Non-financial asset risk assessment method and device, electronic equipment and storage medium

Abstract

The invention discloses a non-financial asset risk assessment method and device, electronic equipment and a storage medium. The method comprises the steps of obtaining asset information of a target non-financial asset of a target mechanism, and determining a basic risk coefficient of the target non-financial asset based on the asset information; action information of the target non-financial assets is obtained, and the deviation degree of the target non-financial assets is determined based on the action information; the action information comprises first biological characteristic information, first time information and target mechanism information; the biological characteristic information is a biological characteristic of an object taking the target non-financial asset away from the target mechanism; the first time information is the time when the target non-financial assets are taken away from and / or back to the target mechanism; the first institution information is institution information that the target non-financial assets are taken away and / or taken back; and determining a target risk coefficient of the target non-financial asset based on a basic risk coefficient and the deviation degree. The off-bank tracking management of the non-financial assets of the bank is realized, and the risk prevention and control capability is improved.

Description

Technical Field

[0001] This invention relates to the field of asset management technology, and in particular to a method, apparatus, electronic device, and storage medium for assessing the risk of non-financial assets. Background Technology

[0002] Regarding non-financial asset management, although banks have built corresponding asset management systems as management tools during their initial IT transformation, these systems lack comprehensive functionality, leading to deficiencies in asset off-bank management. For example, when non-financial assets are transferred across institutions, the asset management system can only track the approval time for the asset transfer; it cannot track when the asset actually leaves the sending institution or arrives at the receiving institution. Furthermore, portable devices such as mobile card-issuing devices, tablets, and laptops are typically used by account managers for outdoor marketing and business trips. Due to the flexibility and high frequency of use of these devices, recording the departure time in the system each time is inefficient and increases the workload of frontline staff. These asset usage scenarios demonstrate that existing bank asset management systems can only trace the approval time of asset departure, lacking the ability to assess and handle off-bank asset risks, posing potential security vulnerabilities. Summary of the Invention

[0003] This invention provides a method, apparatus, electronic device, and storage medium for non-financial asset risk assessment, enabling off-site tracking and management of bank non-financial assets and enhancing risk control capabilities.

[0004] According to one aspect of the present invention, a method for risk assessment of non-financial assets is provided, wherein a target institution is equipped with a biometric identifier and an RFID reader; each non-financial asset of the target institution is equipped with an asset tag corresponding to the institution; the asset tag can be identified by the RFID reader and indicates the institution to which the non-financial asset belongs; the biometric identifier is used to identify the biometric characteristics of objects entering or leaving the institution, and the method includes:

[0005] Obtain asset information of the target non-financial assets of the target institution, and determine the basic risk coefficient of the target non-financial assets based on the asset information; the asset information is used to describe the asset type, asset value and data storage type of the assets;

[0006] The system acquires action information of the target non-financial asset and determines the deviation of the target non-financial asset based on the action information. The action information includes first biometric information, first time information, and first institutional information. The first biometric information is the biometric characteristics of the object that took the target non-financial asset away from the target institution. The first time information is the time when the target non-financial asset was taken away from and / or taken back to the target institution. The first institutional information is the institutional information of the institution where the target non-financial asset was taken away from and / or taken back.

[0007] Based on the basic risk coefficient and the deviation, the target risk coefficient of the target non-financial asset is determined.

[0008] According to another aspect of the present invention, a non-financial asset risk assessment device is provided, wherein a target institution is equipped with a biometric identifier and an RFID reader; each non-financial asset of the target institution is equipped with an asset tag corresponding to the institution; the asset tag can be identified by the RFID reader and indicates the institution to which the non-financial asset belongs; the biometric identifier is used to identify the biometric characteristics of objects entering or leaving the institution, and the device includes:

[0009] The basic risk determination module is used to acquire asset information of the target non-financial assets of the target institution, and determine the basic risk coefficient of the target non-financial assets based on the asset information; the asset information is used to describe the asset type, asset value and data storage type of the assets.

[0010] A deviation determination module is used to acquire action information of the target non-financial asset and determine the deviation of the target non-financial asset based on the action information; the action information includes first biometric information, first time information, and first institutional information; the first biometric information is the biometric characteristics of the object that takes the target non-financial asset away from the target institution; the first time information is the time when the target non-financial asset is taken away from and / or taken back to the target institution; the first institutional information is the institutional information of the institution where the target non-financial asset is taken away from and / or taken back.

