Securities Settlement Trade Aggregation for Deadlock-Free Clearing
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Solution Overview
Problem
Existing securities settlement systems face inefficiencies in clearing and settlement processes due to complex securities transactions, leading to increased demands for liquidity and frequent deadlocks, which hinder the 'speed to market' of new products and services.
Innovation Solution
A securities settlement system that aggregates trades into groups, minimizes the need for liquidity by optimizing the clearing process through incremental and aggregated clearing methods, and utilizes a comparator to ensure all obligations are met within user limits, employing algorithms to iteratively adjust trade groups for successful settlement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If trades are cleared one by one using traditional methods, then each trade can be processed individually, but the clearing process becomes slow and inefficient with frequent deadlocks
Solution Approach 1:
The patent combines multiple individual trade clearings into a single aggregated clearing operation. The system groups multiple trades that share common characteristics (such as same settlement date, same instrument type, or same counterparty) and processes them together as one batch, thereby reducing the total number of clearing operations and eliminating deadlocks that occur in sequential processing.
Solution Approach 2:
The patent segments the clearing process into distinct phases: trade collection, aggregation grouping, obligation calculation, and settlement execution. This segmentation allows the system to handle complex clearing scenarios by breaking them down into manageable steps, improving both speed and reliability of the overall clearing process.
2Loss of energy
If the system aggregates multiple trades into groups for clearing, then the number of transactions is reduced and liquidity demands are minimized, but the system complexity increases due to need for aggregation logic and obligation comparison
Solution Approach 1:
The patent implements a universal aggregation framework that can handle multiple types of trades, instruments, and settlement scenarios through a single set of aggregation rules and obligation comparison logic. The system uses standardized data structures and processing algorithms that work across different trade types, reducing the need for separate handling logic for each scenario.
Solution Approach 2:
The patent changes the parameter of processing from individual trade-level operations to aggregated group-level operations. By transforming the input data into aggregated obligation groups and processing these groups as units, the system reduces liquidity demands while managing complexity through parameter transformation rather than complex individual trade processing.
3Adaptability or versatility
If the system processes more complex securities transactions to meet global market demands, then the adaptability and speed to market improve, but the clearing and settlement processes become more complicated with increased deadlocks
Solution Approach 1:
The patent implements dynamic aggregation rules that can adapt to different market conditions, security types, and transaction characteristics. The system dynamically determines which trades to group together based on current market parameters, settlement rules, and liquidity conditions, allowing it to handle complex securities transactions while maintaining clearing reliability through flexible, condition-based aggregation.
Data Source
AI summary
Example embodiments of a data processing method, system, and non-transitory computer-readable medium are described.