a graph network. Nodes of the graph network may model different entities registered with the community ecosystem infrastructure. Edges of the graph network may model a trust score between entities connected to the edge.

[0018] The trust model may be calibrated according to a set of trusted parties serving as trusted entities relative to other entities. The method may include recalibrating the trust model in response to triggering events. The triggering events may include any one or more of: predefined weather events; forced removals or displacement; changes in trusted parties; and, predetermined time periods between calibrating.

[0019] The method may include registering entities with the community ecosystem infrastructure. The method may include registering a trusted entity device associated with the entity. The entities may all relate to a common geographical area in which the community ecosystem infrastructure is based.

[0020] The method may include providing an entity application, usable by the entity device, for accessing the community ecosystem infrastructure and ecosystem services. The entity application may be configured to operate on the entity device.

[0021] The method may include providing application programming interfaces to one or more external resources for integration of external services with the community ecosystem infrastructure. The external resources may include any one or more of: property deeds office; car registration office; home affairs; banks; credit bureau; and, document signing services.

[0022] Providing ecosystem services may include asset registration and trading services. Assets for asset registration may be property. The external services may include satellite and geographic information systems (GIS). The ecosystem services may include: financing services; security services; environmental services; insurance services; trading services; and, social services.

[0023] The method may include registering entities in the community ecosystem infrastructure as role players within the community. The method may include providing ecosystem services to the registered entities. The method may include providing a platform for registered entities to provide goods and services to other registered entities. The method may include providing training to registered entities thereby providing certification for offering goods and services to other registered entities. The method may include providing integration to external resources for external services provided to the registered entities.

[0024] In accordance with a further aspect of the disclosure there is provided a computer-implemented method, conducted at an entity device, for providing association of an asset related to an entity, comprising: obtaining asset data related to the asset at the entity device, the asset being associated with the entity; transmitting the asset data to a server of the community ecosystem infrastructure, wherein the server is configured to: receive geographical information associated with the asset data from a geographical information register; transmit, to a plurality of verifying entities, a request to verify an association of the asset to the entity; receive, from each of the plurality of verifying entities, a response indicating an approval or rejection of an association between the asset and the entity; and, determine, based on the received responses, a certification of association of the asset by the entity; and, receiving, from the server, a certification of association indicating an association of the asset with the entity.

[0025] The method, conducted at an entity device, may include receiving a request from the server to verify an association of a second asset to a second entity. The method, conducted at an entity device, may include outputting a prompt to the entity device to verify an association between the second asset and the second entity. The method, conducted at an entity device, may include receiving an input at the entity device, the input indicating an approval or rejection of the association of the second asset to the second entity. The method, conducted at an entity device, may include transmitting input indicating approval or rejection to the server.

[0026] In accordance with a further aspect of the disclosure there is provided a system including a server for providing a certification of association of an asset related to an entity within a community ecosystem infrastructure, comprising: an asset data receiving component for receiving asset data related to the asset; a geographical information receiving component for receiving geographical information associated with the asset data from a geographical information register; a request transmitting component for transmitting, to a plurality of verifying entities, a request to verify an association of the entity to the asset; a verification receiving component for receiving, from each of the plurality of verifying entities, a response indicating an association between the asset and the entity; and, an ownership determining component for determining, based on the received responses, a proof-of-ownership of the asset by the entity.

[0027] In accordance with a further aspect of the disclosure there is provided a computer program product for providing an association of an asset related to an entity, the computer program product comprising a computer-readable medium having stored computer-readable program code for performing, at a server, the steps of: receiving asset data relating to the asset; receiving geographical information associated with the asset data from a geographical information service; transmitting, to a plurality of verifying entities, a request to verify an association of the asset to the entity; receiving, from each of the plurality of verifying entities, a response indicating an approval or rejection of an association between the asset and the entity; and, determining, based on the received responses, a certification of association, of the asset by the entity. In accordance with a further aspect of the disclosure there is provided a computer program product for providing an association of an asset related to an entity, the computer program product comprising a computer-readable medium having stored computer-readable program code for performing, at an entity device, the steps of: obtaining asset data related to the asset at the entity device; transmitting the asset data to a server of the community ecosystem infrastructure, wherein the server is configured to: receive geographical information associated with the asset data from a geographical information register; transmit, to a plurality of verifying entities, a request to verify an association of the asset to the entity; receive, from each of the plurality of verifying entities, a response indicating an approval or rejection of an association between the asset and the entity; and, determine, based on the received responses, a certification of association of the asset by the entity; and, receiving, from the server, a certification of association indicating an association of the asset with the entity.

[0028] In accordance with an aspect of the disclosure there is provided a computer-implemented method for providing a community ecosystem infrastructure having a relationship management system, comprising: registering entities in the infrastructure as role players within the community; providing ecosystem services to the registered entities; providing a platform for registered entities to provide goods and services to other registered entities; providing training to registered entities thereby providing certification for offering goods and services to other registered entities; and providing integration to external resources for external services provided to the registered entities.

[0029] External services may include: water and plumbing services, solar electricians, internet providers, barbers and salons, shops and food outlets, waste removal, recycling, and the like.

[0030] Registering entities may include integrating with an external identification resource.

[0031] The computer-implemented method may include generating income streams for registered entities by referrals of new entities to expand the ecosystem.

[0032] The step of providing training may include providing online training at multiple levels. The step of providing training may include providing training certifications.

[0033] Providing ecosystem services may include asset registration and trading services. The assets may be property and asset registration may use external resources. External resources of a deeds office may be used. External sources may include satellite and GIS datapoints. Providing ecosystem services may include financing services. Providing ecosystem services may include security services. Providing ecosystem services may include environmental services. Providing ecosystem services may include providing insurance services. Providing ecosystem services may include providing trading services. Providing ecosystem services may include providing social services.

[0034] In accordance with a further aspect of the disclosure there is provided a computer-implemented community ecosystem infrastructure having a relationship management system, comprising: an entity registration component for registering entities in the infrastructure as role players within the community; an ecosystem services component for providing ecosystem services to the registered entities; a platform for registered entities to provide goods and services to other registered entities; a training component for providing training to registered entities thereby providing certification for offering goods and services to other registered entities; and an integration component for providing integration to external resources for external services provided to the registered entities.

[0035] The system may include an entity application for accessing the platform and ecosystem services for registered entities.

[0036] The integration component may provide application programming interfaces to external resources for integration of their external services. External services may include property deeds office, car registration office, home affairs, credit bureau, document signing services, etc. External services may include satellite imagery and other tracking systems, integration of machine learning, artificial intelligence, virtual property tours, and automated assistance.

[0037] The entity registration component may integrate with an external identification resource. The system may include an income generating component for generating income streams for registered entities by referrals of new entities to expand the ecosystem. The training component may provide online training at multiple levels. The training component may provide training certifications.

[0038] The ecosystem services component may include providing asset registration and trading services. The ecosystem services component may include providing financing services. The ecosystem services component may include providing insurance services. The ecosystem services component may include providing security services. The ecosystem services component may include providing environmental services.

[0039] Embodiments of the technology will now be described, by way of example only, with reference to the accompanying drawings.

[0040] BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In the drawings:

[0042] Figure 1A is a schematic diagram illustrating an example system of a community ecosystem infrastructure in accordance with aspects of the present disclosure;

[0043] Figure 1 B is a schematic diagram illustrating an example system for associating an asset to an entity within the community ecosystem infrastructure in accordance with aspects of the present disclosure;

[0044] Figure 1C is a schematic diagram illustrating an example relationship management system in accordance with aspects of the present disclosure;

[0045] Figure 2A is a flow diagram of an example method for providing a community ecosystem infrastructure in accordance with aspects of the present disclosure;

[0046] Figure 2B is a flow diagram of an example method for registering an entity with the community ecosystem infrastructure in accordance with an aspect of the present disclosure;

[0047] Figure 3A is a swim-lane flow diagram of an example method for association of an asset with an entity according to aspects of the present disclosure;

[0048] Figure 3B is a swim-lane flow diagram of an example method for association of a second asset with a second entity according to aspects of the present disclosure;

[0049] Figure 4 is a schematic diagram of an example method illustrating training and use of machine learning models;

[0050] Figure 5 is a block diagram of an example embodiment of a computing system in accordance with the described system; and,

[0051] Figure 6 is a block diagram of an example embodiment of a computing device in which aspects of the described system may be implemented. DETAILED DESCRIPTION WITH REFERENCE TO THE DRAWINGS

[0052] A computer-implemented method and system are described for providing a community ecosystem infrastructure. The community ecosystem infrastructure may provide for entities in the form of individuals, groups of individuals, or companies to interact with each other and with assets belonging to the entities. The community ecosystem infrastructure (also referred to as “ecosystem”, “infrastructure”, or “ENTERPRISE”) may be provided for a geographical area in which a community is based, and the entities may all be based in the geographical area. The geographical area may span from localised areas, such as informal settlements, to entire cities, countries or further.

[0053] Within informal settlements or rural areas, the lack of proper documentation of physical boundaries, formal land titles, and substandard infrastructure makes it difficult to claim rights to various assets, including both movable and immovable. In some cases, the assets may include land or housing infrastructure. The hurdle to providing records indicating or proving the existence of ownership over immovable assets is not purely administrative: there are no existing divisions of the land or manner of recording such types of ownership that provides a trustworthy, validatable, and digital record of asset ownership. As housing in informal settlements may be quickly built, removed, illegally occupied or destroyed, a new, digital manner of recording such assets for fast approval is required.

[0054] The community ecosystem infrastructure provides a means of recording entities and their relationships to assets. The community ecosystem infrastructure may include a register, such as an asset trade register. The register may record entities and assets. The community ecosystem infrastructure may include a relationship management system for recording relationships between entities and assets, and between different entities, assisting in managing of assets.

[0055] The relationship management system may be provided as a background system, for example, as a server-based system. The relationship management system registers entities in the infrastructure as role players within the community. The community ecosystem infrastructure may provide for registration of assets on the register, such as immovable property, vehicles, and the like. The relationship management system may provide a digital proof of ownership of assets registered on the system. Therefore, the relationship management system may provide a reliable proof of asset ownership. Within the community ecosystem infrastructure, the relationship management system may serve to establish ownership of assets, such as residences, automobiles, valuable assets, etc. The relationship management system may use a peer-to-peer verification for verifying if an asset belongs to an entity.

[0056] The community ecosystem infrastructure provides services to registered entities. The services may include ecosystem services which are services provided by the ecosystem itself. Other services may include external services, which may be services provided by external resources either across the infrastructure, or whereby the infrastructure serves to link entities to external services. In some examples, the external resources may be used in the course of providing ecosystem services, for example, to register assets with external authorities. The community ecosystem infrastructure may provide training to registered entities thereby providing certification for offering goods and services to other registered entities. The ecosystem services may include any one or more of: financing services; security services; environmental services; insurance services; trading services; and social services.

[0057] The relationship management system provides a platform for registered entities to provide goods and services to other registered entities. Providing goods and services may including altering relationships between entities. For example, one entity may sell an asset to another entity. The relationship management system may provide a system for managing a change in ownership of the asset.

[0058] In some examples, entities may wish to provide proof that an asset belongs to them. Such an asset may be a house within an informal settlement. Geographical information and a photograph of the house may be sourced via an application programming interface from a geographic information systems (GIS) partner and enriched by an application of the community ecosystem infrastructure. Verification data may be captured by the community, through which ownership is verified by neighbours. A title deed equivalent may be registered on the register. The data may be sold to partnered banks and other financial institutions via partnered credit bureaux or directly.

[0059] The community ecosystem infrastructure provides critical services to underserved communities. These critical services may reduce the burden placed on their lives, while providing access to services that were previously not available to them.

[0060] Figure 1A is a schematic diagram of an exemplary system 100 for a community ecosystem infrastructure 110. An entity 102, such as a person, may interact with the community ecosystem infrastructure 110. Various other entities may interact with the community ecosystem infrastructure 110. All entities may relate to a common geographical area in which the community ecosystem infrastructure is based. The entity may be associated with an entity device 104 through with the entity 102 may interact with the infrastructure 110. In some examples, the entity device 104 may be a computing device, such as a mobile phone. The entity device 104 may include an application for interacting with the infrastructure 110. The entity may be associated with an entity payment card 106. The entity payment card 106 may be configured for accessing or associated with financial services 153 of the infrastructure 110.

[0061] The entity may download the application onto the entity device. The application may be free for download and use and may provide voucher discounts on expenses like food and data. Entities may become agents and earn commission for running sustainability opportunities in the neighbourhood via the application. Homes may be recognised via the application as belonging to the entity, formalising the entity’s address. The recognition of the address may provide easier access to credit and insurance. In some examples, a trust-less blockchain-like environment and ecosystem token may be used for conducting transactions across the infrastructure.

[0062] The community ecosystem infrastructure 110 may include one or more servers 111. The server 111 may be a computing device configured to perform functions related to the community ecosystem infrastructure 110. The server may include a register 114. The register may store entities 121 , assets 122, and / or trusted parties 123. The entities 121 may include any one or more of: improvers, representatives, build merchants, agents, estate agents, partnerships, borrowers, card users, merchants, franchisees, builders, employees, sellers, savers, planters, insured, coowners, lessees, drivers, car dealers, security agents, and the like.

[0063] The entities 121 may be registered entities who have registered with the community ecosystem infrastructure 110. The trusted parties 123 may be entities registered as trusted entities or “oracles”. The trusted parties 123 may be entities that have a higher trust ranking (trust score) than other entities. The trusted parties 123 may include any one or more of: religious leaders, chiefs, agents, and the like. The purpose of the trusted parties 123 is to promote and verify ownership of assets.

