Data use has an impact on banks’ future business models
Banks must improve the quality of their data to optimise utilisation and safeguard the viability of their business models. Inadequate quality of data leads to inaccurate risk assessments. The use of data has an impact on banks’ profitability on the costs and income side. While data analytics initially require higher investments, they are necessary to improve core processes and will eventually result in lower costs and higher revenues. Data utilisation is essential to ensure effective prevention of financial crime and to bring down the costs of fraud. It offers opportunities for personalised digital customer contact and perfectly ties in with the requirements relating to convenience and user-friendliness (see Figure 1). The importance of data analytics for the core process of lending is set to increase still further. In some cases, credit scores based on new types of data and AI are already delivering better results than traditional credit assessment methods. Nevertheless, the use of personal data is at all times subject to explicit consent from the customer and must be permitted by law. Winners and losers will eventually emerge in this world of increased data utilisation and new data applications. Risks may concentrate with the latter group and market shares may shift as a consequence. As a supervisory authority we will stay alert and monitor the banks’ capacity for change and resolvability.
Focus on data in supervision
We will remind financial institutions of their responsibilities regarding the quality and viability of their data operations. We will monitor the governance of data used in core processes as part of institutions’ sound and ethical operational management. We will focus on questions about e.g. the origin of data, their intended use, data access rights, storage and security, updating and testing procedures and representativity. A new dimension is the application of AI, which uses data in e.g. chatbots and loan offers. We are actively exchanging knowledge with the sector and consult with institutions on the General principles for the use of AI in the financial sector, including soundness, accountability, fairness, ethics, skills and transparency aspects.