Greg brings the commercial dimension into focus. The shift from intuition-based decision-making to data-driven decision-making is, he argues, one of the most significant changes that AI and automation are enabling in financial services. But the quality of the output is entirely dependent on the quality of the input.“ If the underlying data isn’ t correct, you’ re just pushing bad data out faster and in an automated fashion,” Greg says.“ It really is the key to moving forward.” The goal, he adds, is to reach a point where the organisation has a single, trusted source of truth – data that is safe, accurate and reliably understood by everyone who uses it.
Karina puts the stakes in even sharper terms. Data-driven organisations earn customer trust by factually understanding their needs. But that same personalisation can backfire catastrophically if data is ever compromised.“ If their data is ever compromised, customers are not going to be happy that you thought you knew everything about them,” she says.
She continues:“ It is a double-edged sword being a data-centric business,” which still rings true in the headlines seen today.
For Karina, this is why the data conversation must sit alongside – not after – any discussion of AI transformation or risk strategy.“ The conversation around data must go hand in hand with any AI transformation risk discussion that anybody is having,” she says. fintechmagazine. com 69