The effective use of customer data by banks has become a key issue, according to a joint survey by EY and the Institute of International Finance (IIF).
Proper management of existing information can mean faster administration and better offers for customers. Breakthroughs can be brought about primarily by the application of artificial intelligence in the field, as machine learning is able to adapt dynamically to the ever-changing economic environment.
Over the next three years, almost all banks (93%) will focus on improving data quality, and linking different groups of information (57%) will also be a priority, according to a study of senior professionals from 74 banks in 29 countries. In addition to extracting valuable, better quality data (80%), decision-makers are most willing to invest in making it easier to access the information needed to develop a product or enhance the consumer experience (67%).
"Domestic banks place great emphasis on business and growth goals, but they are increasingly challenged to systematize unstructured data and develop new decision support models. Improving data quality - in addition to mandatory compliance with regulators - also acquiring new customers and developing the best product offerings "said János Hoós, Head of Financial Risk Management at EY.
According to respondents, financial institutions store a lot of poor quality data and there are few competent experts who can systematize, process and clean them (61%), which hinders developments. The need for a wide range of expertise is further exacerbated by the fact that supervisors are demanding the introduction of increasingly sophisticated financial models.
Banks would need new staff most in the area of financial risk modeling (70%). The lack of knowledgeable experts is an increasingly pressing problem in the industry. "The application of artificial intelligence can also bring a breakthrough in the field of data processing. Because machine learning can be used to develop complex, multi-dimensional models that can then be adapted to the ever-changing economic environment," he added.
Credit institutions ranked the risk of data loss (79%), industry transformation due to technological advances (79%), geopolitical problems (64%), and the risks of obsolescence of models used for various financial calculations (44%) as the most pressing challenges of the near future.
(Source: marmalade.co.hu; EY | Image: pixabay.com)