The AI Book

CHAPTER 57Algorithm Assurance

By Christian Spindler¹

¹CEO, DATA AHEAD ANALYTICS

Artificial intelligence (AI) is penetrating more and more elements of both personal lives and business processes. Especially in financial services – a data-driven business on the one hand, a regulated and privacy-concerned business on the other hand – the request for assurance, interpretability and fairness of AI algorithms rises. Regulatory organizations continue to raise their voice for a better understanding and control of the risks that come with AI.

The Financial Stability Board says that overall, “AI and machine learning applications show substantial promise if their specific risks are properly managed”. In November 2018, the Monetary Authority of Singapore published principles to foster fairness, ethics, accountability and transparency (FEAT) in the application of artificial intelligence and data analytics in the financial sector. The principles demand, for instance, that AI models shall be free of non-intended bias and companies which use AI models shall be responsible for both internally and externally developed components. Swiss regulator FINMA’s Circular 2013/8, states: “Supervised institutions that engage in algorithmic trading (see margin no. 18) must employ effective systems and risk controls to ensure that this cannot result in any false or misleading signals regarding the supply of, demand for or market price of securities. Supervised institutions must document the key features of ...