[0011] The risk assessment module is used to determine the target risk coefficient of the target non-financial asset based on the basic risk coefficient and the deviation.

[0012] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0013] At least one processor; and

[0014] A memory communicatively connected to the at least one processor; wherein,

[0015] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the non-financial asset risk assessment method according to any embodiment of the present invention.

[0016] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the non-financial asset risk assessment method according to any embodiment of the present invention.

[0017] The technical solution of this invention involves acquiring asset information of a target non-financial asset from a target institution, determining the basic risk coefficient of the target non-financial asset based on the asset information, and using asset information to determine the basic risk coefficient of the target non-financial asset to ensure more accurate risk control of the target non-financial asset, since asset information is used to describe the asset type, asset value, and data storage type. Then, the action information of the target non-financial asset is acquired, and the deviation of the target non-financial asset is determined based on the action information. The action information includes first biometric information, first time information, and first institutional information; the first biometric information is the biometric characteristics of the object that took the target non-financial asset away from the target institution. The first biometric information refers to the time when the target non-financial asset is taken away from and / or returned to the target institution; the first institutional information refers to the institution where the target non-financial asset is taken away from and / or returned. The introduction of the first biometric information, the first biometric information, and the first institutional information enables precise control over the deviation of the target non-financial asset, thereby accurately analyzing the risk of the target non-financial asset deviating from the normal range; finally, based on the basic risk coefficient and the deviation, the target risk coefficient of the target non-financial asset is determined, so as to realize real-time risk assessment of the asset departure situation based on the target risk coefficient, and to carry out corresponding processing operations according to the assessment results, thereby realizing the bank's off-site tracking management of non-financial assets and improving risk prevention and control capabilities.

[0018] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1This is a flowchart of a non-financial asset risk assessment method provided by an embodiment of the present invention;

[0021] Figure 2 A schematic diagram of the structure of a non-financial asset risk assessment device according to an embodiment of the present invention;

[0022] Figure 3 A schematic diagram of the structure of an electronic device for implementing the non-financial asset risk assessment method of the present invention, provided in an embodiment of the present invention. Detailed Implementation

[0023] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0024] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0025] Example 1

[0026] Figure 1 This is a flowchart illustrating a non-financial asset risk assessment method provided in an embodiment of the present invention. This embodiment is applicable to assessing the non-financial assets of an institution. The method can be executed by a non-financial asset risk assessment device, which can be implemented in hardware and / or software and can be configured in any electronic device with network communication capabilities. Figure 1 As shown, the non-financial asset risk assessment method of the present invention may include:

[0027] S110. Obtain asset information of the target non-financial assets of the target institution, and determine the basic risk coefficient of the target non-financial assets based on the asset information; the asset information is used to describe the asset type, asset value and data storage type of the assets.

[0028] The target organization of this invention is equipped with a biometric identifier and an RFID reader; each non-financial asset of the target organization is equipped with an asset tag corresponding to the organization; the asset tag can be identified by the RFID reader and indicates the organization to which the non-financial asset belongs; the biometric identifier is used to identify the biometric characteristics of objects entering and leaving the organization.

[0029] The biometric identifier can be a fingerprint reader or a facial recognition camera; it can be configured at the institution's entrances and exits. For example, a facial recognition camera can be a security camera, allowing the acquisition of an individual's biometric characteristics without requiring additional hardware deployment. The asset tag can contain basic information about the corresponding non-financial asset, enabling RFID readers to sense and read this information, thus knowing whether the non-financial asset has left or returned to the institution.

[0030] Among them, asset types can be classified according to whether the institution's asset catalog involves production and operation. The more non-financial assets are involved in production and operation, the higher the risk coefficient.

[0031] Asset value can be understood as the intrinsic value of a non-financial asset. It can be categorized according to an institution's financial management practices. The higher the asset value of a non-financial asset, the higher its risk coefficient. For example, a first value threshold and a second value threshold can be set, with the first value threshold being lower than the second value threshold. If the asset value is lower than the first value threshold, the risk coefficient is the first preset risk. If the asset value is higher than the first value threshold but lower than the second value threshold, the risk coefficient is the second preset risk. If the asset value is higher than the second value threshold, the risk coefficient is the third preset risk. The first preset risk is lower than the second preset risk, and the second preset risk is lower than the third preset risk.

