MAS Unveils FEAT Principles to Promote Responsible Use of AI and Data Analytics

MAS Unveils FEAT Principles to Promote Responsible Use of AI and Data Analytics

by November 12, 2018

The Monetary Authority of Singapore (MAS) has released a set of principles to promote fairness, ethics, accountability and transparency (FEAT) in the use of artificial intelligence (AI) and data analytics in finance.

Known as the FEAT Principles, the document provides guidance to firms offering financial products and services on the responsible use of AI and data analytics, to strengthen internal governance around data management and use.

This will foster greater confidence and trust in the use of AI and data analytics, as firms increasingly adopt technology tools and solutions to support business strategies and in risk management.

MAS has worked closely with a group of senior industry partners through a FEAT Committee in developing the Principles. The Principles also incorporates views and feedback from financial institutions, industry associations, FinTech firms, technology providers and academia. The Committee is co-chaired by MAS Chief Data Officer, Dr David Hardoon, and Mr Hsieh Fu Hua, Co-Founder and Advisor, PrimePartners.

David Hardoon, MAS-FEAT-AIDADr David Hardoon said, “The FEAT Principles lay the foundation for a thriving AI and data analytics ecosystem. As the financial industry harnesses the potential of AI and data analytics on an increasing scale, we need to be cognisant of using these technologies in a responsible and ethical manner. The FEAT Principles are a significant first step that MAS has taken with the industry. I would also thank the FEAT committee members for their invaluable contribution towards this process.”


The summary of the principle are as follows:

A) Fairness

1. Individuals or groups of individuals are not systematically disadvantaged through AIDAdriven
decisions, unless these decisions can be justified.
2. Use of personal attributes as input factors for AIDA-driven decisions is justified.

Accuracy and Bias.

3.Data and models used for AIDA-driven decisions are regularly reviewed and validated for
accuracy and relevance, and to minimise unintentional bias.
4. AIDA-driven decisions are regularly reviewed so that models behave as designed and

B) Ethics

5. Use of AIDA is aligned with the firm’s ethical standards, values and codes of conduct.
6. AIDA-driven decisions are held to at least the same ethical standards as human driven

C) Accountability

Internal Accountability
7. Use of AIDA in AIDA-driven decision-making is approved by the appropriate internal authority.
8. Firms using AIDA are accountable for both internally developed and externally sourced AIDA models.
9. Firms using AIDA proactively raise management and Board awareness of their use of AIDA.

External accountability
10. Data subjects are provided with channels to enquire about, submit appeals for and request reviews of AIDA-driven decisions that affect them.
11. Verified and relevant supplementary data provided by data subjects are taken into account when performing a review of AIDA-driven decisions.


12. To increase public confidence, use of AIDA is proactively disclosed to data subjects as part of general communication.
13. Data subjects are provided, upon request, clear explanations on what data is used to make AIDA-driven decisions about the data subject and how the data affects the decision.
14. Data subjects are provided, upon request, clear explanations on the consequences that AIDA-driven decisions may have on them.

The full document can be found here