Enterprise Artificial Intelligence Transformation

Chapter 4AI in Financial Services

We're witnessing the creative destruction of financial services, rearranging itself around the consumer. Who does this in the most relevant, exciting way using data and digital, wins!

Arvind Sankaran, partner at Jungle Ventures

Although banks, asset managers, and other financial services companies tend to agree that AI is essential, they vary widely in why, how, and when to adopt this new technology. According to an article in the McKinsey Quarterly,¹ more than a dozen European banks are now using machine learning techniques instead of older statistical-modeling approaches, and some are now seeing up to 10% increases in new-product sales; 20% savings in capital expenditures; and a decline in customer churn of 20%. In 2018, the World Economic Forum reported that “a growing number of financial institutions are applying AI to customer advice and interactions, laying the groundwork for self-driving finance.”² One European bank, according to a McKinsey survey, was quoted in the Financial Times as having 500–800 people working in AI.³ Although these metrics seem impressive, it is likely that many of the examples are smaller proofs of concept rather than enterprise-wide applications of machine learning.

Financial institutions have large volumes of structured data, often already of high quality, which makes it amenable to AI use. Many banks are using AI for assessing and managing risk, such as in fraud detection and managing credit risk to approve ...