[0064] The entities 121 and / or trusted parties 123 may have entity profile data associated with them. The entity profile data may include personal information and / or contact and verification information. The personal information may include any one or more of: identity information; demographic data; profile images; and legal compliance information. Each entity profile may include a systemgenerated entity identifier. For example, the system-generate entity identifier may be a hash of personal details of the entity, such as “f47ac10b-58cc-4372-a567”. The identify information may be a Cognito™ identifier for secure authentication. The demographic data may include basic demographic information, including a first name, surname, email address, phone number, date of birth, sex, gender and the like. The profile image may be an entity photo, uploaded by the relevant entity, including bearing / orientation metadata. The legal compliance information may include a tag associated with a timestamp of acceptance, by the entity, of a Terms of Service and privacy policy document. The entity profile data may include a GPS coordinate of the entity for community mapping. Each entity profile may have an associated residency status, such as owner, renter, or landlord. The residency status may be unique for each asset associated with the entity. For example, the entity may be an owner in relation to an asset, but a renter in relation to another. The entity profile may include a community integration metric, such as a duration of residence in the community.

[0065] The contact verification information may include primary contact details, an email address, and account status. The primary contact details may be a mobile phone number usable as a primary identifier for trust network participation. The email address may be a secondary contact method fortrust network participation. The account status may be a status indicator of whether an account of the entity is active, inactive, banned, blocked or otherwise disabled. The account status may be usable for tracking accounts for operational purposes.

[0066] The server 111 may include a relationship management system 112. The relationship management system 112 may be configured to manage relationships between entities 121 and assets 122, as well as entities 121 to entities 121. The relationship management system 112 allows for assets to be registered in the register 114. The assets may include property, such as movable and / or immovable property. The register may include details related to the assets 122, such as asset metadata 124. Asset metadata 124 may, in an example of the asset 122 being a property, include any one or more of: owner information, property value, property identification details, building information, mortgage and financial details, legal information, utilities and amenities.

[0067] The owner information may include any one or more of: full name of the owner; contact information; date of ownership transfer; previous owner; and the like. The property value may include any one or more of: market value; purchase price; property tax assessment value; recent sales history; sale prices; annual property tax amount; and the like.

[0068] The property identification details may include any one or more of: property address (including full street address with area identification); plot number or parcel number; zoning details; lot size; dimensions; global positioning system (GPS) coordinates, including latitude and longitude information; geographic usage data, including property usage patterns and purposes; and, multi- location support, such that a single entity may be associated with multiple properties.

[0069] Building information may include, if the asset is a property, a property type. For example, the property type may be a residential structure classification. The building information may include any one or more of: surface area, number of rooms, bathrooms, and floors, the year in which it was erected, renovation or improvement history, building materials, building condition, structure details, such as a building type, number of residences per structure, visual documentation, such as a front and side property images which may include GPS coordinates, and, ownership structure, including owner, tenant or resident relationships.

[0070] The mortgage and financial details may include any one or more of: outstanding mortgage amount; mortgage lender / bank information; lien status; structure cost; transfer date; ownership shareholding or percentage; and number of co-owners. The mortgage and financial details may include tenant property data, including: rental amounts; payment frequency; and move-in date. The mortgage and financial details may include, in the case of resident properties, a move-in date for non-owner occupants.

[0071] The legal information may include any one or more of: title deed number; easements or rights-of- way affecting the property; encumbrances; property boundary disputes; and legal issues. The utilities and amenities may include any one or more of: water supply; electricity supply; sewage connections; access to public amenities like schools, parks, and public transportation; neighbourhood features; and facilities.

[0072] The community ecosystem infrastructure 110 may interface with external resources 160. External resources 160 may provide external services. External services may include satellite and geographical information systems. The external resources 160 may include any one or more of: property deeds office, car registration office, home affairs, credit bureau, document signing services, geospatial service 138, and the like. The community ecosystem infrastructure 110 may include ecosystem services 152. The ecosystem services 152 may be service providers by and / or within the community ecosystem infrastructure 110.

[0073] The community ecosystem infrastructure 110 may include training services 151. The training services may provide training for entities on using and interacting with the infrastructure 110. The training services may be provided as online training (e-training). The training may include training ecosystem infrastructure agents, trusted parties 123, representatives, merchants, drivers, and the like. The infrastructure 110 may include financial services 153. The financial services may include services such as credit checks, lending, underwriting, and the like. The financial services may be provided directly by the infrastructure 110 or together with external resources.

[0074] The server 111 may include one or more application programming interfaces (API) 130. The API 130 may be configured to interact with the external resources. The AP1 130 may include interfaces dedicated to specific functions and / or services. The API 130 may integrate external services with the community ecosystem infrastructure.

[0075] The API 130 may include a facial recognition API 131. The facial recognition API may transmit or receive facial recognition information to and from the server, such as a photo of a face of the entity 102 and receive verification that an entity identity is correct (matches the photo). The facial recognition API 131 may communicate with an external resource, such as home affairs, for identity confirmation. The API 130 may include a deeds office API 134. The deeds office API 134 may be configured to communicate with a deeds office for asset registration. The API 130 may include a geographical information system (GIS) API 132. The geographical information system AP1 132 may be configured to transmit asset metadata 124 to an external resource, and / or receive geospatial information relating to geographical coordinates or asset metadata. The API 130 may include a traffic information API 133. The traffic information AP1 133 may be configured to transmit and receive traffic information from a third-party platform, such as vehicle information, vehicle ownership, and vehicle registration.

[0076] The server may include a valuation system 116. The valuation system 116 may be configured to receive assets 122 and assets metadata 124 and output a valuation of the assets. The valuation system 116 may include an artificial intelligence (Al) system for outputting the valuation.

[0077] The server 111 may include a security system 118. The security system 118 may interface with security providers to offer security services for entities 121. The server 111 may include an electronic peg (e-peg) system 119. The e-peg system 119 may include electronic markers related to assets. For example, the electronic marker may include a GPS coordinate. The electronic markers may be stored together with assets metadata 124 in the register.

[0078] The server 111 may include a verification system 117. The verification system 117 may be configured to verify relationships between assets and entities, and between entities themselves. The verification system 117 may include a trust model. The trust model may indicate a level of trust between entities and assets. The trust model may have a trust score for each entity. In some examples, the trust model may include a trust score for a relationship between individual pairs of entities, i.e., each combination of two entities has a trust score. The trust model may include a trust score between entities and assets. In some examples, the verification system 117 may form part of the relationship management system 112. The community ecosystem infrastructure may incentivise participation through a rewards system, where entities earn points for successful verifications, endorsements, and / or referrals. This gamified approach encourages continued engagement and ensures that the infrastructure remains active and reliable.

[0079] The verification system 117 may utilise a trust endorsement system and / or a geographic relationship system. Entities may endorse each other's residency, i.e. confirm that another entity resides in proximity, to improve a trust score of one or both of the entities. For each pair of entities, a trust score of an endorsement between the pairs may be calculated (for example, as a value between 0 to 100). The trust endorsement system may include a property-specific endorsement, tied to specific property addresses. Therefore, certain entities residing at predetermined address or in specific areas may have a higher trust score. The trust endorsement system may determine a trust score for a verification (endorsement) based on when the verification was performed. The trust endorsement system may account for two entities both giving and receiving verifications (endorsements) to each other.

[0080] The geographic relationship system may account for geographic proximity of entities. Neighbours may receive larger trust scores. The geographic relationship system may cluster communities together. The clustering may be determined along community boundaries and / or local area definitions.

[0081] Figure 1 B is a schematic diagram illustrating the system 100 for verifying an asset 115 for association with the entity 102. The entity device 104 may include one or more input sensors. The input sensors may include and one or more of: a camera, a microphone, a haptic feedback module, a low-energy Bluetooth™ sensor, and the like. The entity device 104 may obtain an image 171 A of the asset 115. The entity device 104 may obtain image metadata 171 B. In some examples, the image 171A and image metadata 171 B may be obtained by taking a photo of the asset with the entity device 104.

[0082] The relationship management system 112 may be configured to obtain the image 171 A and image metadata 171 B. For example, the image 171A and image metadata 171 B may be transmitted over a network, such as the internet, to the server 111 and to the relationship management system 112. The geospatial service 117 may be configured to receive the image 171A and image metadata 171 B (or other asset and asset metadata) and output a standardised address 171C.

[0083] The relationship management system 112 may communicate with a plurality of verifying entity devices 127, including entity devices 191 A, 191 B related to other entities. The verifying devices 127 may be configured to output a prompt to an entity operating said device, obtain an input from the said entity and generate a response message.

[0084] The relationship management system 112 may include a certificate generator for generating a certificate 173. If the relationship management system 112, together with the verification system 117, determines that an association exists between the asset 115 and the entity 102, a certificate 173 may be generated. The certificate 173 may be usable by the entity device 104 as a proof-of- ownership when interacting on the community ecosystem infrastructure 110.

[0085] Figure 1C is a schematic diagram illustrating an example relationship management system 112. The relationship management system 112 may include a database 180. The database 180 may be a graph database. The database 180 may store one or more models 184. The model 184 may be the trust model. The model 184 may be a graph network model. The model 184 may be stored in the database 180 and provisioned to the verification system 117 when required. The model 184 may include model architecture information, such as model weights 181 , model nodes 183, model edges 182, and the like. The model edges 183 may include information on connectivity of nodes. Nodes of the graph network may model different entities registered with the community ecosystem infrastructure. Edges of the graph network may model a trust score between entities connected to the edge. The model may be calibrated. The model may be calibrated according to a set of trusted parties serving as trusted entities relative to other entities. For example, a set of entities may be pre-selected as being trustworthy entities within the community ecosystem infrastructure.

[0086] The relationship management system 112 may include a relationship updating module 165. The relationship updating module 165 may update the one or more models 184 by updating any of the weights 181 , edges 182, and nodes 183. The relationship updating module 165 may determine when a triggering event occurs, triggering an update of the models. The triggering even may include any one or more of: predefined weather events; forced removals or displacement; changes in trusted parties; and predetermined time periods between calibrating.

[0087] The relationship management system 112 may include a trust determining module 166. The trust determining module may include a trust scoring mechanism. The trust determining module may include fraud prevention measures. The trust scoring mechanism may incorporate weighted factors, including any one or more of: geographic proximity between an endorsing entity (an entity being asked to verify an association) and an endorsed entity (entity required a certification of association); duration of residency in the community (longer-term residents may have a higher trust score); mutual connections (entities in common between endorsing entity and endorsed entity) may be assigned a higher trust score than two entities without any mutual connections; historical endorsement accuracy (previous false endorsements / verifications may reduce a trust score of an entity); and an overall trustworthiness score (endorsement credibility) of the endorsing entity. This ensures that endorsements with higher credibility have a greater impact on verifying an association, reducing the risk of fraudulent claims.

[0088] The trust determining module may be configured to receive responses from verifying entities and determine a trust score based on said responses. The trust score may reflect a credibility of an entity’s claim to be associated with the asset. The trust determining module 166 may output a certification of association based on the trust score. The trust score may be a combined trust score from multiple entities. The trust determining module may be configured to receive verifications (endorsements) from other entities (verifying entities). Each entity may have a personal trust score, being an individual credibility rating between 0 and 100. Each entity may have a property verification status, indicating ownership or rental verification. Each entity may include a total endorsement strength, including a cumulative trust from all verifications received by the entity. Each entity may include a community integration score based on neighbour relationships and duration in the community. The trust determining module may be configured to adapt all trust scores relating to individual entities, relationships between entities, and the like.

[0089] The weighted factors may be implemented using edges of the graph network. For example, the graph network may be configured with a plurality of edges between any two nodes. Each edge between any two nodes may represent one or the weighted factors. The model weights 181 may be associated with model edges 182. The model weights 181 may represent a relation / correlation between two nodes 183. The value of the model weight for each edge between the same two nodes represents a strength of the specific weighting factor between two nodes. For example, if two entities (with a node representing each entity) are proximate each other in the physical world, the weight of the edge representing the proximity weighting factor may be large relative to other weighting factors. Therefore, the closer entities are to each other (endorsing entity and endorsed entity), a higher trust weight may be assigned to the edge. In some examples, if an entity has been determined to provide fraudulent verification response, all the weights of the edges to and from the node representing said entity may be minimised.

[0090] The graph network may provide for weighted trust calculations and fraud detection techniques, creating a scalable, transparent, and tamper-resistant verification system. This approach may strengthen financial inclusion by giving users access to credit, insurance, and other financial services based on their established housing stability or other associations with assets.

[0091] The relationship management system 112 may include an asset configuring module 167. The asset configuring module 167 may interface with the register. The asset configuring module 167 may create, modify, and / or cancel associations of an asset between other assets and entities to reflect associations of assets.

[0092] The community ecosystem infrastructure 110, including the server 111 , register 114, relationship management system 112, and APIs 130 may each utilise blockchain-type technology. The blockchain-type technology may allow decentralised operation of the infrastructure 110. For example, the register 114 may store entities 121 , assets 122 and the like using decentralised technology, allowing the storage across a plurality of storage locations to improve data collection time, improve data security and improve the ability to interact seamlessly amongst entities, assets, and the like. The application may be a decentralised application (dApp) configured for interfacing with a decentralised server 111.

[0093] The community ecosystem infrastructure 110 may provide data security and privacy controls. All data stored within the community ecosystem infrastructure 110, or in storage controlled / integrated with the community ecosystem infrastructure 110, may be encrypted storage at rest and in transit. Strict access controls may be implemented, with each entity having an associated role (being a role player) within the infrastructure 110. Each role may have role-based access with audit logging. All use of data may be General Data Protection Regulation (GDPR) compliant, allowing compliant privacy policy acceptance and data portability. Advanced authentication methods, such as Cognito-based identity management, may be implemented.

[0094] The community ecosystem infrastructure 110 may adhere to privacy by design concepts, such as minimal data collection, consent management, data retention, and entity control. Minimal data collection may include only collecting data necessary for trust assessment with the trust scoring mechanism. The consent management may provide clear terms of service and include a tag for privacy policy acceptance by the entity. Data retention may include requirements for data retention, including defined retention periods for different data types. Entity control may include a set of controls, selected by the entity, to manage their profile and verification (endorsement) data.

[0095] The provided system may be usable for business intelligence for financial services. For example, the system may be usable for credit assessment support. Individual risk profiles for entities may be determined for comprehensive trust assessment for loan applications. A community verification system using neighbour-based identity and residency verification may be provided. Property value assessment, ownership verification and property documentation may be provided for rural communities. Payment history indicators, such as tenant payment frequency and reliability data may be collected. The system may provide for geographic market analysis. Community trust density may be determined to identify high-trust areas for service expansion. Local market penetration may be documented by tracking user adoption and engagement by area. Risk distribution mapping of credit risks by geographic distribution can be determined. Community leader identification can be used for local influencers for partnership.

