Private-Asset Derivatives Platform With Segregated Access Control
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Solution Overview
Problem
Existing technologies face challenges in creating and managing private asset derivatives due to computational scalability issues, lack of transparency, and security concerns, particularly in cloud-based systems, which hinder efficient risk management and trading for diverse investors with varying needs.
Innovation Solution
A digital computer platform with segregated data storage and processing capabilities allows for the creation and management of private asset derivatives, utilizing machine-readable digital identities and archetypes to efficiently process and price derivative instruments, enabling secure and scalable transactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If cloud-based distributed infrastructure is used to store vast amounts of data, then data storage capacity is improved, but data security and access control become more difficult to manage
Solution Approach 1:
The system segments data storage into multiple logical subdivisions, each with its own access control policies. Data is organized into discrete units (digital identities, archetypes, instruments) that can be independently accessed and managed, allowing cloud infrastructure to provide vast storage while maintaining security through fine-grained access control at the data unit level.
Solution Approach 2:
The patent introduces an intermediary layer (the computing system with processors and databases) that mediates between cloud storage infrastructure and users. This intermediary enforces authentication, authorization, and access control policies, ensuring that even in a distributed cloud environment, data security is maintained through controlled access to digital identities and financial instruments.
2Productivity
If traditional financial markets infrastructure is used for private equity derivatives, then market liquidity is improved, but pricing complexity and transparency issues worsen
Solution Approach 1:
The system creates digital copies (digital identities) of private equity assets and their characteristics. These digital representations can be traded and priced without requiring direct access to the underlying complex private equity instruments, simplifying pricing while maintaining market liquidity through standardized digital instrument exchanges.
Solution Approach 2:
The patent transforms complex private equity asset characteristics into standardized parameters and archetypes that can be systematically priced and traded. By changing the representation from complex underlying assets to simplified digital instruments with defined parameters, the system reduces pricing complexity while enabling liquid trading.
3Reliability
If access to private equity derivatives is restricted to accredited investors only, then risk control is improved, but market accessibility and diversity worsen
Solution Approach 1:
The system implements dynamic access control where investor qualifications and permissions are not fixed but can change over time. The computing system continuously verifies investor status and adjusts access rights accordingly, allowing accredited investors to access appropriate instruments while potentially expanding access to other qualified participants, thus balancing risk control with market accessibility.
Data Source
AI summary
A computer-implemented system for creation, matching, and trading of private-asset derivative instruments (synthetic or standard) for portfolio management and risk transfer is provided. The system include one or more databases organized into logical subdivisions associated with users of different qualifications, the databases storing digital identities representing private assets, private-asset derivative instruments and derivatives archetypes. Processors, which can be cloud-deployed, are configured to receive user preferences for risk, return, and exposure; determine user access rights; identify or create a derivatives archetype that satisfies those preferences; and generate or return a corresponding private-asset derivative instrument for portfolio management, risk transfer, or trading. Archetypes are associated through machine-readable references with digital identities of corresponding instruments or their underlyings. The processors may employ quantitative or machine-learning models to convert user preferences into statistical descriptors, select private-asset representatives, project cash flows, and match users on a trading platform for execution or restructuring of transactions.