[0032] Data storage type can be understood as the data type stored in non-financial assets, and can be divided into three categories: office data, production data, and confidential data. For example, for assets involving office data, the risk coefficient is the fourth pre-set risk; for assets involving production data, the risk coefficient is the fifth pre-set risk; and for assets involving confidential data, the risk coefficient is the sixth pre-set risk. The fourth pre-set risk is less than the fifth pre-set risk, and the fifth pre-set risk is less than the sixth pre-set risk.

[0033] In an embodiment of the present invention, optionally, determining the underlying risk coefficient of the target non-financial asset based on asset information may include steps A1-A2:

[0034] Step A1: Determine the first risk coefficient based on the asset type in the asset information; determine the second risk coefficient based on the asset value in the asset information; determine the third risk coefficient based on the data storage type in the asset information.

[0035] Specifically, if there is a first pre-established relationship between different asset types and risk coefficients, then a first risk coefficient can be matched based on the asset type in the asset information from the first pre-established relationship. If there is a second pre-established relationship between different asset values ​​and risk coefficients, then a second risk coefficient can be matched based on the asset value in the asset information from the second pre-established relationship. If there is a third pre-established relationship between different data storage types and risk coefficients, then a third risk coefficient can be matched based on the data storage type in the asset information from the first pre-established relationship.

[0036] Step A2: Determine the basic risk coefficient of the target non-financial asset based on the first risk coefficient, the second risk coefficient, and the third risk coefficient.

[0037] Specifically, the first risk coefficient, the second risk coefficient, and the third risk coefficient are weighted and calculated to obtain the basic risk coefficient of the target non-financial asset.

[0038] In this embodiment of the invention, a first risk coefficient is determined based on the asset type in the asset information; a second risk coefficient is determined based on the asset value in the asset information; a third risk coefficient is determined based on the data storage type in the asset information; and then, based on the first, second, and third risk coefficients, the basic risk coefficient of the target non-financial asset is determined. The introduction of various types of data ensures the accuracy of determining the basic risk coefficient of the target non-financial asset.

[0039] S120. Obtain action information of the target non-financial asset, and determine the deviation of the target non-financial asset based on the action information; the action information includes first biometric information, first time information and first institutional information; the first biometric information is the biometric characteristics of the object that takes the target non-financial asset away from the target institution; the first time information is the time when the target non-financial asset is taken away from and / or taken back to the target institution; the first institutional information is the institutional information of the target non-financial asset being taken away from and / or taken back.

[0040] Specifically, there is a pre-defined correspondence between action information and the deviation of non-financial assets, and thus, based on the action information of the target non-financial assets, the appropriate deviation of the target non-financial assets can be matched from the pre-defined correspondence.

[0041] Optionally, in this embodiment of the invention, determining the deviation of the target non-financial asset based on action information may include steps B1-B4:

[0042] Step B1: Obtain the second biometric information. Based on the similarity between the first and second biometric information, determine the first deviation of the target non-financial asset. The second biometric information is the biometric characteristics of the user of the target non-financial asset registered in advance.

[0043] Specifically, when the first object carrying the target non-financial asset leaves the target institution, the biometric identifier will identify the first object's first biometric information, and then determine the similarity between the first biometric information and the second biometric information, so as to determine the first deviation of the target non-financial asset based on the similarity. If the similarity is less than the preset similarity, it means that the second object corresponding to the second biometric information is not the same object as the first object. In this case, the corresponding first deviation will be very high, and the back-office staff will be promptly alerted to manage it in time, which greatly improves the risk management capability.

[0044] Step B2: Obtain the second time information. Based on the first and second time information, determine the second deviation of the target non-financial asset. The second time information is the planned time for the target non-financial asset to be taken away from and / or taken back to the target institution, which is recorded in advance.

[0045] For example, when a target non-financial asset is taken away from the target institution, the time when the RFID reader deployed in the institution reads the asset tag is the actual departure time, i.e., the first time information. At this time, the second time information is the planned time when the target non-financial asset is taken away from the target institution, which is recorded in advance. When the second time information is before the first time information, the second deviation is high; when the second time information is after the first time information, the second deviation is low.

[0046] When the target non-financial asset is brought back to the target institution, the time when the RFID reader deployed in the institution reads the asset tag is the actual arrival time, i.e., the first time information. At this time, the second time information is the planned time when the target non-financial asset is brought back to the target institution, which is recorded in advance. If the second time information is after the first time information, the second deviation is high; if the second time information is before the first time information, the second deviation is low.

