Commodity Exposure Management via Atomic Segmentation
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Solution Overview
Problem
Existing exposure management systems struggle to efficiently calculate and adjust variable or floating price exposures in sales and purchase orders, and lack an intuitive methodology to restructure atomic level exposures into aggregated positions needed for hedging, accounting, and legal requirements, especially in industries like metals, mining, and oil.
Innovation Solution
A service-oriented architecture (SOA) is used to send messages between systems, parsing pricing formulas to create sub raw exposure line items at atomic levels, regrouping them to calculate exposure positions based on actions, commodities, and circumstances, with mapping rules to update and report exposure positions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing exposure management systems are used to calculate fixed price exposures, then the calculation is straightforward, but the system becomes difficult and cumbersome to configure for variable or floating price exposures
Solution Approach 1:
The patent segments the exposure calculation process into atomic level components (individual sales and purchase orders with their specific pricing formulas) that can be independently configured and then aggregated. This allows the system to handle variable and floating price exposures by breaking them down into manageable atomic units rather than requiring complex overall system reconfiguration.
Solution Approach 2:
The patent implements dynamic exposure calculation by allowing pricing formulas to reference multiple futures exchange prices over different time periods. The system can adapt to changing market conditions and adjust exposures as circumstances change (when commodities are ordered versus shipped versus delivered versus paid for), making the system versatile without proportionally increasing configuration complexity.
2Measurement precision
If atomic level exposure analysis is performed, then detailed exposure information is obtained, but the process of restructuring into aggregated exposure positions becomes difficult
Solution Approach 1:
The patent introduces a new dimensional approach by organizing exposures along multiple axes simultaneously - atomic level transactions, commodity types, pricing formulas, and aggregation levels. This multi-dimensional structure allows the system to maintain detailed atomic level analysis while providing intuitive restructuring capabilities by viewing exposures from different organizational perspectives without increasing procedural complexity.
3Reliability
If the system adjusts exposure positions as circumstances change, then accurate risk management is achieved, but the time and effort required to update exposures increases
Solution Approach 1:
The patent implements preliminary action by pre-configuring pricing formulas and exposure calculation rules at the atomic level. When circumstances change (orders, shipments, deliveries, payments), the system automatically applies these pre-established rules to adjust exposures, eliminating the need for manual recalculation and reducing update time while maintaining accuracy.
Solution Approach 2:
The patent incorporates feedback mechanisms that automatically detect changes in circumstances (commodity ordering, shipping, delivery, payment status) and trigger corresponding exposure adjustments. This closed-loop system ensures accurate risk management by continuously monitoring and updating exposures based on actual transaction progress without requiring manual intervention at each stage.
Data Source
AI summary
A message may be used to update computing system of a commodity transaction. The message may include a commodity identifier, a date term, a quantity term, and a price term. The price term may include a formula arrangement or reference to a formula arrangement for calculating a fractional exposure of the entity to the commodity on each date in which an event affecting commodity transaction occurs. Each of these fractional exposures may be calculated for each commodity transaction and stored as separate entries in a data structure. The entries may then be updated, queried, and/or reorganized to generate an exposure position.