Liquidity Engine for Netting Transaction Cash Positions
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Solution Overview
Problem
Payment processors face challenges in managing liquidity and mitigating currency risk when promising users access to funds at different times, currencies, or locations than the actual settlement, leading to unsustainable capital buffer requirements as transaction volume grows.
Innovation Solution
A centralized liquidity engine that aggregates transaction-level commitments, nets out cash imbalances, and plans cost-effective cash movements using machine learning for predicted inventory data, enabling efficient and compliant capital deployment across currencies and locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If payment processors maintain large capital buffers to meet user fund access promises across different times and currencies, then reliability of fund availability is improved, but device complexity and capital deployment efficiency worsen
Solution Approach 1:
The system segments capital management into multiple dimensions including currency type, geographic location, time horizon, and liquidity requirement. Each segment is managed independently with tailored strategies, allowing the payment processor to optimize capital deployment for each segment while maintaining overall reliability of fund availability.
Solution Approach 2:
The system dynamically changes capital deployment parameters based on real-time conditions including currency exchange rates, interest rate environments, liquidity requirements, and risk parameters. This allows the capital buffer to adapt its composition and deployment strategy while maintaining the reliability needed to meet user fund access promises.
2Adaptability or versatility
If payment processors hold capital in multiple currencies and locations to fulfill settlement promises, then adaptability to different user requirements is improved, but loss of substance through capital inefficiency worsens
Solution Approach 1:
The system creates a universal capital management framework that handles multiple currencies, locations, and time horizons through a single integrated platform. This multi-functional system optimizes capital deployment across all dimensions simultaneously, improving adaptability to different user requirements while minimizing capital inefficiency through centralized optimization.
Solution Approach 2:
The system performs preliminary capital deployment decisions based on predicted settlement patterns and liquidity requirements. By anticipating future cash flow needs and currency conversion requirements, the system pre-position capital in optimal locations and currencies, reducing the need for expensive last-minute capital movements and improving overall capital efficiency.
3Ease of operation
If payment processors move money globally to meet settlement promises, then ease of operation for users is improved, but loss of time in capital deployment worsens
Solution Approach 1:
The system introduces liquidity providers and financial intermediaries as mediators between the payment processor's capital and user fund access requirements. These intermediaries enable rapid global capital movements and currency conversions without requiring the payment processor to maintain physical capital in every location, thus improving user ease of access while reducing capital deployment time.
Solution Approach 2:
The system performs preliminary liquidity arrangements and pre-funded agreements with financial intermediaries to enable rapid capital deployment when needed. This preliminary setup allows the system to meet user fund access requests globally without experiencing delays in actual capital movement, as the pathways and agreements are already established in advance.
Data Source
AI summary
A method and apparatus for managing liquidity when processing transactions are disclosed. In some embodiments, the method is implemented by a computing device and comprises: receiving data for a plurality of transactions; continuously reading in and aggregating, with an aggregator implemented at least partially in hardware of the computing device, transactions to produce one or more netted currency positions based on a plurality of properties of the transactions and on a plurality of netting constraints; generating one or more tasks, using a trade generator implemented at least partially in hardware of the computing device, to route cash movements as one or more batched fund transfers based on one or more trading policies; and sending the one or more tasks via network communications to one or more entities to execute the batched fund transfers.