[0047] Optionally, the first time information includes the first arrival time and the first departure time; the second time information includes the second arrival time and the second departure time; determining the second deviation of the target non-financial asset based on the first time information and the second time information may include: determining a first reference deviation based on the comparison result of the first arrival time and the second arrival time; determining a second reference deviation based on the comparison result of the first departure time and the second departure time; and determining the second deviation of the target non-financial asset based on the first reference deviation and / or the second reference deviation, thereby achieving accurate determination of the second deviation of the target non-financial asset.

[0048] Step B3: Obtain the second institution information. Based on the first and second institution information, determine the third deviation of the target non-financial asset. The second institution information is the institution information deployed by the RFID reader that identifies the first institution information when the target non-financial asset is taken away and / or taken back.

[0049] For example, when the target non-financial asset is taken away from the target institution, the first RFID reader reads the institution to which the asset tag belongs, i.e., the first institution information. The second institution information is the institution information deployed by the RFID reader that identifies the first institution information when the target non-financial asset is taken away. Then the first institution information and the second institution information are compared. If the comparison results are inconsistent, the third deviation is high, and the corresponding value is set.

[0050] When the target non-financial asset is brought back to the target institution, the RFID reader reads the institution to which the asset tag belongs, i.e., the first institution information. The second institution information is the institution information deployed by the RFID reader that identifies the first institution information when the target non-financial asset is brought back. Then the first institution information and the second institution information are compared. If the comparison results are inconsistent, the third deviation is high, and the corresponding value is set.

[0051] Optionally, the first institutional information includes first outgoing institutional information and first arriving institutional information; the second institutional information includes second outgoing institutional information and second arriving institutional information; determining the third deviation of the target non-financial asset based on the first and second institutional information may include: determining a third reference deviation based on the comparison results of the first and second outgoing institutional information; determining a fourth reference deviation based on the comparison results of the first and second arriving institutional information; and determining the third deviation of the target non-financial asset based on the third reference deviation and / or the fourth reference deviation, thereby achieving accurate determination of the third deviation of the target non-financial asset.

[0052] Step B4: Determine the deviation of the target non-financial asset based on the first deviation, the second deviation, and the third deviation.

[0053] Specifically, based on the comparison results between the first deviation, the second deviation, and the third deviation and the preset deviation, corresponding deviation weight values ​​are matched for the first deviation, the second deviation, and the third deviation, and the sum of the three deviation weight values ​​is 1. Then, the first deviation, the second deviation, and the third deviation are weighted and calculated based on the deviation weight values ​​to obtain the deviation of the target non-financial asset.

[0054] In this embodiment of the invention, a first deviation of the target non-financial asset corresponding to the first biometric information, a second deviation of the target non-financial asset corresponding to the first time information, and a third deviation of the target non-financial asset corresponding to the first institutional information are determined respectively. Based on the first deviation, the second deviation, and the third deviation, the deviation of the target non-financial asset is determined, thereby realizing a comprehensive assessment of the risk of the target non-financial asset through multiple factors and ensuring the accuracy of the risk assessment of the target non-financial asset.

[0055] S130. Based on the basic risk coefficient and deviation, determine the target risk coefficient of the target non-financial asset.

[0056] Specifically, there is a pre-defined correlation between the base risk coefficient and the deviation and the risk coefficient, thereby matching the target risk coefficient of the target non-financial asset from the pre-defined correlation based on the base risk coefficient and the deviation. The pre-defined correlation can be a linear relationship between the weighted calculation result of the base risk coefficient and the deviation and the risk coefficient.

[0057] Optionally, the target risk coefficient of the target non-financial asset is determined based on the basic risk coefficient and the deviation, including: determining the weighting coefficients of the deviation and the basic risk coefficient based on the comparison results between the deviation and the preset deviation threshold; and determining the target risk coefficient of the target non-financial asset based on the basic risk coefficient, the deviation, and the weighting coefficients.