[0096] The system 100 described above may implement a method 200 for providing a community ecosystem infrastructure. Exemplary methods 200,250 for providing a community ecosystem infrastructure are illustrated in the flow diagrams of Figure 2A and 2B.

[0097] The method 200 may include providing 210 a community ecosystem infrastructure. Providing 210 the community ecosystem infrastructure may include providing the relationship management system. Providing 210 the community ecosystem infrastructure may include providing the register 114. Providing 200 the community ecosystem infrastructure may include provisioning a server computer for hosting the ecosystem infrastructure.

[0098] The method 200 may include a step of registering 211 entities 121 in the ecosystem infrastructure. The entities may be registered as role players within the community. Registering entities may include integrating with an external identification resource. The method includes providing 212 ecosystem services 152. Providing ecosystem services may include asset registration and trading services. In some examples, the assets for asset registration may include property. Providing ecosystem services may include financing services. Providing ecosystem services may include security services. Providing ecosystem services may include environmental services. Providing ecosystem services may include providing trading services.

[0099] The method includes providing 213 a platform to the registered entities to provide goods and services 154 to other registered entities. The method includes providing 214 training to registered entities thereby providing entity certification 156 for offering goods and services. The step of providing training may include: providing online training at multiple levels, providing online guideline contract documents at multiple levels, and providing training certifications. The training provides certification to the goods and services offered by the entities via the platform. The method includes providing 215 integrations to external resources 160 for external services provided to the registered entities. In the example of a property asset (immovable property), the method may access an external resource of the deeds office.

[0100] The community ecosystem infrastructure may include generating income streams for registered entities by referrals of new entities to expand the ecosystem or by franchising-related options. The order of the method steps may vary from the arrangement presented in Figure 2A and may occur in any suitable order.

[0101] In the example illustrated in Figure 2B, the method 250 is shown starting with an entity initialisation 251 where an entity is identified (the entity being a trusted party 123), such as a community leader, approached and informed of the benefits of the community ecosystem infrastructure. A new entity may register with the community ecosystem infrastructure. The entity may download the application onto the entity device. For example, the entity may receive, on the entity device, a message with a link to download the application. The message may be received on a messaging service, such as WhatsApp™. In some examples, the message may be sent via the server 111 to verify that the message was sent, and that message tracking may be performed. In some examples, a record of all communication between the server and each entity device registered with the server may be stored, enabling auditing of registrations and response messages from verifying requests.

[0102] The new entity member supplies personal information during registration 252 and may submit an application 253 for membership. The application is reviewed, and the identity may be verified 254 via an external resource and, if sufficient, approval will be issued. Depending on the community entity member’s role, they may require training 255. Further steps may be provided, including: certification (i.e. tangible property); funding; support and monitoring; and expansion. The community entity member may provide 256 goods and services to other entity members. The new entity may add and / or invite neighbours associated with the entity.

[0103] The system 100 described above may implement a method for a community ecosystem infrastructure. An exemplary method for a community ecosystem infrastructure is illustrated in the swim-lane flow diagram of Figure 3A and 3B in which respective swim-lanes delineate steps, operations or procedures performed by respective entities or devices.

[0104] Figure 3A illustrates an example method 300 for registering an asset on the community ecosystem infrastructure. The method may include steps conducted at an entity device 104 of an entity 102. The entity 102 may have a related asset 115 that they wish to verify as belonging to them. Alternatively, the entity device 104 may belong to an associated entity that is acting on behalf of the entity 102 in the role of an agent, or representative. The entity may first be verified 304 with the infrastructure 110 before being provided access. Verifying 304 the entity may include the entity taking a photo of their face. The entity device may transmit the photo to a facial verification service. The photo may be transmitted via the facial recognition API 131.

[0105] The entity may obtain 301 asset data related to the asset. For example, the asset data may include an image 171A and image metadata 171 B. The image metadata 171 B may include GPS coordinates of the entity device when the image 171 A was obtained. The entity may take a photo, using the entity device 104, of the asset. The photo may be taken through a camera functionality of the entity device.

[0106] The entity device 104 may transmit 302 the asset data to the server. The server may determine a certification of association of the asset to the entity. The entity device 104 may receive 303 a response from the server indicating whether the verification was approved or rejected. An approved response may include the certification of association (i.e., proof-of-ownership) being received at the entity device.

[0107] The method 300 may include steps conducted at the server 111 of the community ecosystem infrastructure 110. The server may receive 310 asset data from the entity device. Receiving the asset data may include receiving asset metadata. For example, the asset data may include an image 171 A and image metadata 171 B of the asset. The server may transmit 312 the asset data to an external resource. For example, the external resource may be a geospatial service 138. The server may receive 314 geographical information associated with the asset data from the geospatial service 138. The geographical information may include a standardised address 171 C, a SG21 digit code, ownership data, spatial visualisation information, and / or a GPS coordinate.

[0108] The relationship management system may process the geographical information 171 C, image 171A and image metadata 171 B together to determine a set of verifying devices 127. The verifying devices may be selected according to a trust score criteria and / or a geographical criterion. For example, verifying devices within a predefined proximity of the GPS coordinate may be selected. In some examples, verifying devices with a trust score above a predetermined threshold are selected.

[0109] The server may transmit 316 a request to verify an association of the asset. The server may transmit 316 the request to verify an association of the asset to the entity to a plurality of verifying entity devices 127. The plurality of verifying entity devices may be selected by the relationship management system. For example, the number of verifying entities may include seven different entities. The server may determine the verifying entities using a radius-based user discovery method, such that trusted entities (having a trust score above a predefined threshold) within a predefined radius (such as 1 to 5 kilometres) of the entity are selected. In some examples, the server may use geographic trust mapping, by selecting verified entities according to trust score distributions across communities. In some examples, verifying entities are selected based on a trust score associated with the specific address of each verifying entity. The verification system may perform a trust network mapping, including a network analysis and risk assessment. The trust network mapping may include a complete network analysis, providing an overview of an entity’s trust connections. The verification system may perform an endorsement flow analysis, providing a network of which entities are verifying entities for each other and strengths of relationships. The verification system may perform a bi-directional relationship tracking to analyse which verifications are provided by one entity to another entity versus verifications received. The verification system may perform a network density analysis, providing insights into how connected community members are. In some examples the network density analysis may provide a numerical quantification of connectedness.

[0110] The verification system may perform risk assessment analytics. The verification system may rank entities with the largest trust scores. The verification system may perform an endorsement pattern analysis to identify potentially fraudulent patterns of verifications. The verification system may perform a geographic clustering analysis to verify that verifications originate from actual neighbours geographically proximate the entity. The verification system may perform a historical trend analysis to track trust scores over time and log changes to trust scores.

[0111] The plurality of verifying devices 127 may each transmit an approval or rejection of the verification of association of the entity to the asset. The server may receive 318 a response from one or more of the verifying devices 127. The response may indicate approval or rejection of an association between the asset and the entity. The server may extract an approval or rejection from the response. The request may be transmitted to an application operating on each of the verifying devices. In some examples, the request may be transmitted to a messaging service operating on each of the verifying devices, such as WhatsApp™.

[0112] The server may determine 320 a certification of association of the asset by the entity. The certification of association may indicate that the asset belongs to the entity. Determining 320 the certification of association may include inputting the response from the verifying entity devices into the verification system. The verification system may include a graph network for efficient traversal of relationships between nodes (which may represent entities), providing for: efficient verification of approvals or rejections; anomaly detection; adjustments to approvals and the like which may be made; and, establishing of trust networks.

[0113] The server may detect fraudulent activities. Fraud prevention is a key focus of the platform, with mechanisms in place to detect circular endorsements, limit endorsement frequency, and adjust trust scores dynamically based on historical accuracy. The server may perform benchmarking of trust scores. Benchmarking trust scores may include determining percentile rankings, comparisons against verified users, and regional normalization. The server may analyse endorsement patterns over time, refining weightings and detecting inconsistencies that could indicate manipulation. The server may perform a re-calibration of the trust model to ensure that trust levels remain meaningful across different geographic and social contexts.

[0114] The received responses may be input into a trust model. The trust model may be configured to output an approval or rejection of the certification of association based on the received response. The verification system may determine whether a verification was received by a geographic neighbour of the entity. The verification system may determine whether a verifying entity is well- integrated in their community, for example, based on the verifying entity’s trust score. The verification system may identify suspicious verification patterns, influencing the trust score of the relevant verifying entity. The verification system may determine whether a verifying entity is a community member with a higher trust score relative to other entities in the community.

[0115] The verification system may output an approval or rejection of if the certification of association is to be provided to the entity. In response to determining an approval of the certification of association between the asset and the entity, the server may issue a certificate. The certificate may indicate an approval of association of the asset. The certificate may be usable on the community ecosystem infrastructure as a proof-of-ownership of the asset with services. If the verification system determines that a certification of association is approved, the server may transmit 322 the certification of association to the entity device 104.

[0116] In some examples if an asset is associated with an entity, the server may receive, from the entity device, a transfer request. The transfer request may include asset data and an identifier of a receiving entity. The request may be a request for transferring the certification of association of the asset to the receiving entity. For example, the receiving entity may purchase the asset from the entity. The entity may initiate a transfer of ownership by transmitting, from the entity device, the transfer request.

[0117] The entity may permit another utilising entity to utilise the asset. The server may receive a utilisation request. The utilisation request may include a request permitting a utilising entity to utilise the asset. The utilisation request may include identification details of the utilising entity. The server may associate the asset to the utilising entity. Associating the asset to the utilising entity may include providing a temporary certificate of association to the utilising entity.

[0118] Figure 3B illustrates an example method 350 for providing approval or rejection of an asset of a second entity within the community ecosystem infrastructure. The method 350 may include transmitting 360, from a second entity device 105, second asset data to the server 111. The second asset data may be asset data associated with a second asset. The second asset may be an asset related to a second entity. The server 111 may receive the second asset data 362. The server may process the second asset data similarly to that of the asset data in Figure 3A.

[0119] The server may transmit 364 a request to the entity device 104 to verify an association of the second asset to the second entity. The entity device 104 may receive 366 the request to verify an association of a second asset to a second entity.

[0120] The entity device may output 368 a prompt to the entity device 104. The prompt may be output to verify an association between the second asset and the second entity. The prompt may be output at a display of the entity device 104. The entity device may receive 370 an input from the entity 102. The input may indicate an approval or rejection of the association of the second asset to the second entity. The input may include the entity verifying their identity using the facial recognition API. Verifying the identity may include capturing biometric information of the entity, such as a photo of a face of the entity. The entity device may format the input into a response for transmitting to the server. The entity device may transmit 372 the input to the server 111. The server may receive 374 the response from the entity device 104.

[0121] The terms artificial intelligence (Al), machine learning, and deep learning may be used interchangeably throughout this disclosure when referring to trained Al models. Al models may be utilised in various parts of the infrastructure 110. For example, Al models may be used for providing valuations of assets in the register, and / or as part of the verification system.

[0122] Machine learning may be considered a sub-branch of Al and deep learning may be considered a sub-branch of machine learning. Deep learning is a form of machine learning that uses a layered network, referred to as an artificial neural network (ANN). Any Al, machine learning and deep learning system may rely on an underlying model. The model may be tailored to a specific use case. Although Al is considered the broadest of term, it is common that any Al system includes some form of machine learning, with some systems further including deep learning. Some examples of machine learning models may include, but are not limited to: decision trees, random forest regression, support-vector machines, K-means clustering, regression analysis, Gaussian processes, and the like.

[0123] Machine learning models (as well as deep learning models) may be categorised into classification or regression. Classification models may classify an input into one or more of a set of classifications, with the output being one of discrete classifications. Regression models may determine an output that may be a value or output across a continuous output range. A regression model may estimate a relationship between an input to an output. The graph network configured to output a certification of association may be a classification type model.

[0124] ANNs may include a variety of structures, which are referred to as architectures. Different architectures are suitable for different use cases. Examples of ANN architectures may include convolutional neural networks or recurrent neural networks. Convolutional neural networks may be suitable for image-based data or multi-dimensional input data. Recurrent neural networks, such as long-short term memory networks, may be more suitable for time series applications. Graph networks may be suited to problems that may be modelled using a plurality of nodes and edges. The nodes may represent discrete actors and edges may represent interactions between the actors.

[0125] An ANN may consist of interconnected units, commonly referred to as neurons, as they are inspired by and resemble neurons of the brain. The units may be made up of nodes and edges forming a connected network. The edges may connect nodes together. ANNs may be configured in the form of a layered structure with an input at the first layer and an output provided by the final layer. The layers between the first layer and final layer are hidden layers.

[0126] The input layer may include one or more nodes. An edge may extend from each node. Each edge may be connected to a node in a subsequent hidden or output layer. Each node may include more than one edge that connects the node to a plurality of other nodes in other layers. In some examples, an edge may feedback into a previous node in a preceding layer (a node not in subsequent layers but in a further layer), or to a different node in the same layer.

[0127] The output of a node may be computed by an activation function, which may be a linear or a nonlinear function of the sum of the inputs into each node in each layer. The output value of each node in the preceding layer is multiplied by a weighting value, which determines the strength of each nodes’ output value. Finally, the value that is determined at the node(s) of the final layer is the output of the ANN. For regression type ANNs, the output may contain only a single node with a value, or many nodes. For classification type ANNs, the output may include multiple nodes, where each node is an output of the probability of a classification type.

[0128] More complex ANNs are better suited to specific tasks. In addition to the weights and activation functions of a regular ANN, a convolutional neural network applies a filter (or a kernel) onto a two- dimensional data structure, which may reduce the number of edges between the hidden layers in the neural network. This may in turn reduce the number of weights within the neural network. A convolutional neural network may find application in image-based tasks, where image data may be structured as a two-dimensional data structure. A convolutional neural network may be extended into further dimensions by increasing the dimensions of the filter / kernel to match the number of dimensions of the input data.

