Clifford Chance

Artificial intelligence (AI) is well-known as the theory and development of computer systems able to perform tasks that traditionally have required human intelligence. Financial institutions have taken an increasing interest in this development and AI applications in such institutions have become increasingly common. They are already used in financial products and services, such as robo-advice (e.g. when taking out a mortgage), loan and insurance underwriting and algorithmic trading. AI applications are found both in front- and back-office functions of financial institutions, such as chatbots (for customer's queries), client onboarding tools, transaction data analysis, fraud detection, and risk and portfolio management.

Both on a European level and on a local level, the use of AI has caught the attention of regulators and supervisory authorities. In the Netherlands, the Dutch Central Bank (De Nederlandsche Bank, (DNB)) expects that the increased use of AI in the financial sector will have a big impact in the near future. With the growing use of AI, the influence that AI will have on (core) processes within financial institutions will also grow and with that operational, prudential and reputational risks may arise.

DNB starts a dialogue and coins SAFEST principles

To start a dialogue with the financial sector, DNB published a discussion paper 'General principles for the use of Artificial Intelligence in the financial sector' on 25 July 2019. This discussion paper formulates general principles for the use of AI applications by financial institutions. According to DNB, financial institutions using AI-driven applications should pay attention to six key principles, collectively known as 'SAFEST':

• Soundness
• Accountability
• Fairness
• Ethics
• Skills
• Transparency.

DNB stated that the SAFEST principles should be seen in the context of the regulatory requirement of "controlled and sound business operations". Proportionality applies to these principles and takes into consideration the scale, complexity and materiality of the AI applications. How the SAFEST principles are applied will also depend on the role a specific AI application takes in the decision-making process of the financial institution (i.e. whether the AI application serves a descriptive, diagnostic, predictive, prescriptive or automation purpose).

DNB refers to the below ‘heat map’ in this respect.