[0058] Specifically, if the deviation is greater than or equal to a preset deviation threshold, the deviation is matched with a first weighting coefficient, the basic risk coefficient is matched with a second weighting coefficient, and the first weighting coefficient is greater than the second weighting coefficient, and the sum of the first and second weighting coefficients is 1; if the deviation is less than the preset deviation threshold, the deviation is matched with the second weighting coefficient, and the basic risk coefficient is matched with the first weighting coefficient. Furthermore, based on the first weighting coefficient, the second weighting coefficient, the basic risk coefficient, and the deviation, the target risk coefficient of the target non-financial asset is determined, achieving accurate determination of the target risk coefficient.

[0059] Optionally, after determining the target risk coefficient of the target non-financial asset, the method further includes: assessing the risk level of the target non-financial asset based on the target risk coefficient. Specifically, if the target risk coefficient is less than or equal to a first risk threshold, the risk level is level one; if the target risk coefficient is greater than the first risk threshold and less than a second risk threshold, the risk level is level two; if the target risk coefficient is greater than or equal to the second risk threshold, the risk level is level three; level one is lower than level two, and level two is lower than level three. This facilitates determining whether corresponding risk management is needed based on the risk level, and risk alerts can be sent through the risk management module, for example, by sending specific risk details and related asset information to relevant personnel via email, SMS, or telephone. This allows asset administrators to formulate corresponding risk management operations based on different risk levels, minimizing potential losses from asset out-of-pocket risks.

[0060] The technical solution of this invention involves acquiring asset information of a target non-financial asset from a target institution, determining the basic risk coefficient of the target non-financial asset based on the asset information, and using asset information to determine the basic risk coefficient of the target non-financial asset to ensure more accurate risk control of the target non-financial asset, since asset information is used to describe the asset type, asset value, and data storage type. Then, the action information of the target non-financial asset is acquired, and the deviation of the target non-financial asset is determined based on the action information. The action information includes first biometric information, first time information, and first institutional information; the first biometric information is the biometric characteristics of the object that took the target non-financial asset away from the target institution. The first biometric information refers to the time when the target non-financial asset is taken away from and / or returned to the target institution; the first institutional information refers to the institution where the target non-financial asset is taken away from and / or returned. The introduction of the first biometric information, the first biometric information, and the first institutional information enables precise control over the deviation of the target non-financial asset, thereby accurately analyzing the risk of the target non-financial asset deviating from the normal range; finally, based on the basic risk coefficient and the deviation, the target risk coefficient of the target non-financial asset is determined, so as to realize real-time risk assessment of the asset departure situation based on the target risk coefficient, and to carry out corresponding processing operations according to the assessment results, thereby realizing the bank's off-site tracking management of non-financial assets and improving risk prevention and control capabilities.

[0061] Example 2

[0062] Figure 2This is a schematic diagram of a non-financial asset risk assessment device provided in an embodiment of the present invention. This embodiment is applicable to the assessment of an institution's non-financial assets. The non-financial asset risk assessment device can be implemented in hardware and / or software and can be configured in any electronic device with network communication capabilities. The target institution is equipped with a biometric identifier and an RFID reader; each non-financial asset of the target institution is equipped with an asset tag corresponding to the institution; the asset tag can be identified by the RFID reader and indicates the institution to which the non-financial asset belongs; the biometric identifier is used to identify the biometric characteristics of objects entering or leaving the institution, such as... Figure 2 As shown, the non-financial asset risk assessment device of the present invention may include:

[0063] The basic risk determination module 210 is used to obtain asset information of the target non-financial assets of the target institution, and determine the basic risk coefficient of the target non-financial assets based on the asset information; the asset information is used to describe the asset type, asset value and data storage type of the asset.

[0064] The deviation determination module 220 is used to acquire the action information of the target non-financial asset and determine the deviation of the target non-financial asset based on the action information; the action information includes first biometric information, first time information, and first institutional information; the first biometric information is the biometric characteristics of the object that takes the target non-financial asset away from the target institution; the first time information is the time when the target non-financial asset is taken away from and / or taken back to the target institution; the first institutional information is the institutional information of the institution where the target non-financial asset is taken away from and / or taken back.

[0065] Risk assessment module 230 is used to determine the target risk coefficient of the target non-financial asset based on the basic risk coefficient and the deviation.

[0066] Based on the above embodiments, optionally, the basic risk determination module is used to: determine a first risk coefficient based on the asset type in the asset information; determine a second risk coefficient based on the asset value in the asset information; determine a third risk coefficient based on the data storage type in the asset information; and determine the basic risk coefficient of the target non-financial asset based on the first risk coefficient, the second risk coefficient, and the third risk coefficient.