[0129] Recurrent neural networks include a recurrent unit. This recurrent unit may maintain a hidden state over time, thereby providing a pseudo-memory capability. Such models may find application in time series or sequential operations, such as speech or text. Multiple recurrent units may be connected to each other, where the output of one unit at a first timestep may be used as an input into another recurrent unit at a second timestep. Examples of recurrent neural networks include, but are not limited to, long short-term memory networks, and gated recurrent units. Transformers are another form of deep learning architectures well suited for sequential based data. Transformers may utilise a self-attention mechanism instead of recurrence (such as in a recurrent neural network).

[0130] A trained Al model may be configured to run on a computing device, such as a Raspberry Pi ™, a NVIDIA Jetson Nano ™ developer kit, or a standard personal computer (PC) including a graphical processing unit (GPU). Example computing devices may be designed to perform specific computational tasks, which may include running multiple neural networks in parallel for applications including image classification, object detection, segmentation, and speech processing. In some cases, a trained Al model may be configured to run on a computing device in the form of a large computing system, such as a computing cluster (such as that found in a data centre).

[0131] T raining Al models may be a computationally intensive and time consuming. Models may thus be trained on a computing device provided by a large computing infrastructure or a cloud computing infrastructure that can be accessed over a network. These resources allow for dynamic computing resources to be dedicated to training a deep neural network, after which the trained model can be downloaded to run on a separate application.

[0132] Figure 4 illustrates a general overview of training and use of machine learning models 414 in accordance with aspects of the present disclosure. The training may include a data preparation process 411 that formats a raw incoming data 410. The data preparation process 411 may prepare training data 412. The data preparation process 4114 may involve labelling the raw incoming data 410. Labelling the raw incoming data 4104 may include labelling each input data of the raw incoming data 410. Labelling the data may include providing a known value or solution that must be output by the model when a specific data is input into the model. For example, the raw incoming data may be previous verification response from a plurality of verifying entities 127, where an association between an entity 102 and an asset 115 is known.

[0133] The data preparation process 411 may include formatting the raw incoming data 410 into a format suitable for the type of model or in the case of an ANN, suitable for the model architecture. For example, the process 411 may include formatting the data for a graph network. The data preparation process 411 may generate the training data 412. The training data 412 may include a subset of data called validation data. The model may be trained using the training data 412, but excluding the validation data. The validation data may be used within a training process 413 to determine an accuracy level of the model on “unseen” input data. The validation data may be applied to the model during and after training.

[0134] The training process 413 may receive the training data 412 and iteratively update the model until a predefined quality criteria and / or accuracy criteria are achieved. The model 414 may be output at the end of the training process 413 to be used in a runtime process 422. For example, if the model, such as the trust model, is a graph network, iteratively updating the model may include adjusting model weights 181. The training process may include providing online guideline contract documents at multiple levels; this may require calibrating or re-calibrating within the verification system.

[0135] Calibrating, or re-calibrating the model may include re-training the model. During operation of the model within the verification system, the model may be re-calibrated (or re-trained) based on triggering events. For example, a trusted entity may be removed from the list of trusted entities, and no longer able to provide trust-worthy approval or rejection of an association between assets and entities. The non-trustworthy entity is removed (node is removed or weights set to zero) and the model is re-calibrated such that it may accurately determine whether an association between the asset and entity exists based on responses from verifying devices. In some examples, an entity may move locations and may no longer be close to other entities. The model weights 181 may be updated such that two entities located relative far away from each other have a smaller influence on determining the trust score.

[0136] The model 414 may be trained using a training method. The training method may include any one of: supervised learning, unsupervised learning, semi-supervised, and reinforcement learning. The training process 413 may include using a plurality of training methods. Supervised learning may require labelled training data 412, such that the correct output is known for each training data input. The task of the training process 413 is to minimize the difference (or error) between the output of the model 414 and the known output (for example, due to the labelling process) of the training data 412.. The training procedure modifies the machine learning model 413 such that the difference (or error) is minimized. Unsupervised learning may be configured to extract features or patterns from unlabelled data. Unsupervised learning may be used when the raw incoming data 410 is too large to be labelled. For example, unsupervised learning may be used for autoencoders, where the aim is for the model output to match the model input by encoding the input data, and decoding the encoded input data.

[0137] When the model 414 is in use, an input 421 may be received into the runtime process 422 that uses the model 414 to obtain an output 423 that may be used in a downstream process 424. The computation of the runtime process 422 is often referred to as ‘inference’. For example, when an entity 102 requests verification of an association with an asset 115, a node related to the entity may be determined. Nodes of verifying entities 127 may be determined based on selected verifying entities 127. A value of one may be assigned the node of the entity 102 and verifying entities 127, and a value of zero to all other entities. The value at each node of each verifying entity may be changed based on whether their response is an approval or rejection of the association. The value of the nodes may be multiplied by the model weight between the node of each verifying entity and the node of the entity. The trust score may be a sum or weighted average of the multiplication step. In some examples, the trust score may be normalised between zero and one. The association may be approved if the trust score is above a predefined threshold.

[0138] The training process 413 may be computationally demanding and time consuming. To successfully train a machine learning model, very large datasets may be used which are stored on a database. The training process may be performed on a computing device in the form of a large computing cluster which may access the database to obtain the training data when required. Additionally, the trained machine learning model 414 may be stored on the database. The runtime process 422 may run on an end user computing device by downloading the machine learning model 414 over a network from a database, or the runtime process 422 may run on a large computing infrastructure such as a computing cluster. An example embodiment of interacting with the machine learning model 414 may include an end user computing device, such as a mobile device or a computer which may obtain or be the source of the input data 421 , transmit the input data 421 over a network to a computing cluster to perform the runtime process 422. Alternatively, an end user computing device may obtain the machine learning model from a database over a network and store the machine learning model locally on the device. The end user device may obtain an input data 421 and perform the runtime process 422 locally on the device to obtain an output 432. By performing the runtime process 422 locally on the device, the input data 421 does not need to be transmitted over a network, reducing bandwidth usage. This may be referred to as ‘on-the-edge’ computing.

[0139] The provided system and method may support various analytics services. Trust scoring analytics examples are provided below. Individual trust scoring may include examining a specific entity. The entity may have a system-generated identifier, name, trust score (for example, 87.3 / 100), a community duration (for example, 8 years), a residency status (for example, as an owner), a property address, and a mobile phone number.

[0140] An endorsement analysis may be performed on the entity profile. The endorsement analysis may measure a total number of endorsements received (for example: 5); and average endorsement strength (for example: 84.2) indicating the trust score of verifying entities; a number of neighbour endorsements from actual geographic neighbours (for example: 3); a community integration score (for example: 91.5). The endorsement analysis may collate entity profiles of entities that were verifying entities, including the trust score, geographic proximity of each verifying entity, if they are a neighbour or not, a duration in the community, if they are a business owner in the community, and the like. The individual trust scoring may output a risk assessment of the entity (for example, LOW RISK). The individual trust scoring may indicate if the entity has been: geographically validated (by multiple neighbour endorsements); a long-term resident in the community; and whether the entity is an owner of the property through verified ownership (through a certification of association).

[0141] Geographical trust scoring may be provided. The geographical trust scoring may include a trust distribution by area (for example, within 1 kilometre radius samples). The geographical trust scoring may include a GPS centre, being a GPS coordinate of the centre of a circle area, and a radius. The geographical trust scoring may include an area description, such as a suburb name. The geographical trust scoring may include: a number of entities within the radius; an average trust score of the entities within the radius; a number of entities with a high-level of trust (for example, the number of entities with a trust score above 80 / 100); a number of entities with a medium-level of trust (for example, the number of entities with a trust score between 60 / 100 and 80 / 100); and, a number of entities with a low-level of trust (for example, the number of entities with a trust score below 60 / 100)

[0142] The system and method may provide network analysis results, including community trust network metrics. The community trust network metrics may include a total number of active entities (for example: 100), a total number of properties (for example: 100), a total number of endorsements (for example: 47), and an average number of endorsements per entity (for example: 0.47). The network analysis may include a network density analysis, including: number of entities with more than a provided threshold of endorsements (for example: 15 users (15%)); a number of entities with neighbour endorsements (for example: 8 users (8%)); a number of geographic endorsement clusters: (for example: 4); and, an average distance between endorser / endorsed (for example: 385 meters). The network analysis may provide a list of most connected entities or top trust network hubs, including: the name, number of endorsements provided (being verifications provided when prompted to verify and association), and number of endorsements received.

[0143] The system and method may provide risk assessment analytics, such as fraud detection patterns. The risk assessment analytics may provide endorsement pattern analysis, including: geographic validation (for example 89% of endorsements are from entities within 1km); mutual endorsements (for example, 34% bidirectional endorsement rate); cluster analysis (for example, no suspicious endorsement clusters detected); and temporal patterns (for example, endorsements distributed normally over time).

[0144] The risk assessment may include risk flags detection. Example flags may include: 0 users with all endorsements from within 5km distance; 0 users with endorsement timestamps clustered within 24 hours; and, 2 users with single endorsements (flagged for additional verification).

[0145] The system and method may provide business intelligence queries & results. For example, a first query may be to find high-trust users within a 2km radius for loan targeting results. The first query may output: a name, trust score, address, and relationship type (such as owns, rents, or lives in). A second query may be to find neighbour verified users for premium services results. The second query may output: a name, trust score, number of neighbour endorsements, and average strength (being an average trust score).

[0146] The system and method may provide real-time analytics dashboard metrics, including daily trust network activity. For example: Monday: 2 new endorsements, 1 user verification; Tuesday: 1 new endorsement, 0 user verifications; Wednesday: 3 new endorsements, 2 user verifications; Thursday: 1 new endorsement, 1 user verification; Friday: 4 new endorsements, 2 user verifications; Saturday: 0 new endorsements, 0 user verifications; Sunday: 1 new endorsement, 1 user verification. The real-time analytics dashboard metrics may include weekly growth numbers, including: new users; new properties; new endorsements; trust score improvements; community expansion.

[0147] The real-time analytics dashboard metrics may include trust score distribution analysis, including trust score ranges: For example: trust score between 90-100 may be classified as premium credit candidates; trust score between 80-89 may be classified as standard credit approved; trust score between 70-79 may be classified as basic services eligible; trust score between 60-69: may be classified as community banking services; trust score between 50-59: may be classified as requires additional verification; trust score between 0-49: may be classified as high risk I insufficient data. The real-time analytics dashboard metrics may include an average community trust score (for example 67.8 / 100); and a trend analysis over a time period of how the average trust score changes (for example: 30 days):

[0148] The system and method may include a financial services integration, for example, a loan application risk assessment. An assessment request may include an entity’s name, systemgenerated identifier, a loan amount requested, and a purpose of the loan (for example, small business expansion)

[0149] The community ecosystem infrastructure may perform a trust assessment. The community ecosystem infrastructure may provide: a trust score of the entity; a high / medium / low trust score rating; community duration; and stable / unstable community duration rating; number of neighbour endorsements; property relationships; payment pattern indicator (for example, consistent rental payer); geographic verification; community integration (for example, active endorser and number of endorsements given; a risk rating (for example, LOW-MEDIUM); and a recommended action (for example, APPROVE with standard terms).

[0150] Additional Verifications may be provided, such as property owner contact details; community references, and emergency contact details.

[0151] Referring to Figure 5, an example embodiment of a system providing the community ecosystem infrastructure is shown. The ecosystem infrastructure may include a relationship management system 510 that may be provided on a computing system 500 (such as a server computer) and entity applications 521 that may be provided on an entity device 520 such as a mobile device or a personal computer of the entities. The entity application 521 may be used for accessing the community ecosystem infrastructure and ecosystem services for registered entities. The ecosystem infrastructure may include integration with external resources 530.

[0152] A relationship management system 510 may be provided on a computing system 500 having a processor 501 for executing the functions of components described below, which may be provided by hardware or by software units executing on the computing system 500. The software units may be stored in a memory component 502 and instructions may be provided to the processor 501 to carry out the functionality of the described components. In some cases, for example in a cloud computing implementation, software units arranged to manage and / or process data on behalf of the relationship management system 510 may be provided remotely.

[0153] The computing system 500 includes an entity registration component 511 arranged to register entities within the infrastructure. The entities may be registered as role players within the community. The entity registration component 511 may integrate with an external resource 530 that provides identification checks.

[0154] The computing system 500 includes an ecosystem services component 512 arranged to provide ecosystem services to the registered entities. The ecosystem services component may include providing asset registration and trading services. The ecosystem services component may include providing financing services. The ecosystem services component may include providing security services. The ecosystem services component may include providing environmental services. The ecosystem services component may include providing trading services.

[0155] The computing system 500 includes a platform component 513 arranged to register entities to provide goods and services to other registered entities. The relationship management system 510 includes a training component 514 for providing training to registered entities thereby providing certification for offering goods and services to other registered entities. The training component 514 may provide online training at multiple levels. The training component may provide training certifications.

[0156] The computing system 500 includes an integration component 515 arranged to provide integration to external resources for external services provided to the registered entities. The integration component 515 may provide APIs to external resources 530 for integration of their external services. External resources 530 may include property deeds office, car registration office, home affairs, credit bureau, document signing services, etc. The relationship management system 510 may include an income generating component 516 for generating income streams for registered entities by referrals of new entities to expand the ecosystem.

[0157] The computing system 500 may include an asset data receiving component 540 arranged to receive asset data related to the asset. The computing system 500 may include a geographical information receiving component 540 arranged to receive geographical information associated with the asset data from a geographical information register. The computing system 500 may include a request transmitting component 544 arranged to transmit, to a plurality of verifying entities, a request to verify an association of the entity to the asset. The computing system 500 may include a verification receiving component 546 arranged to receive, from each of the plurality of verifying entities, a response indicating an association between the asset and the entity. The computing system 500 may include an ownership determining component 548 arranged to determine, based on the received responses, a proof-of-ownership of the asset by the entity. The components may be provided by the relationship management system 510 of the computing system 500.

[0158] Figure 6 illustrates an example of a computing device 600 in which various aspects of the disclosure may be implemented. The computing device 600 may provide the computing system 500 on which the relationship management system 510 is provided. The computing device 600 may provide the entity devices 520 on which entity applications 521 are provided.

