This paper aims to demonstrate the importance of a cash flow generating standard for individual financial contract level data and the ability to create such a standard.
The authors analyze the importance for such a standard of software that turns natural language contracts into cash flow generating algorithms; a data dictionary that standardizes contract terms; and access to variables that represent the state of the world (e.g. market risk, counterparty risk, etc.) that affect contractual obligations.
The ability to realize benefits from the use of such a contract level algorithmic standard depends on the following: making the standard’s software open source; fully testing the software to have complete confidence in its accuracy; and enabling the software to use of a wide range of models of various sources of risk (market, credit and behavior risk) to support forward-looking analysis. Such a standard would solve the disconnect that exists in financial firms between the representation of financial contracts for transaction processing and analysis. The ACTUS Financial Research Foundation is building, testing and making available such a standard that represents almost all financial contracts extant in markets.
The adoption of such a standard would reduce the costs of operations of financial firms, provide the computational infrastructure for more effective regulatory oversight, reduce regulatory reporting costs and improve financial market transparency. It would also enable the assessment of systemic risk by directly quantifying the interconnectedness of firms.
This is a new approach to financial analytics that clearly separates the deterministic components of finance, which can be standardized from the stochastic elements that cannot be standardized.
