Finance:Algorithmic Contract Types Unified Standards

From HandWiki
Short description: ACTUS system for financial contracts


Algorithmic Contract Types Unified Standards, abbreviated to ACTUS, is an attempt to create a globally accepted set of definitions and a way of representing almost all financial contracts. Such standards are regarded as important for risk management, financial regulation, the tokenization of financial instruments, and the development of smart contracts for decentralized finance (DeFi) using blockchain. The ACTUS data standard has been included in a reference database run by the Office of Financial Research, an arm of the US Treasury.[1] An ACTUS Financial Research Foundation and the ACTUS Users Association control the intellectual property and development approaches.[2]

History

The difficulty of defining and analyzing financial data were described by Willi Brammertz and his co-authors in a 2009 book, Unified Financial Analysis: The missing links of finance.[3] The simplicity of the problem is described in an ECB paper, “Modelling metadata in central banks”. This cites the issue of how financial institutions have tried to overcome data silos by building enterprise-wide data warehouses. However, while these data warehouses physically integrate different sources of data, they do not conceptually unify them. For example, a single concept like notional value still might be captured in various ways in fields that might be labeled ‘nominal value,’ ‘current principal,’ ‘par value’ or ‘balance’.[4] Standardization of data would improve internal bank operations, and offer the possibility of large-scale financial risk analytics by leveraging Big Data technology.[5] Key to this is the idea of "contract types".[6]

The concepts were expanded upon by Brammertz and Allan I. Mendelowitz in a 2018 paper in the Journal of Risk Finance. They describe the need for software that turns natural language contracts into algorithms – smart contracts – that automate financial processes. The idea of such contracts predates digital currencies, but because there are only a limited number of cash flow exchange patterns, they identify less than three dozen smart contracts.[7] Underlying these contracts there has to be a data dictionary that standardizes contract terms.[8] In addition, the smart contracts have access to information representing the state of the world and which affects contractual obligations. This information would include variables such as market risk and counterparty risk held in online databases that are outside the blockchain (sometimes called "oracles"[9]).

The authors argue that the adoption of a standard for smart contracts and financial data would reduce the cost of operations for financial firms, provide a computational infrastructure for regulators, reduce regulatory reporting costs, and improve market transparency. Also, it would enable the assessment of systemic risk by directly quantifying the interconnectedness of firms.[10][11]

This led to the ACTUS proposal for a data standard alongside an algorithmic standard. Together, these can describe most financial instruments through 31 contract types or modular templates. The research foundation and users' association develop the structure to implement the ideas. The specifications[12] are developed, maintained, and released on GitHub.[13]

References

  1. ↑ "OFR Expands Its Financial Instrument Reference Database to Help Identify Inconsistencies in Financial Terms" (in en). https://content.govdelivery.com/accounts/USTREASOFR/bulletins/3369164. 
  2. ↑ "Home" (in en). https://www.actusfrf.org/. 
  3. ↑ Brammertz, Willi (2009). Unified Financial Analysis: The missing links of finance. Wiley. ISBN 978-0470697153. 
  4. ↑ https://www.ecb.europa.eu/pub/pdf/scpsps/ecbsp13.en.pdf
  5. ↑ Kurt, Stockinger; Heitz, Jonas; Bundi, Nils; Breymann, Wolfgang (December 2018). "Large-Scale Data-Driven Financial Risk Modeling Using Big Data Technology". 2018 IEEE/ACM 5th International Conference on Big Data Computing Applications and Technologies (BDCAT): 206–207. doi:10.1109/BDCAT.2018.00033. ISBN 978-1-5386-5502-3. https://ieeexplore.ieee.org/document/8606653. 
  6. ↑ Brammertz, Willi (2013), Lemieux, Victoria, ed., "The Office on Financial Research and Operational Risk" (in en), Financial Analysis and Risk Management: Data Governance, Analytics and Life Cycle Management (Berlin, Heidelberg: Springer): pp. 47–71, doi:10.1007/978-3-642-32232-7_3, ISBN 978-3-642-32232-7, https://doi.org/10.1007/978-3-642-32232-7_3, retrieved 2023-06-30 
  7. ↑ "Smart Contracts Were Around Long Before Cryptocurrency" (in en). 2016-11-17. https://www.americanbanker.com/opinion/smart-contracts-were-around-long-before-cryptocurrency. 
  8. ↑ Brammertz, Willi; Mendelowitz, Allan I. (2018-01-01). "From digital currencies to digital finance: the case for a smart financial contract standard". The Journal of Risk Finance 19 (1): 76–92. doi:10.1108/JRF-02-2017-0025. ISSN 1526-5943. https://doi.org/10.1108/JRF-02-2017-0025. 
  9. ↑ "Oracles" (in en). https://ethereum.org/. 
  10. ↑ Brammertz, Willi; Mendelowitz, Allan I. (2018-01-01). "From digital currencies to digital finance: the case for a smart financial contract standard". The Journal of Risk Finance 19 (1): 76–92. doi:10.1108/JRF-02-2017-0025. ISSN 1526-5943. https://doi.org/10.1108/JRF-02-2017-0025. 
  11. ↑ Brammertz, Willi (2010-01-01). Clacher, Iain. ed. "Risk and regulation". Journal of Financial Regulation and Compliance 18 (1): 46–55. doi:10.1108/13581981011019624. ISSN 1358-1988. https://doi.org/10.1108/13581981011019624. 
  12. ↑ "Technical Specification" (in en). https://www.actusfrf.org/techspecs. 
  13. ↑ "ACTUS Financial Research Foundation" (in en). https://github.com/actusfrf. 


Retrieved from "https://handwiki.org/wiki/index.php?title=Finance:Algorithmic_Contract_Types_Unified_Standards&oldid=3162096"