[0159] The computing device 600 may be embodied as any form of data processing device including a personal computing device (e.g. laptop or desktop computer), a server computer (which may be self-contained, physically distributed over several locations), a client computer, or a communication device, such as a mobile phone (e.g. cellular telephone), satellite phone, tablet computer, personal digital assistant or the like. Different embodiments of the computing device may dictate the inclusion or exclusion of various components or subsystems described below.

[0160] The computing device 600 may be suitable for storing and executing computer program code. The various participants and elements in the previously described system diagrams may use any suitable number of subsystems or components of the computing device 600 to facilitate the functions described herein. The computing device 600 may include subsystems or components interconnected via a communication infrastructure 605 (for example, a communications bus, a network, etc.). The computing device 600 may include one or more processors 610 and at least one memory component in the form of computer-readable media. The one or more processors 610 may include one or more of: CPUs, graphical processing units (GPUs), microprocessors, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs) and the like. In some configurations, a number of processors may be provided and may be arranged to carry out calculations simultaneously. In some implementations various subsystems or components of the computing device 600 may be distributed over a number of physical locations (e.g. in a distributed, cluster or cloud-based computing configuration) and appropriate software units may be arranged to manage and / or process data on behalf of remote devices.

[0161] The memory components may include system memory 615, which may include read only memory (ROM) and random access memory (RAM). A basic input / output system (BIOS) may be stored in ROM. System software may be stored in the system memory 615 including operating system software. The memory components may also include secondary memory 620. The secondary memory 620 may include a fixed disk 621 , such as a hard disk drive, and, optionally, one or more storage interfaces 622 for interfacing with storage components 623, such as removable storage components (e.g. magnetic tape, optical disk, flash memory drive, external hard drive, removable memory chip, etc.), network attached storage components (e.g. NAS drives), remote storage components (e.g. cloud-based storage) or the like.

[0162] The computing device 600 may include an external communications interface 630 for operation of the computing device 600 in a networked environment enabling transfer of data between multiple computing devices 600 and / or the Internet. Data transferred via the external communications interface 630 may be in the form of signals, which may be electronic, electromagnetic, optical, radio, or other types of signal. The external communications interface 630 may enable communication of data between the computing device 600 and other computing devices including servers and external storage facilities. Web services may be accessible by and / or from the computing device 600 via the communications interface 630.

[0163] The external communications interface 630 may be configured for connection to wireless communication channels (e.g., a cellular telephone network, wireless local area network (e.g. using Wi-Fi™), satellite-phone network, Satellite Internet Network, etc.) and may include an associated wireless transfer element, such as an antenna and associated circuitry. The external communications interface 630 may include a subscriber identity module (SIM) in the form of an integrated circuit that stores an international mobile subscriber identity, and the related key used to identify and authenticate a subscriber using the computing device 600. One or more subscriber identity modules may be removable from or embedded in the computing device 600.

[0164] The computer-readable media in the form of the various memory components may provide storage of computer-executable instructions, data structures, program modules, software units and other data. A computer program product may be provided by a computer-readable medium having stored computer-readable program code executable by the central processor 610. A computer program product may be provided by a non-transient or non-transitory computer- readable medium or may be provided via a signal or other transient or transitory means via the communications interface 630.

[0165] Interconnection via the communication infrastructure 605 allows the one or more processors 610 to communicate with each subsystem or component and to control the execution of instructions from the memory components, as well as the exchange of information between subsystems or components. Peripherals (such as printers, scanners, cameras, or the like) and input / output (I / O) devices (such as a mouse, touchpad, keyboard, microphone, touch-sensitive display, input buttons, speakers and the like) may couple to or be integrally formed with the computing device 600 either directly or via an I / O controller 635. One or more displays 645 (which may be touch- sensitive displays) may be coupled to or integrally formed with the computing device 600 via a display or video adapter 640.

[0166] Detailed description of example embodiments of the Community Ecosystem Infrastructure.

[0167] The method and system aim to create a comprehensive register for properties, vehicles, and other valuable assets, and establish clear ownership of these assets. It aims to provide reliable proof of asset ownership and facilitate the trading, sale, enhancement, encumbrance, leasing, and overall use of these assets. Funding and finance-related services may be provided, contributing to wealth creation for both asset owners and participants within the community. Further goals may include aiming to enhance convenience, increase income, reduce costs, improve comfort, and ensure safety. The system and method may be configured to allow for the dependable identification of all community participants / entities.

[0168] The method and system are designed to be profitable by leveraging several cash flow streams. These may include charges to users of the register and valuation services, where information is presented in an Annualised Break-Even Rate Stack-Up Model (Return on Equity Model) to assist financial services users with profitability modelling. Additionally, revenue may be generated through commissions from property trades via estate agencies, interest and fees from advanced credit, franchise fees, subscription fees, app registration fees, and debit and credit card interest and fees. Investment income and insurance premium income may further contribute to the financial robustness of the method and system. It is designed to aim to enhance people's and property’s sense of dignity by enabling financial growth, safety, employment, and wealth through a franchise model, a community intelligence platform / app, and collaboration with data intelligence workers and partners. An initiative of the present disclosure aims to boost social and environmental well-being by addressing gaps in housing, mobility, education, connectivity, security, solar power, water, and services, supporting waste recycling, and high-density housing for a greener planet. The broad purpose is to try and empower community members to excel by utilizing digitally driven property registration and data-driven intelligence, providing them access to credit and opportunities for wealth growth.

[0169] This solution may provide purpose-driven, cloud-native, blockchain-type registration and verification for digital application assets, including ownership, property improvements, and building extensions. It may incorporate Al and agent or valuer-driven valuations to assist in accurate assessments. The system may also support registered rentals, liens, and trades, offering integrated credit, insurance, investment, authentication, and security subsystems. It may operate on an end-to-end franchise model that may include contributions from non-citizens. Additionally, the app may be integrated with partners via APIs and core modules, such as member relationship management and e-learning.

[0170] Technologies such as satellite imagery and other tracking systems, along with the integration of machine learning, Al, virtual property tours, and automated assistance, can be used to support property registration and asset validation.

[0171] E-pegs, or electronic pegs, may provide geospatial data for identifying and marking property boundaries and locations. They may offer digital markers for property lines, which can be useful for registration and avoiding disputes. By providing location data, e-pegs may help in assessing the value of the property more accurately. This may contribute to the digitalization of property records, making it easier to manage and retrieve information. E-pegs may integrate with GIS (Geographic Information Systems) and other mapping technologies to provide datapoints for property details.

[0172] The infrastructure may include community intelligence to create data required to decrease cost of capital / borrowing.

[0173] The ecosystem infrastructure may obtain, enrich, package and collaborate data from entities to decrease pricing, origination cost, maintenance cost, risk premiums (probability of default, loss given default, source of income and affordability), and weighted cost of capital i.e. the cost of institutional borrowing and funding and the required return / perceived risk to investors. The enriched data may reduce interest rates, towards secured and prime levels. In some examples, where the assets are property, the asset may be recognised as being associated with entities and appreciate in value, while loan-to-value is increased in lending policies. Lenders may be ready to consume this into their Annualised Break-even Rate-stack-up Pricing Models and Capital Planning.

[0174] The method and system may be implemented within a community. Various role players may be involved to facilitate numerous interactions between community members and support growth of local businesses.

[0175] Examples of applications of the ecosystem include:

[0176] Building Projects: approving the financing for building projects and issuing the necessary funds. New Business Ventures: supports new business ventures by facilitating the establishment of various franchises, such as security, driver, car sales, and e-scooter services. This support includes approving applications, providing necessary funding and credit facilities, assisting with franchise registration and training, and offering loans for initial costs.

[0177] Community Integration: engages new merchants and franchisees, including non-local individuals, by facilitating their registration and integration into the system. Property Management and Sales: contributes to boosting property sales and values through its involvement in improved business practices and property management. General Support: provides loans, funding, training, and certification for various business ventures and personal needs, supporting growth and success within the community.

[0178] Case Study and Example

[0179] The following examples are provided of how the system, and method may be implemented within a community. There are numerous areas where the system and method may be implemented and several branches of business where it may be employed. Throughout the following paragraphs, wherever reference is made to the “ENTERPRISE” this refers to the community ecosystem infrastructure.

[0180] To become established, the ENTERPRISE partnered with a business to determine the geographic coordinates for properties lacking existing diagrams and title deeds, enabling the issuance of ENTERPRISE Digital Certificates of Ownership. They collaborated with a business to assess the value of properties without recognized valuations, making it possible to offer loan facilities to property owners. ENTERPRISE worked with ENTERPRISE Investment Fund Nr 1 to attract investors. These investments were structured to offer competitive interest rates and secure home bonds or other forms of collateral, such as instalment sale agreements, to provide funding for home, car, and other asset loans. House ownership verification categories, owner credit scores, and valuation levels help determine asset classes for investment tranches and the associated risk-return profiles.

[0181] Additionally, information from ENTERPRISE members improves credit scoring (enhanced Probability of Default modelling) and affordability assessments. All members' net income, obligations, and expenses are recorded and regularly updated on the ENTERPRISE app (being the application operating on the entity device), optimizing loan amounts, ensuring responsible lending, and calculating Exposure at Default. The Loss Given Default is kept low, controlled by ongoing valuation improvements and security measures, which are enhanced by operational intelligence from agents and enriched data within the register, such as property ownership and instalment sale agreements over assets. As the data becomes more comprehensive, credit interest rates are expected to improve, and members will qualify for better credit scores, affordability, and valuations. Credit providers, including ENTERPRISE Investment Fund Nr 1 , banks, and others, will benefit from more refined Annualized Break-Even Rate models, ensuring strong investment returns and profitability. Equivalent data enhancements will improve probability and profitability models for other investment funds, such as ENTERPRISE Investment Fund Nr. 2 (below), and insurance structures (e.g. Cell-captive against fund Nr. 3) within the ENTERPRISE and its partners.

[0182] The ENTERPRISE partnered with ENTERPRISE Investment Fund Nr 2 to find investors interested in purchasing houses and apartments, renting them out to generate steady rental income, and achieving strong returns on investment and capital growth.

[0183] As example, the ENTERPRISE began their operations in “Protea Estate” (a fictional area used throughout the following example) to show how the method and system can be implemented within a community. In this example, the process is started with the community leaders and then moves to the broader community members.

[0184] The following role players are mentioned:

[0185] 1 . Sandra - A resident of Protea Estate who undertakes building projects and eventually starts a security business.

[0186] 2. Stu - A representative of Protea Building Supplies helping with building quotes and planning.

[0187] 3. Peter - A draftsman who assists Sandra with building plans and suggestions for home extensions.

[0188] 4. Abraham - A builder who provides quotes for Sandra’s building projects and undertakes the construction work.

[0189] 5. Mary - An ENTERPRISE agent who helps Sandra with selling and renting out apartments and introduces the idea of becoming a registered business owner.

[0190] 6. Ruth - A new resident who buys an apartment from Sandra and starts a driver business.

[0191] 7. Jeanne - A tenant who wants to start a business buying and selling second-hand cars and later expands into e-scooter rentals.

[0192] 8. Father Brian - An ENTERPRISE Representative and community figure who supports Sandra.

[0193] 9. Shirley - The Franchise Manager at ENTERPRISE who assists Sandra and other new franchisees with their registration and training.

[0194] 10. Xola - A builder who works with Abraham on the construction projects.

[0195] 11. Non-citizen Retailers, Plumbers, Drivers - Non-citizens who become involved with the ENTERPRISE as franchisees or drivers.

[0196] 12. Business Owners - Individuals or entities involved in different business sectors within Protea Estate, including retail, services, and home improvement.

[0197] The ENTERPRISE began by reaching out and forming a partnership with a prominent community leader, in this case a spiritual leader such as Father Brian. At that time, Shirley, a full-time ENTERPRISE Franchise Manager, contacted Father Brian by phone and visited him at his home. Shirley emphasized to Father Brian that the ENTERPRISE'S focus is on serving the local community and meeting its needs, with implementation carried out by residents of the area. She invited Father Brian to partner with ENTERPRISE as a representative, referring potential leaders from the community

[0198] Father Brian agreed to the proposal and immediately thought of Mary. Father Brian and Shirley presented Mary with details about ENTERPRISE offerings and the emphasis on local service, and asked if she was interested in becoming a registered ENTERPRISE agent. ENTERPRISE offered them: i. Membership in the ENTERPRISE Community. ii. ENTERPRISE digital credit cards for each, with a limit, usable at merchants whom they would help ENTERPRISE to onboard, with monthly repayments required. iii. Richard, the ENTERPRISE IT Specialist, assisted Mary and Father Brian in installing the relevant ENTERPRISE apps on their phones. iv. Mary received the ENTERPRISE Estate Agency app, while Father Brian got the ENTERPRISE Representative app. v. Their respective apps contained the necessary ENTERPRISE training programs, which they needed to study and pass exams to qualify. vi. Each was required to pay ENTERPRISE a subscription fee (varying by individual), which ENTERPRISE deducted from their credit cards.

[0199] Once a part of ENTERPRISE, details of Father Brian may be captured in the ENTERPRISE (community ecosystem infrastructure). Details captured may include Father Brian’s name, trust score (for example, 87.3, which may be generated immediately based on specific factors), a duration in the community (for example, 8 years), a residency status (for example, as an owner), a property address (for example 100 Example Street), and a mobile phone number. Father Brian may be stored in a database of high-trust community leaders.

[0200] Shirley explained how merchants could register with ENTERPRISE and the implications of this for them and the community. Mary and Father Brian began identifying potential merchants, including Benny from Protea Nursery, Martha from Protea Hair Salon, Charmaine from Protea Eats, Stu from Protea Building Supplies, Abraham the Builder, and Draftsman Peter.

[0201] Shirley detailed the ENTERPRISE offerings to Benny, highlighting the focus on local service.

[0202] Shirley registered Benny and the following steps were taken: i. He joined the ENTERPRISE Community; ii. received an ENTERPRISE digital credit card with a limit; iii. Shirley helped Benny install the ENTERPRISE app on his phone; iv. Benny received the relevant ENTERPRISE training program on his app, which he needed to study and pass an exam to qualify; v. He had to pay ENTERPRISE a subscription fee, which ENTERPRISE deducted from his credit card.