[0067] Based on the above embodiments, optionally, the deviation determination module includes: a first deviation determination unit, a second deviation determination unit, and a third deviation determination unit; the first deviation determination unit is used to acquire second biometric information and determine a first deviation of the target non-financial asset based on the similarity between the first biometric information and the second biometric information; the second biometric information is the biometric characteristics of the user of the target non-financial asset registered in advance; the second deviation determination unit is used to acquire second time information and determine a second deviation of the target non-financial asset based on the first time information and the second time information; the second time information is the planned time for the target non-financial asset to be taken away from and / or taken back to the target institution as recorded in advance; the third deviation determination unit is used to acquire second institution information and determine a third deviation of the target non-financial asset based on the first institution information and the second institution information; the second institution information is the institution information deployed by the RFID reader that identifies the first institution information when the target non-financial asset is taken away from and / or taken back.

[0068] The deviation determination unit is used to determine the deviation of the target non-financial asset based on the first deviation, the second deviation, and the third deviation.

[0069] Based on the above embodiments, optionally, the first time information includes a first arrival time and a first departure time; the second time information includes a second arrival time and a second departure time; the second deviation determination unit is configured to: determine a first reference deviation based on the comparison result of the first arrival time and the second arrival time; determine a second reference deviation based on the comparison result of the first departure time and the second departure time; and determine a second deviation of the target non-financial asset based on the first reference deviation and / or the second reference deviation.

[0070] Based on the above embodiments, optionally, the first institution information includes first outgoing institution information and first arriving institution information; the second institution information includes second outgoing institution information and second arriving institution information; the third deviation determination unit is used to: determine a third reference deviation based on the comparison result of the first outgoing institution information and the second outgoing institution information; determine a fourth reference deviation based on the comparison result of the first arriving institution information and the second arriving institution information; and determine a third deviation of the target non-financial asset based on the third reference deviation and / or the fourth reference deviation.

[0071] Based on the above embodiments, optionally, the risk assessment module is used to: determine the weighting coefficient of the deviation degree and the basic risk coefficient based on the comparison result of the deviation degree and the preset deviation threshold; and determine the target risk coefficient of the target non-financial asset based on the basic risk coefficient, the deviation degree and the weighting coefficient.

[0072] Optionally, based on the above embodiments, the risk assessment module is further configured to: assess the risk level of the target non-financial asset based on the target risk coefficient.

[0073] The non-financial asset risk assessment device provided in the embodiments of the present invention can execute the non-financial asset risk assessment method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0074] Example 3

[0075] According to embodiments of this disclosure, this disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0076] Figure 3 A schematic diagram of an electronic device that can be used to implement the non-financial asset risk assessment method of embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0077] like Figure 3 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0078] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0079] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, central processing unit (CPU), graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as non-financial asset risk assessment methods.

[0080] In some embodiments, the non-financial asset risk assessment method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via read-only memory (ROM) 12 and / or communication unit 19. When the computer program is loaded into random access memory (RAM) 13 and executed by processor 11, one or more steps of the non-financial asset risk assessment method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the non-financial asset risk assessment method by any other suitable means (e.g., by means of firmware).

[0081] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), system-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0082] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0083] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0084] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0085] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0086] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0087] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and no limitation is imposed herein.

[0088] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for assessing the risk of non-financial assets, characterized in that, The target institution is equipped with a biometric identifier and an RFID reader; each non-financial asset of the target institution is equipped with an asset tag corresponding to the institution; the asset tag can be identified by the RFID reader and indicates the institution to which the non-financial asset belongs; the biometric identifier is used to identify the biometric characteristics of objects entering or leaving the institution, and the method includes: Obtain asset information of the target non-financial assets of the target institution, and determine the basic risk coefficient of the target non-financial assets based on the asset information; the asset information is used to describe the asset type, asset value and data storage type of the assets; The system acquires action information of the target non-financial asset and determines the deviation of the target non-financial asset based on the action information. The action information includes first biometric information, first time information, and first institutional information. The first biometric information is the biometric characteristics of the object that took the target non-financial asset away from the target institution. The first time information is the time when the target non-financial asset was taken away from and / or taken back to the target institution. The first institutional information is the institutional information of the institution where the target non-financial asset was taken away from and / or taken back. Based on the basic risk coefficient and the deviation, the target risk coefficient of the target non-financial asset is determined.

