Creating a data-centric future driven by the latest advances in RegTech and artificial intelligence may sound like a lofty goal. Yet that is precisely what the Data Foundation is attempting to facilitate when it recently issued a set of eight recommendations to help create a platform for reporting government data in standardized and structured formats.
The Data Foundation, a non-profit think tank based in Washington, D.C., strives to deliver policy and rule changes to improve data quality, expand the use of data standards, and encourage the use of common terms and definitions for improved analytical capabilities.
To this end, the Data Foundation’s Open Data Standards Task Force identified eight areas in which the federal government could institute much-needed improvements to financial regulatory data beginning in 2021.
The first recommendation is to promote effective implementation of broad national data laws, such as the Foundations for Evidence-Based Policymaking Act of 2018 and the OPEN Government Data Act. Over the last decade, says the Data Foundation, these laws have established the legal authority “to promote the use of applicable data standards and establish new leadership capabilities, like chief data officers, and promote mechanisms for sound data management (i.e. learning agendas, data inventories, and data governance frameworks).”
Here are the remaining seven recommendations:
- Identify and address technology gaps.
- Prioritize data literacy training for agency staff.
- Support data sharing among Financial Stability Oversight Council (FSOC) member agencies.
- Improve data sharing between US financial regulatory agencies and statistical agencies.
- Encourage regular public-private exchanges with banking and financial institutions.
- Employ the use of nonproprietary identifiers and validation data tools to mitigate risks, reduce financial cybercrime, and improve data blending across agencies.
- Amplify efforts in the federal government that fortify supply chain traceability, visibility, and reliability.
The goal is that sweeping efforts to improve data quality—while also improving training on the expanded use of data standards-- will result in innovative and streamlined analytical programs, truly rooted in the modern, data-centric world. In this vision, human beings will spend less time reading documents. Rather, bots will collect data and then machine learning and artificial intelligence applications will streamline what’s collected and transform it into both structured and unstructured data.
To find out more about each of the eight recommendations, take a look at the Data Foundation’s recent publication “Ensuring Meaningful Management and Use of Financial Regulatory Data: Eight Policy Recommendations for the 2021 Transition.”