[0203] Benny passed an exam (performed digitally) and could start functioning as an ENTERPRISE Merchant. Over the next two days, Shirley, Mary, and Father Brian visited the other prospective merchants, all of whom decided to join. They followed the same registration process as Benny.

[0204] Sandra also discovered that once several ENTERPRISE Merchants were established, Shirley returned to discuss ENTERPRISE franchise opportunities with Father Brian. Shirley and Father Brian visited Benny to discuss registering Protea Nurseries as an ENTERPRISE franchise. Having experienced the benefits of being a merchant, Benny agreed to register Protea Nurseries as a franchise. Shirley and Benny went through the same registration process as with Mary.

[0205] Subsequently, Shirley and Father Brian visited Martha from Protea Hair Salon, Charmaine from Protea Eats, Stu from Protea Building Supplies, Abraham the Builder, and Draftsman Peter, with the same objective. All decided to become ENTERPRISE franchisees, and Shirley guided them through the registration process.

[0206] Despite their prior status as ENTERPRISE Merchants, they had to re-register as franchisees and complete an additional ENTERPRISE training course. With these steps taken, the ENTERPRISE has established itself within a community and the following case study aims to showcase how the implemented method and system may assist a community and its individual members.

[0207] Sandra Mayekiso lives in her home in Protea Estate with her two daughters. Despite having lived in her home for over a decade, Sandra does not possess a title deed for her property. The City, which serves as her local municipality, has been providing essential services such as water, sewerage systems, gravel roads, and electricity to Protea Estate for over 15 years, along with regular maintenance of these services. Sandra now hopes to expand and improve her home and plans to rent out the new extension to generate additional income.

[0208] Sandra is a member of the Protea Independent Church, where Father Brian serves as the pastor. To support himself financially, Father Brian has found it necessary to take on secular work in addition to his pastoral duties, for which he receives little to no remuneration. To achieve this, he paid a subscription fee to the ENTERPRISE, completed its training program, joined the ENTERPRISE Community, and became an ENTERPRISE Representative. The church congregates at Father Brian's home on Sundays and sometimes during the week, where an ENTERPRISE sign is displayed above his door. Because of this, Sandra is aware of Father Brian’s involvement with the ENTERPRISE Community.

[0209] Sandra approaches Father Brian to discuss her desire to extend and improve her home. Father Brian explains how the ENTERPRISE Community operates and tells her about the local network of people in Protea Estate who are already members. Sandra is interested and he registers Sandra on the ENTERPRISE App using his phone and assists her in downloading the app. She completes the authentication process through Home Affairs and receives a digital ENTERPRISE Community Card, which functions like a debit card linked to an e-wallet that includes community rewards and discounts.

[0210] Father Brian introduces Sandra to Stu, the owner of a building supplies store in Protea Estate, via a messaging or chat application. This introduction is facilitated through the ENTERPRISE App, which includes a relationship management system. Sandra is comfortable with the transparency provided throughout this process, knowing that Father Brian earns referral commissions on all her transactions as an ENTERPRISE Representative.

[0211] The next day, Stu invites Sandra for coffee and sends his address and a location pin via a messaging service. Stu has paid a higher subscription fee to the ENTERPRISE than Father Brian, completed a more advanced training program, joined the ENTERPRISE Community, and became an ENTERPRISE Building Merchant. Sandra arranges for two days off from work and visits Stu at his shop, which is near her home. She notices the ENTERPRISE sign above his door as she enters. Stu greets her and continues to assist the other customers in the shop. Once he is free, he joins Sandra to discuss the materials needed for her home improvements.

[0212] Stu assists Sandra in drawing a rough sketch of her property and home, adding the planned extension and the improvements she wants to make. He confirms that he is a registered ENTERPRISE Building Merchant and explains in greater detail the benefits of the ENTERPRISE Community. On his phone, Stu shows Sandra a high-resolution satellite image of Protea Estate, and she is excited to see her home clearly identifiable in the photo.

[0213] Stu also tells Sandra about Peter, a draftsman who is part of the ENTERPRISE Community and who can prepare a plan for her home extension and improvements for a fee. Sandra accepts Stu's recommendation and agrees to hire Peter. Stu further suggests that Sandra meet with Abraham, a registered ENTERPRISE Builder known for his honesty, thoroughness, reasonable pricing, and quick, tidy work.

[0214] Stu then explains how Sandra can easily join the ENTERPRISE Community to access various benefits, such as obtaining an ENTERPRISE credit card, securing a loan against her home for building materials, and even selling her home if she chooses. Convinced by the information provided by Stu and Father Brian, Sandra expresses her interest in joining the ENTERPRISE Community.

[0215] Stu recommends Mary, the ENTERPRISE agent in Protea Estate, as the best person to help Sandra join the community. Using the ENTERPRISE App on his phone, Stu introduces Sandra and Mary to each other via a messaging or chat application such as WhatsApp. Sandra notices on the ENTERPRISE app that Stu receives compensation from the ENTERPRISE for her purchases at his shop, a fact she is comfortable with, understanding that Stu is an ENTERPRISE Building Merchant.

[0216] Mary reaches out to Sandra via WhatsApp to arrange a visit to her home that same day. Sandra agrees and sends her address and a location pin. Mary has paid an even higher subscription fee to the ENTERPRISE than Stu or Father Brian, completed the most advanced training program, joined the ENTERPRISE Community, and became an ENTERPRISE agent. At the agreed time, Mary arrives at Sandra’s home, where Mary explains the workings and benefits of the ENTERPRISE Community in more detail than Stu and Father Brian had provided.

[0217] Mary informs Sandra that the ENTERPRISE will determine the geographic coordinates of her property, known as e-pegs, and that Sandra will receive an ENTERPRISE Digital Certificate of Ownership for her home. Sandra is eager to proceed and completes an ENTERPRISE application form on her app with Mary's assistance, signing it electronically via an electronic signature service or e-signature platform such as Docusign. Mary then takes photos of Sandra and her identification document, with Sandra’s authentication confirmed on Mary’s section of the app. Mary also photographs the interior and exterior of Sandra’s home. The next step requires Sandra to have several of her neighbours verify her ownership of the home by signing an ENTERPRISE form. There are certain requirements that these neighbours must comply with, for example, these neighbours must live within a 200-meter radius, be household members, be over 18, and have valid ID documents or passports. Mary accompanies Sandra to each neighbour’s home, presenting the ENTERPRISE form via the app on her phone, reading it aloud, and helping each neighbour sign it electronically using Docusign. She also takes pictures of each neighbour and their ID documents or passports. Five of the seven neighbours decide to join the ENTERPRISE Community, and Mary registers them on the spot. They download the app, are authenticated via Home Affairs, and receive their digital ENTERPRISE Community Cards. The system is scalable to accommodate the growth of new members and enriches the ENTERPRISE Register with demographic and geographic data, making administration paperless and more convenient.

[0218] During their visits, Mary sends a WhatsApp™ message to Father Brian, who, as the local pastor and religious leader, must also verify Sandra’s ownership of her home. Father Brian completes the form on his ENTERPRISE app and sends it, along with a photo of himself and his ID document, to Mary, all electronically, which may speed up the process. It takes about 30 minutes to obtain each neighbour’s signature, and by the evening, they have finished. Mary schedules another visit with Sandra for the next morning.

[0219] At home, Mary processes the documents for the two neighbours who did not register with the ENTERPRISE or download the app and submits them to the ENTERPRISE office, confident that everything will be ready for Sandra by the following day.

[0220] Mary arrives at Sandra's home the next morning, with all the necessary documents from the ENTERPRISE office, accessible through the ENTERPRISE app on her phone. First, Sandra is welcomed as a member of the ENTERPRISE Community, and she receives the ENTERPRISE app on her phone. One of the documents on the app is a certificate verifying her membership in the ENTERPRISE Community, which she can print if she wishes. Sandra also receives a digital certificate of ownership for her home through the app on her phone — this certificate of homeownership gives her a sense of dignity.

[0221] Sandra can start the ENTERPRISE Level 1 Training Program, which is already available on her app, take the exam, and receive a certificate if she completes it successfully. The ENTERPRISE approved the following loan secured against her property with a bond or instalment sale agreement, considering her ability to service the loan with the income she earns from her full-time job (the affordability calculation is tracked and updated via the app): a digital credit card with a limit, usable at over 100 participating merchants, with a requirement for monthly repayments; a credit line with a pre-approved limit, specifically for purchasing building materials at Protea Building Supplies to extend and enhance her home; an additional loan facility (with a limit) to pay a contractor for the necessary building work.

[0222] Mary informs Sandra that ENTERPRISE Insure offers comprehensive home and household insurance, and a short-term insurance policy is included in the ENTERPRISE package. Sandra also receives an offer for a life insurance policy from the ENTERPRISE that covers the repayment of her home loan and provides an additional payout to her estate upon her death. Mary notes that the home loan and other financial support are funded by the ENTERPRISE Investment Fund.

[0223] Sandra can also request Mary, as an ENTERPRISE agent, to sell her home if she ever decides to do so. Mary explains that Sandra must pay a registration fee to the ENTERPRISE, which will be automatically deducted from her digital credit card.

[0224] Mary goes over the ENTERPRISE documents that Sandra needs to sign and assists her in signing them electronically using an e-signature service on the ENTERPRISE app. Sandra and Mary celebrate Sandra's new financial reality and her status within the ENTERPRISE community.

[0225] Sandra receives a notification on the app that Mary, as an ENTERPRISE agent, received a commission from ENTERPRISE for assisting Sandra in securing all the credit, financing, and other approvals. Sandra visits Martha at the nearby Protea Hair Salon and is pleased to find out that Martha is already a member of the ENTERPRISE Community, and Sandra pays for the service with her ENTERPRISE digital credit card.

[0226] Sandra then heads to Stu's shop at Protea Building Supplies. Feeling hungry, she stops by Protea Eats to buy a hamburger from Charmaine, paying with her ENTERPRISE credit card. Stu helps her select the materials she will need to extend and enhance her home. Stu also shows Sandra the design drafted by Peter, the draftsman. She is satisfied with the plan and agrees that Stu will ask Peter to send her the invoice for his drafting services, and she will request ENTERPRISE to pay it. Sandra also asks Stu to prepare an invoice for the materials she purchased from Protea Building Supplies for her home extension and improvements, and she will request ENTERPRISE to cover the cost.

[0227] Stu notes that, technically, Sandra should apply for building plan approval for her home extension from the City. However, he mentions that none of the houses in Protea Estate, including Sandra’s, have approved building plans from the municipality. He expresses hope that the involvement of ENTERPRISE in Protea Estate might encourage the municipality to regularize planning, service installations, and freehold ownership in the area.

[0228] Sandra suggests that Stu contact Abraham, a builder registered with ENTERPRISE. Stu calls Abraham, who agrees to come over to Stu’s shop for a meeting in the late afternoon. Abraham is an ENTERPRISE-registered builder. He paid a subscription fee, completed an advanced training program, joined the ENTERPRISE Community, and became a recognized builder within the network. ENTERPRISE provided him with a specialized app on his phone that includes various documents and guidelines to help him be an effective builder, serve his clients well, and achieve success. The app includes tools like a building contract template, a costing sheet, and a to-do list.

[0229] When Abraham arrived, Sandra, Stu, and Abraham discussed the building project for Sandra's home. Stu printed out the extension plan prepared by Draftsman Peter. On the back of the plan, Abraham listed all the tasks he needed to complete for Sandra’s extension. Abraham estimated the time required for each task. He also calculated the cost of his labour for each activity, including a contingency amount, and provided a quotation for the entire project. Sandra appreciated Abraham’s transparent approach and was satisfied with his quotation.

[0230] Stu had a draft building contract on the ENTERPRISE app on his phone. Stu read through the contract and explained it to Sandra and Abraham. Both confirmed their understanding and willingness to proceed. Stu finalized the contract, inserted their names, and they signed it digitally using Docusign. Sandra confirmed that the ENTERPRISE loan facility for her home extension was sufficient to cover payments to Stu, Abraham, and Draftsman Peter, and that these payments would be made directly by ENTERPRISE. The three of them shook hands on the agreement. Abraham committed to starting the project on Saturday.

[0231] Sandra was pleased that Stu, as an ENTERPRISE Building Merchant, received a commission from ENTERPRISE Draftsman Peter and ENTERPRISE Builder Abraham for securing new work from her and facilitating the agreements among them. Sandra was also glad that ENTERPRISE earned a commission from these transactions. This was disclosed transparently.

[0232] On Saturday, Abraham and his assistant, Xola, arrived at Sandra’s home in Abraham’s bakkie. Abraham discussed the work plan and schedule with Sandra, who was satisfied with the arrangements. Abraham took photos of Sandra's home, particularly of the areas for extension and improvement. He sent these photos to Sandra and asked her to forward them to ENTERPRISE, along with a note about the state of her home before the work began. Abraham and Xola commenced work immediately. By sunset, they had made significant progress. Before leaving, Abraham took more photos to document their progress and asked Sandra to send these to ENTERPRISE that night. Each evening, Abraham took photos of the day's progress and sent them to Sandra, who forwarded them to ENTERPRISE.

[0233] On Tuesday morning, Abraham requested an advance for the work completed. Sandra, already at work, sent an ENTERPRISE payment request form via the app to Abraham for completion and return. Sandra signed the completed form with Docusign. Later that day, ENTERPRISE transferred the requested funds from Sandra’s home loan account to Abraham’s ENTERPRISE bank account and informed both Sandra and Abraham. Both were pleased with the transaction.

[0234] Abraham and Xola continued their work, and on Thursday, Abraham arranged to meet Sandra at her home on Friday. On Friday, Abraham had prepared a detailed list of tasks for the extension, including the time spent, materials used, and photos of each stage. He used the ENTERPRISE app to manage this documentation. Abraham showed Sandra the completed extension and reviewed the task list with her. Sandra was grateful and satisfied.