2. The method according to claim 1, characterized in that, Based on the aforementioned asset information, the underlying risk coefficient of the target non-financial asset is determined, including: Based on the asset type in the aforementioned asset information, a first risk coefficient is determined; A second risk coefficient is determined based on the asset value in the aforementioned asset information; Based on the data storage type in the asset information, a third risk coefficient is determined; Based on the first risk coefficient, the second risk coefficient, and the third risk coefficient, the underlying risk coefficient of the target non-financial asset is determined.

3. The method according to claim 1, characterized in that, Determining the deviation of the target non-financial asset based on the aforementioned action information includes: Obtain second biometric information, and determine the first deviation of the target non-financial asset based on the similarity between the first biometric information and the second biometric information; the second biometric information is the biometric characteristics of the user of the target non-financial asset registered in advance. Obtain second time information, and determine the second deviation of the target non-financial asset based on the first time information and the second time information; the second time information is the planned time for the target non-financial asset to be taken away from and / or taken back to the target institution as recorded in advance. Obtain second institutional information, and determine a third deviation of the target non-financial asset based on the first institutional information and the second institutional information; the second institutional information is the institutional information deployed by the RFID reader that identifies the first institutional information when the target non-financial asset is taken away and / or taken back. The deviation of the target non-financial asset is determined based on the first deviation, the second deviation, and the third deviation.

4. The method according to claim 3, characterized in that, The first time information includes the first arrival time and the first departure time; the second time information includes the second arrival time and the second departure time. Based on the first time information and the second time information, the second deviation of the target non-financial asset is determined, including: Based on the comparison results of the first arrival time and the second arrival time, a first reference deviation is determined; Based on the comparison results of the first departure time and the second departure time, a second reference deviation is determined; A second deviation of the target non-financial asset is determined based on the first reference deviation and / or the second reference deviation.

5. The method according to claim 3, characterized in that, The first institutional information includes first outgoing institutional information and first arriving institutional information; the second institutional information includes second outgoing institutional information and second arriving institutional information; based on the first institutional information and the second institutional information, a third deviation of the target non-financial asset is determined, including: Based on the comparison results between the first departure mechanism information and the second departure mechanism information, a third reference deviation is determined; Based on the comparison results of the first arrival agency information and the second arrival agency information, a fourth reference deviation is determined; The third deviation of the target non-financial asset is determined based on the third reference deviation and / or the fourth reference deviation.

6. The method according to claim 1, characterized in that, Based on the aforementioned basic risk coefficient and the aforementioned deviation, the target risk coefficient of the target non-financial asset is determined, including: Based on the comparison result between the deviation degree and the preset deviation threshold, the weighting coefficients of the deviation degree and the basic risk coefficient are determined; The target risk coefficient of the target non-financial asset is determined based on the basic risk coefficient, the deviation, and the weighting coefficient.

7. The method according to claim 1, characterized in that, After determining the target risk coefficient of the target non-financial asset, the method further includes: The risk level of the target non-financial asset is assessed based on the target risk coefficient.

8. A non-financial asset risk assessment device, characterized in that, The target institution is equipped with a biometric identifier and an RFID reader; each non-financial asset of the target institution is equipped with an asset tag corresponding to the institution; the asset tag can be identified by the RFID reader and indicates the institution to which the non-financial asset belongs; the biometric identifier is used to identify the biometric characteristics of objects entering or leaving the institution, and the device includes: The basic risk determination module is used to acquire asset information of the target non-financial assets of the target institution, and determine the basic risk coefficient of the target non-financial assets based on the asset information; the asset information is used to describe the asset type, asset value and data storage type of the assets. A deviation determination module is used to acquire action information of the target non-financial asset and determine the deviation of the target non-financial asset based on the action information; the action information includes first biometric information, first time information, and first institutional information; the first biometric information is the biometric characteristics of the object that takes the target non-financial asset away from the target institution; the first time information is the time when the target non-financial asset is taken away from and / or taken back to the target institution; the first institutional information is the institutional information of the institution where the target non-financial asset is taken away from and / or taken back. The risk assessment module is used to determine the target risk coefficient of the target non-financial asset based on the basic risk coefficient and the deviation.

9. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the non-financial asset risk assessment method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that, when executed by a processor, implement the non-financial asset risk assessment method according to any one of claims 1-7.

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