Automated CDS Pricing System with Risk Control Monitoring
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Solution Overview
Problem
The current CDS market lacks a meaningful mechanism to accurately determine market prices reflecting the quality of entities and underlying debt instruments, leading to significant pricing inefficiencies and risk exposure due to lack of visibility into risk positions, digital discontinuity, and inadequate risk modeling, particularly for bundled financial instruments.
Innovation Solution
A fully automated system for real-time pricing and risk control in online auctions of credit default swaps (CDS) using predetermined risk and quality factors, decoupling borrowers from debt issuers, eliminating rating inflation, and providing transparent risk monitoring and control through a reverse auction platform that accounts for primary and secondary insurance default risks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated pricing engines are used to compute bid prices for CDS, then pricing efficiency and speed are improved, but the accuracy of risk modeling and price discovery deteriorates due to lack of visibility into risk positions
Solution Approach 1:
The system implements feedback loops where auction results, trading volumes, and risk position data are continuously fed back into the pricing engine to refine bid price computations. This allows the automated system to learn from market outcomes and improve price accuracy over time while maintaining high productivity
Solution Approach 2:
The patent introduces an intermediary auction platform that sits between the automated pricing engines and the final price discovery process. This intermediary aggregates risk position data from multiple sources, applies risk control monitoring, and facilitates transparent bidding, thereby bridging the gap between automated computation and accurate price discovery
2Reliability
If risk control monitoring is implemented with full visibility into risk positions, then risk management accuracy is improved, but system complexity and data processing requirements worsen
Solution Approach 1:
The risk control system is segmented into modular components: risk data collection modules, risk position analysis modules, control rule engines, and monitoring dashboards. Each module handles specific aspects of risk monitoring independently, improving accuracy while managing complexity through modular architecture
Solution Approach 2:
The auction platform is designed with multi-functionality, serving simultaneously as a pricing engine, risk monitoring system, and transaction clearinghouse. This universal system reduces overall complexity by consolidating multiple functions into a single integrated platform rather than requiring separate systems for each function
3Measurement precision
If digital discontinuity is eliminated through continuous risk monitoring, then price discovery accuracy is improved, but data processing time and computational resources worsen
Solution Approach 1:
The system implements periodic risk position updates and price recalculations at predetermined intervals rather than continuously. This periodic action maintains accurate price discovery by capturing meaningful market changes while avoiding the excessive computational burden of truly continuous monitoring
Solution Approach 2:
The patent employs dynamic parameter adjustment where monitoring frequency and data processing intensity are changed based on market conditions. During periods of low volatility, monitoring intensity is reduced to save computational resources, while during high volatility periods, the system increases monitoring frequency to maintain accurate price discovery
Data Source
AI summary
Embodiments of the invention provide an innovative, fully-automated system that facilitates the buying and selling of debt-based derivatives and other assets. The techniques described herein eliminate opaqueness, inefficiencies, and lack of risk monitoring and provide an end-to-end, highly efficient reverse-auction platform that considers many aspects of risk control and other parameters. This is accomplished while computing a true CDS price by incorporating reference entity, primary and secondary insurance company default risks. Furthermore, the reference entity pricing model decouples the borrower from the entity issuing the debt and eliminates rating inflation due to digital discontinuity.