[0235] Abraham also discussed the project finances with Sandra, who was content with the details. A surplus of timber was returned to Protea Building Supplies, and Stu issued a credit to Sandra’s account. Sandra and Abraham agreed on the remaining balance owed to Abraham. They completed an ENTERPRISE payment request on Sandra’s app, signed it digitally, and Sandra submitted Abraham’s task list and photos to ENTERPRISE.

[0236] It was Friday evening, but Sandra and Abraham knew ENTERPRISE would transfer the final payment to Abraham’s bank account on Monday. Sandra thanked Abraham and Xola.

[0237] The extension is separate from Sandra’s main house. Mary explained that although the extension shares a wall with the main house, ENTERPRISE would register it as a separate erf and house. This means Sandra could sell the extension separately and potentially earn a significant profit. Sandra was intrigued and asked Mary for an estimated selling price.

[0238] Mary examined the extension plan, assessed its size, and took several photos. She calculated a proposed selling price, more than double the cost of the extension and improvements. This valuation utilized the ENTERPRISE register, which is also used by BUSINESS INVEST, INSURE, BANKS, and other credit providers for inquiries and valuations, enriched with ENTERPRISE property trade data.

[0239] Sandra expressed her initial intent to rent the extension but was now interested in selling it for Mary’s suggested price. Mary agreed to register the extension with ENTERPRISE on Monday morning and obtain a BUSINESS Digital Certificate of Ownership for Sandra. Sandra authorized Mary with a sole mandate to sell the extension for the agreed upon price. Mary completed the mandate on her app, and both signed it digitally. Mary suggested waiting until Monday morning for the BUSINESS Digital Certificate of Ownership before proceeding.

[0240] Mary planned to start advertising the extension on social media that afternoon. She anticipated significant interest, as she could assist potential buyers in obtaining a home loan from ENTERPRISE. Mary would arrange viewings with interested buyers for Sandra. On Monday morning, Mary processed Sandra’s application with ENTERPRISE, received approval, and obtained a BUSINESS Digital Certificate of Ownership for Sandra. Mary also received a copy.

[0241] Mary prepared an advertisement featuring photos of the extension’s interior and exterior and posted it on social media. On Tuesday, Mary and the first prospective buyer visited Sandra’s extension. The third prospective buyers, a young couple named Paddy and Lynne, decided to purchase the extension. They signed an offer digitally on the Deed of Sale using the ENTERPRISE app. Mary promptly sent the offer document to Sandra and requested a meeting, even though it was late. Sandra and Mary met at Sandra’s home, where Sandra signed the Deed of Sale digitally.

[0242] On Thursday morning, Mary met with Paddy and Lynne to help them join the ENTERPRISE Community and apply for a home loan. Mary explained that the loan and other funding came from the ENTERPRISE Investment Fund. Their funding package was approved early Thursday afternoon. Mary visited them again to congratulate them and assist with the completion and signing of all necessary funding and transfer documents.

[0243] That evening, Mary visited Sandra to help with the completion and signing of the ENTERPRISE transfer documents. Mary submitted all documents to ENTERPRISE that night. On Friday morning, ENTERPRISE confirmed the transfer of ownership from Sandra to Paddy and Lynne and issued a new BUSINESS Digital Certificate of Ownership to the couple.

[0244] ENTERPRISE transferred the sale proceeds to Sandra’s account. Mary’s commission of 2% of the selling price was deposited into her ENTERPRISE bank account. Sandra’s ENTERPRISE home loan was paid off from the sale proceeds, and the remaining amount was invested in a short-term savings account for Sandra.

[0245] Mary informed Sandra that Paddy and Lynne, currently living in a small backyard room, wanted to move into their new home on Saturday morning. Sandra agreed. Mary suggested that Sandra consider investing some or all of her excess funds in the ENTERPRISE Investment Fund. This investment would provide Sandra with monthly interest income, allow her to join other local and foreign investors, and help others progress financially.

[0246] Sandra agreed to invest her excess funds in the ENTERPRISE Investment Fund. Mary assisted her in completing and signing the necessary documents digitally. On Saturday morning, Sandra welcomed Paddy and Lynne as her new neighbours.

[0247] On Sunday morning, Sandra attends Protea Independent Church, where Father Brian is the preacher. As it is Environment Day, he mentions that he is affiliated with the ENTERPRISE Community, a passionate organization dedicated to community-focused business practices. ENTERPRISE has chosen the Spekboom as their Tree of the Year. Father Brian further explains that Protea Nursery, located in Protea Estate, is the registered ENTERPRISE Nursery for the area. ENTERPRISE, in partnership with Protea Nursery, has committed to giving each homeowner in Protea Estate two Spekboom trees free of charge, provided they plant and care for them on their properties.

[0248] With his deep commitment to environmental issues, Father Brian also introduces two new outdoor programs from ENTERPRISE. One program involves the local nursery, Protea Nursery, adjudicating and awarding the best garden in the neighbourhood. The other program features Benny, the owner of Protea Nursery, who will provide monthly demonstrations on how homeowners in Protea Estate can grow their own vegetables using purified wastewater.

[0249] After church, Sandra collects two Spekboom trees at Protea Nursery. Sandra purchases compost and a spade, paying with her ENTERPRISE digital credit card. Sandra informs Paddy and Lynne about the ENTERPRISE and Protea Nursery Spekboom initiative. She offers a spade and some compost left over from her purchase.

[0250] Paddy and Lynne invite Sandra over for tea. Lynne shares how impressed they are with the ENTERPRISE package. Paddy appreciates that ENTERPRISE provided them with home and household insurance, acknowledging the financial protection against theft, fire, storms, and other emergencies. Lynne mentions their eagerness to tackle new challenges together, and Paddy notes that they understand ENTERPRISE appoints and registers ENTERPRISE Insurance Agents.

[0251] Sandra suggests that they visit Mary to seek her assistance. The following morning, they meet Mary at her home, who supports their plan to become ENTERPRISE Insurance Agents for the area. Mary, as the ENTERPRISE agent, is excited to work with them and instructs them to contact ENTERPRISE Franchise Manager Shirley at the office for assistance with their registration. Mary provides Shirley’s contact details.

[0252] Paddy and Lynne call Shirley, who joins them via video call to explain the process. Shirley helps them complete the necessary forms, which they sign digitally. The next morning, Shirley calls to congratulate them on being accepted as the new ENTERPRISE Insurance Agents for Protea Estate. As current members of the ENTERPRISE Community, they need to pay a subscription fee and complete an advanced ENTERPRISE insurance marketing training program. ENTERPRISE has offered them a further loan on their house to cover the subscription fee, and the ENTERPRISE Insurance Agent app has been installed on their phones.

[0253] Shirley assists Paddy and Lynne in completing and signing all necessary documents digitally. They download the ENTERPRISE 5 Training Programme on their phones.

[0254] The following day, they start their new role as ENTERPRISE Insurance Agents. They visit homes door-to-door to present the home and household insurance opportunity, leveraging the recent fire in a neighbouring village to highlight the importance of insurance. They successfully sell one or more policies each day and also offer ENTERPRISE life insurance policies. The sales process is regulated and facilitated by the ENTERPRISE system, which tracks members' financial data and assets. Paddy and Lynne also encounter people interested in extending their properties, selling their homes, or obtaining home loans, earning referral commissions for these additional ENTERPRISE services.

[0255] As they continue their efforts, Paddy and Lynne build their business daily. They provide homeowners with comprehensive insurance packages, including the ENTERPRISE app, membership, a Digital Certificate of Ownership, the ENTERPRISE 1 Training Programme, a home loan from the ENTERPRISE Investment Fund, a digital credit card, and both short-term and life insurance policies from ENTERPRISE Insure. Soon, Paddy and Lynne begin discussing plans to extend their small house.

[0256] Sandra decides to undertake another construction project on her property. She schedules a meeting with Stu from Protea Building Supplies and requests that Draftsman Peter and Builder Abraham join them for the discussion. Sandra brings several photos of her home and the extension that now belongs to Paddy and Lynne. At the scheduled time, Sandra meets with the three professionals at Protea Building Supplies. She informs them that she has sold the extension to her home, which they had previously helped her with. Sandra then reveals her intention to extend her home again and seeks their advice.

[0257] Peter reviews Sandra’s Digital Certificate of Ownership and the photos she provided. He notes that Sandra does not have enough vacant land left on her property and suggests that adding another storey to her existing single-storey house might be a viable option. Additionally, Peter proposes that it would be practical for Paddy and Lynne to also build another storey on their home simultaneously with Sandra’s project. Sandra appreciates this idea, knowing that Paddy and Lynne are looking to extend their home. Abraham agrees with Peter’s proposal but points out that such a project would take longer, be more disruptive during construction, and be more costly per square meter.

[0258] Three days later, Sandra, Paddy, and Lynne meet with Peter, Abraham, and Stu at Protea Building Supplies. Peter presents his plans and explains them, while Abraham and Stu provide and discuss their quotes. It becomes clear that undertaking both projects simultaneously is financially sensible. Both parties agree to proceed, approve the quotes, and are satisfied with the proposed arrangements. Stu uses the ENTERPRISE app on his phone to open the necessary documents and helps everyone complete and sign them electronically. They finalize and submit their ENTERPRISE Investment Fund applications from home.

[0259] Two days later, they receive the approvals from ENTERPRISE and complete the required documents. Sandra makes the arrangements for materials, construction, and payments with Stu and Abraham, like her previous project. Construction begins two days later with Abraham and Xola working on both projects. They diligently complete the work within a month. Sandra and Paddy and Lynne are pleased with the results, arrange payment, and take possession of their respective spaces.

[0260] Sandra contacts Mary to discuss her building project. Sandra shows Mary the apartments and mentions considering selling one and renting the other. She seeks Mary’s opinion on the feasibility of her plans. Mary explains that if Sandra provides ENTERPRISE with Peter’s plans and photos of the completed building, ENTERPRISE will determine the geographic coordinates for her original home and the two new apartments. Sandra will then receive three Digital Certificates of Ownership for each property.

[0261] Mary further details the ENTERPRISE Title System, which allows for multiple ownership of multistorey buildings. This includes issuing Digital Certificates of Ownership for each apartment, establishing a legal entity to manage communal property, and creating guidelines for ownership and usage, insurance, and conflict resolution. These guidelines are like conventional sectional title schemes but are more concise.

[0262] Sandra asks Mary for help in finding a buyer for one apartment and a tenant for the other. Mary reviews Peter’s plans, calculates the apartment sizes, and advises on which apartment to sell and which to rent. She provides suggestions for the selling price and rental amount, which Sandra accepts. Sandra agrees to appoint Mary to find a suitable buyer and tenant.

[0263] The next evening, Mary visits Sandra’s apartment with potential buyer Ruth. Ruth decides to buy the apartment. They prepare and sign the deed of sale. When Sandra arrives home, she reviews and signs the document, and Mary departs. Mary then arranges a package offer from ENTERPRISE and a loan offer from ENTERPRISE Investment Fund for Ruth, who accepts both offers.

[0264] ENTERPRISE decides that Sandra, Paddy, Lynne, and Ruth should jointly register and belong to the ENTERPRISE Title Scheme for the property. The three parties agree, and Mary prepares and presents the necessary documents, which are signed.

[0265] Two days later, all the paperwork is complete, and Ruth moves into her new home. Meanwhile, Mary shows Sandra’s rental apartment to Jeanne and Seanne, who decide to rent it. They are originally from a different country and register on the ENTERPRISE app. Their information is stored and authenticated, and they are issued ENTERPRISE cards linked to e-wallet accounts. They move in the next day.

[0266] A few days later, Ruth invites Sandra for tea and mentions that she owns a small car and is interested in starting a driver service for commuters in the area. Sandra suggests that Ruth contact ENTERPRISE Franchise Manager, Shirley, for information about the ENTERPRISE Driver program. She provides Shirley’s contact details.

[0267] Ruth calls Shirley, who explains the process to become a registered ENTERPRISE Driver during a video call. Shirley helps Ruth complete the forms, which are signed electronically. The next day, Shirley congratulates Ruth on being accepted as a new ENTERPRISE Driver for Protea Estate and neighbouring areas. Ruth, already part of the ENTERPRISE Community, needs to pay a subscription fee and complete advanced driving training. ENTERPRISE offers a loan to cover the subscription fee, and the ENTERPRISE Driver app is downloaded to her phone. Shirley assists Ruth in completing and signing all documents. Ruth begins studying the ENTERPRISE 6 Training Programme and schedules a virtual exam with Shirley, passes, and is ready to start as an ENTERPRISE Driver.

[0268] One evening, her tenant Jeanne approaches Sandra about starting a business buying and selling second-hand cars and seeks her opinion on partnering with ENTERPRISE. Sandra suggests contacting Shirley and provides Jeanne’s contact number. Jeanne calls Shirley to inquire about partnering with ENTERPRISE for his car business. She explains the ENTERPRISE Cars franchise and Jeanne expresses his interest in applying.

[0269] Shirley assists Jeanne with the application forms and mentions that she will visit him the next day to discuss ENTERPRISE’S response. Shirley visits Jeanne and informs him that ENTERPRISE has approved his application for a franchise. Jeanne will join the ENTERPRISE Community, receive a credit card with a set limit, and ENTERPRISE will finance car buyers after assessing each application. Jeanne will pay a franchise fee from his credit card limit. Shirley explains that ENTERPRISE will also provide funding to purchase the first car, but Jeanne must contribute a portion. Jeanne agrees to contribute 30% of the funding, which Shirley confirms.

[0270] Shirley helps Jeanne complete and sign the necessary documents. Jeanne studies the training material, passes the exam, and deposits the required amount into his ENTERPRISE savings account. He is now ready to start his business, Protea Quality Cars.

[0271] Jeanne finds a good-quality Toyota Corolla at a reasonable price, adds to the asking price, and advertises it on social media. He quickly receives a response. After purchasing the car and securing funding from ENTERPRISE, Jeanne sells the car to a buyer who takes it for a test drive and finalizes the purchase.

[0272] Jeanne then starts looking for his next car to buy and sell. He also convinces Shirley and ENTERPRISE to grant him an e-scooter franchise for Protea Village and the surrounding area, which he names Protea Quality e-Scooter. Jeanne plans to focus on acquiring and converting 2- seater electric e-scooters into 3-seaters for a commuter business, using the same ENTERPRISE app as the Driver Franchise. ENTERPRISE will work with Jeanne to expand this opportunity and potentially offer e-scooter franchises in other areas.

