Privacy-Preserving Inventory Matching via Secure Aggregation
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Solution Overview
Problem
Current inventory matching systems in financial markets reveal firms' trading intentions, leading to unfavorable trading conditions and increased costs, as they must disclose their inventory and clients' trading activities to facilitate matches, compromising privacy and efficiency.
Innovation Solution
Implementing privacy-preserving inventory matching methods using secure Multi-Party Computation (MPC) cryptographic protocols and additive homomorphic encryption schemes to mask clients' submissions, allowing for encrypted transactions without revealing identities or trading intentions until matches are confirmed, ensuring that only matched parties are notified.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the bank publishes an axe list to facilitate client trading matches, then trading activity and internalization are improved, but the bank's inventory and client trading activities are revealed, compromising privacy
Solution Approach 1:
The patent introduces a third-party service provider that acts as an intermediary between the bank and clients. This mediator aggregates trading data and facilitates matching while maintaining privacy through anonymization and encryption, allowing the bank to publish aggregated information without revealing individual client positions or intentions
Solution Approach 2:
The system creates anonymized copies of trading data for aggregation and matching purposes. Instead of sharing raw personal information, the system works with sanitized, aggregated representations that preserve trading activity patterns while removing identifiable details about individual clients and their specific positions
2Productivity
If the bank aggregates internal firm inventory along with risk inventory to construct the axe list, then trading internalization is achieved, but the bank leaks its own axe and client trading activity is revealed
Solution Approach 1:
The patent segments the aggregation process into separate components: internal firm inventory is aggregated separately from client risk inventory. The system can publish aggregated internal inventory without necessarily disclosing client-specific positions, allowing partial transparency that facilitates matching while preserving privacy for individual client data
Solution Approach 2:
Different levels of transparency are applied to different data types. Aggregated firm-level inventory information can be published to facilitate matching, while client-level detailed positions remain private. The system applies selective disclosure where only aggregated, anonymized data is shared, not raw individual client information
3Adaptability or versatility
If the bank performs trades in the public market when no internal matches are found, then trading flexibility is maintained, but additional costs are incurred and price impact increases
Solution Approach 1:
The system implements a feedback loop where client trading requests are continuously monitored and matched against available internal inventory. When matches are identified, the system facilitates internal trades that eliminate the need for public market execution, thereby reducing costs and price impact. The feedback mechanism enables real-time optimization of trading execution
Data Source
AI summary
Systems and methods for privacy-preserving inventory matching are disclosed. In one embodiment, in an information processing apparatus comprising at least one computer processor, a method for inventory matching may include: (1) receiving, from each of a plurality of clients, a masked submission comprising an identification of at least one security to buy or sell and a desired quantity to buy or sell; (2) aggregating the masked submissions resulting in a sum of the desired quantities to buy or sell; (3) matching at least two of the clients to conduct a transaction based on aggregation and their respective masked submissions; and (4) conducing the transaction between the matched clients.