[0273] Sandra’s two daughters are growing up and want to explore Protea Estate on their own. However, recent violent incidents have raised concerns about safety in the area. Sandra is worried about both her own and her daughters' security. To address these concerns, Sandra considers the possibility of registering as an ENTERPRISE Security Agent. Sandra then visits Shirley at the ENTERPRISE office to explore her options. She realizes that she would need to resign from her full-time cleaning job at a nearby factory to focus entirely on her new role as an ENTERPRISE Security Agent.

[0274] Sandra reviews her financial situation, noting that she has repaid her home loan, which is a positive step. Her income sources include the monthly rent from the upstairs apartment, a small pension from her previous cleaning job, and growing returns from the ENTERPRISE Investment Fund. Sandra feels these sources provide a financial cushion, especially during the initial months of her new security business. Shirley agrees and offers to advance funds if needed, secured against the bond on her home.

[0275] Satisfied with this support, Sandra agrees to register her new business, Protea Security Services, as an ENTERPRISE Security Agent. Shirley helps her complete the necessary forms, which Sandra signs. She will receive a new ENTERPRISE app and training program, and will need to pay a franchise fee, which ENTERPRISE will deduct from her credit card. Sandra completes her training program, passes the exam, and is officially registered as a new ENTERPRISE franchisee.

[0276] Sandra, now a local entrepreneur, decides to launch a security initiative and business for her street and the three adjacent streets, covering a total of about 100 houses. With the assistance of a consultant, she devises a plan to install a community security system. The system includes 10 high-definition Al cameras, 10 solar-powered spotlights with batteries installed inside nearby houses, Wi-Fi connections from each camera to a central tower, a monitoring app for the cell phones of each participating homeowner, and a 24 / 7 monitoring system for all 10 cameras. The setup also features alarms and microphones at each camera location. The ENTERPRISE'S franchise fees and management fees are factored into the overall costs.

[0277] Sandra then develops a comprehensive security plan for the entire Protea Estate. This involves writing detailed specifications for the security system, collaborating with an app development team to create preventative mobile solutions, and integrating trauma treatment services and other reactive measures. All data collected is used to enhance preventative alerts for app users. She calculates the monthly costs of the system, divides these costs among the participating households to determine each one's contribution, and registers the Protea Estate East Security Village with ENTERPRISE, opening a dedicated bank account for the project.

[0278] ENTERPRISE agrees to loan the funds needed to purchase and install the security equipment for Protea Estate East Security Village. Eager to implement the system quickly, Sandra faces an initial participation rate of 80%, prompting her to adjust the number of cameras, lights, power supply units, and alarms / microphones from 10 to 8.

[0279] Three months after the security project is implemented, it is assessed and shows positive results: no attacks, violence, or theft have occurred, the community feels safer, children are playing outside again, there is strong participation from homeowners, and property values have increased. These results are published in the media, and Sandra is soon approached by two other groups interested in implementing a similar security system.

[0280] Through her home visits, Sandra gets to know many residents and discovers opportunities to refer them for services like short-term insurance, real estate transactions, home renovations, and starting new franchise businesses. She earns referral commissions from these interactions. Many other businesses in the Protea Estate community become involved as Merchants or Franchisees, offering services such as plumbing, solar energy solutions, and barbering.

[0281] As new retail shops, hair salons, and take-away outlets open along pavements and street corners, or operate from backyard spaces, these traders are approached by ENTERPRISE to join as Merchants or Franchisees. This inclusivity helps establish non-citizens as valued contributors to the local economy. ENTERPRISE thereby creates opportunities for non-citizens to attain home ownership and other related benefits.

[0282] Additionally, with the appointment and training of agents, improved business operations, and enhanced security, there is a growing sense of pride in Protea Estate. This has led to an increase in property sales, and ENTERPRISE plays a significant role in driving up property values in the area.

[0283] As mentioned, the method and system provide for the establishment of an asset register for property (movable and immovable) within the infrastructure. The asset register may be a computer-based register and may be accessible via the entity application. The asset register may integrate with high-density satellite imagery of dwellings, mapped to micro-coordinates (e-pegs / e- tiles). The asset register may include the following: detailed property and structure descriptions, ownership verification, owner identification data points, proof of address, and complementary authentication information. It may also leverage specialist valuation insights alongside Al-driven valuations to facilitate credit assessments and enable insurance services.

[0284] The following is an example embodiment of a step-by-step method of the system involving ENTERPRISE’S support and processes:

[0285] • Business Idea & Decision: A community member or entrepreneur identifies a business opportunity and decides to start a new venture.

[0286] • Initial Consultation: The individual meets with ENTERPRISE representatives to discuss the business idea and the requirements for registration.

[0287] • Application & Approval: Submit an application for the franchise or business opportunity; ENTERPRISE reviews the application, assesses the viability, and approves or provides feedback.

[0288] • Funding & Financial Arrangements: ENTERPRISE offers financial support, including loans or credit facilities, based on the business plan; Funds are allocated for initial setup costs, such as franchise fees, equipment, or other expenses.

[0289] • Franchise Registration & Training: The new business registers with ENTERPRISE and completes necessary forms; ENTERPRISE provides training programs and resources relevant to the business type.

[0290] • Operational Setup: The business sets up its operations, including any required licenses or certifications.

[0291] • Ongoing Support & Monitoring: ENTERPRISE monitors the progress of the new business, offering additional support as needed; This may include further financial assistance, operational guidance, or marketing support.

[0292] • Community Integration: The new business integrates into the community, contributing to local economic growth and prosperity.

[0293] • Evaluation & Expansion: ENTERPRISE evaluates the success of the business and explores opportunities for further expansion or additional support.

[0294] The foregoing description has been presented for the purpose of illustration; it is not intended to be exhaustive or to limit the technology to the precise forms disclosed. Persons skilled in the relevant art can appreciate that many modifications and variations are possible in light of the above disclosure.

[0295] Any of the steps, operations, components or processes described herein may be performed or implemented with one or more hardware or software units, alone or in combination with other devices. Components or devices configured or arranged to perform described functions or operations may be so arranged or configured through computer-implemented instructions which implement or carry out the described functions, algorithms, or methods. The computer- implemented instructions may be provided by hardware or software units. In one embodiment, a software unit is implemented with a computer program product comprising a non-transient or non- transitory computer-readable medium containing computer program code, which can be executed by a processor for performing any or all of the steps, operations, or processes described. Software units or functions described in this application may be implemented as computer program code using any suitable computer language such as, for example, Java™, C++, or Perl™ using, for example, conventional or object-oriented techniques. The computer program code may be stored as a series of instructions, or commands on a non-transitory computer-readable medium, such as a random-access memory (RAM), a read-only memory (ROM), a magnetic medium such as a hard-drive, or an optical medium such as a CD-ROM. Any such computer-readable medium may also reside on or within a single computational apparatus and may be present on orwithin different computational apparatuses within a system or network.

[0296] Flowchart illustrations and block diagrams of methods, systems, and computer program products according to embodiments are used herein. Each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, may provide functions which may be implemented by computer readable program instructions. In some alternative implementations, the functions identified by the blocks may take place in a different order to that shown in the flowchart illustrations.

[0297] Some portions of this description describe the examples in terms of algorithms and symbolic representations of operations on information. These algorithmic descriptions and representations, such as accompanying flow diagrams, are commonly used by those skilled in the data processing arts to convey the substance of their work effectively to others skilled in the art. These operations, while described functionally, computationally, or logically, are understood to be implemented by computer programs or equivalent electrical circuits, microcode, or the like. The described operations may be embodied in software, firmware, hardware, or any combinations thereof.

[0298] The language used in the specification has been principally selected for readability and instructional purposes, and it may not have been selected to delineate or circumscribe the inventive subject matter. It is therefore intended that the scope of the present disclosure be limited not by this detailed description, but rather by any claims that issue on an application based hereon. Accordingly, the present disclosure is intended to be illustrative, but not limiting, of the scope of any accompanying claims.

[0299] Finally, throughout the specification and any accompanying claims, unless the context requires otherwise, the word ‘comprise’ or variations such as ‘comprises’ or ‘comprising’ will be understood to imply the inclusion of a stated integer or group of integers but not the exclusion of any other integer or group of integers.

Claims

CLAIMS1. A computer-implemented method, conducted at a community ecosystem infrastructure, for providing an association of an asset to an entity, comprising: receiving asset data relating to the asset; receiving geographical information associated with the asset data from a geographical information service; transmitting, to a plurality of verifying entities, a request to verify an association of the asset to the entity; receiving, from at least one of the plurality of verifying entities, a response indicating an approval or rejection of an association between the asset and the entity; and, determining, based on the received responses, a certification of association of the asset to the entity.

2. The method of claim 1 , including, in response to determining an approval of the certification of association between the asset and the entity, issuing a certificate indicating an approval of association of the asset, wherein the certificate is usable on the community ecosystem infrastructure as proof-of-ownership of the asset with services.

3. The method of claim 1 or 2, including receiving, from an entity device, a transfer request including asset data and an identifier of a receiving entity for transferring the certification of association of the asset to the receiving entity.

4. The method of claim 1 or 2, including receiving, from an entity device, a utilisation request permitting a utilising entity to utilise the asset.

5. The method of any one of the preceding claims, wherein determining the certification of association of the asset includes inputting the received responses into a trust model, wherein the trust model is configured to output an approval or rejection of the certification of association based on the received response.

6. The method of claim 5, wherein the trust model is a graph network, wherein nodes of the graph network model different entities registered with the community ecosystem infrastructure and wherein edges of the graph network model a trust score between entities connected to the edge.

7. The method of claims 5 or 6, wherein the trust model is calibrated according to a set oftrusted parties serving as trusted entities relative other entities.

8. The method of any one of claims 5 to 7, including recalibrating the trust model in response to triggering events.

9. The method of claim 8, wherein the triggering events include any one or more of: predefined weather events; forced removals or displacement; changes in trusted parties; and, predetermined time periods between calibrating.

10. The method of any one of the preceding claims, including registering entities with the community ecosystem infrastructure.

11. The method of claim 10, including registering a trusted entity device associated with the entity.

12. The method of any one of the preceding claims, wherein the entities all relate to a common geographical area in which the community ecosystem infrastructure is based.

13. The method of any one of the preceding claims, including providing an entity application, usable by one or more entity devices, for accessing the community ecosystem infrastructure and ecosystem services.

14. The method of any one of the preceding claims, including providing application programming interfaces to one or more external resources for integration of external services with the community ecosystem infrastructure.

15. The method of claim 14, wherein the external resources include any one or more of: property deeds office; car registration office; home affairs; banks; credit bureau; and, document signing services.

16. The method of any one of the preceding claims, wherein providing ecosystem services includes asset registration and trading services.

17. The method of claim 16, wherein assets for asset registration are property.

18. The method of any one of the preceding claims, wherein the external services include satellite and geographic information systems (GIS).

19. The method of any one of the preceding claims, wherein the ecosystem services include: financing services; security services; environmental services; insurance services; and, social services.

20. The method of any one of the preceding claims, including: registering entities in the community ecosystem infrastructure as role players within the community; providing ecosystem services to the registered entities; providing a platform for registered entities to provide goods and services to other registered entities; providing training to registered entities thereby providing certification for offering goods and services to other registered entities; and providing integration to external resources for external services provided to the registered entities.

21. The method of any one of the preceding claims, wherein the entity is associated with an entity device.

22. A computer-implemented method, conducted at an entity device, for providing association of an asset to an entity, comprising: obtaining asset data related to the asset at the entity device; transmitting the asset data to a server of the community ecosystem infrastructure, wherein the server is configured to: receive geographical information associated with the asset data from a geographical information register; transmit, to a plurality of verifying entities, a request to verify an association of the asset to the entity; receive, from each of the plurality of verifying entities, a response indicating an approval or rejection of an association between the asset and the entity; and, determine, based on the received responses, a certification of association of the asset by the entity; and, receiving, from the server, a certification of association indicating an association of the asset with the entity.

23. The method of claim 22, including: receiving a request from the server to verify an association of a second asset to a secondentity; outputting a prompt to the entity device to verify an association between the second asset and the second entity; receiving an input at the entity device, the input indicating an approval or rejection of the association of the second asset to the second entity; and, transmitting input indicating approval or rejection to the server.

24. A system including a server for providing a certification of association of an asset to an entity within a community ecosystem infrastructure, comprising: an asset data receiving component for receiving asset data related to the asset; a geographical information receiving component for receiving geographical information associated with the asset data from a geographical information register; a request transmitting component for transmitting, to a plurality of verifying entities, a request to verify an association of the entity to the asset; a verification receiving component for receiving, from one or more of the plurality of verifying entities, a response indicating an association between the asset and the entity; and, an ownership determining component for determining, based on the received responses, a proof-of-ownership of the asset by the entity.

25. A computer program product for providing an association of an asset to an entity, the computer program product comprising a computer-readable medium having stored computer- readable program code for performing, at a server, the steps of: receiving asset data relating to the asset; receiving geographical information associated with the asset data from a geographical information service; transmitting, to a plurality of verifying entities, a request to verify an association of the asset to the entity; receiving, from each of the plurality of verifying entities, a response indicating an approval or rejection of an association between the asset and the entity; and, determining, based on the received responses, a certification of association of the asset to the entity.

26. A computer program product for providing an association of an asset to an entity, the computer program product comprising a computer-readable medium having stored computer- readable program code for performing, at an entity device, the steps of: obtaining asset data related to the asset at the entity device; transmitting the asset data to a server of the community ecosystem infrastructure, whereinthe server is configured to: receive geographical information associated with the asset data from a geographical information register; transmit, to a plurality of verifying entities, a request to verify an association of the asset to the entity; receive, from each of the plurality of verifying entities, a response indicating an approval or rejection of an association between the asset and the entity; and, determine, based on the received responses, a certification of association of the asset to the entity; and, receiving, from the server, a certification of association indicating an association of the asset with the entity.

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