Using AI to Put Empathy Back into Banking

Think about ML as the winning team, with deep learning as the star player.

Meanwhile, the financial services industry is facing its own revolution. The use of physical cash and bank branches is steadily declining as customers go online. Retail banking products are becoming commoditized. As the industry goes digital, new players are entering the market. On one side, while capitalized Nasdaq majors such as Apple, Alibaba, Alphabet, and Tencent are launching payment platforms, current accounts, and wealth products, on the other side, we see new Fintechs such as Ant Financial, Acorns, Betterment, and Stripe attracting billions from venture capital and innovating relentlessly. Banking is in a period of rapid change and competition is becoming intense.

So, what about AI and banking? Interestingly, both banks and insurance companies have been using ML for longer than you might imagine. Predictive models, developed from the experience of past customer interactions, are used to forecast anything from credit and fraud losses to attrition and policy claims. While new ML algorithms will certainly improve the accuracy of these models, the big question is what new opportunities will this technology open up? Where do we go next?

The simplest and most compelling answer is at the heart of any business – its customers. If retail products are increasingly commoditized, then banks can only truly differentiate themselves by excelling in service. Clients may be attracted by brand and specific product features, but it is in the quality of delivery that they experience individually which most influences their buying decisions. One thing we all know about good service is that it starts with understanding and empathy. In the race to compete, it is easy to miss this human reality and become fixated with selling products. If we are to become truly client-centric, we need to transform our understanding of our customers, from financial consumers into real human beings who are emotional first and logical second.

Trying to figure out the emotional state and financial well-being of each of our clients may sound like a formidable challenge, but it is exactly the kind of challenge at which AI excels. Deep learning, the star player of the AI world, is uniquely positioned to deliver on this requirement. It excels in areas of facial expression capture, sentiment analysis, anomaly detection and other human-like skills required for emotional intelligence.

The bank of the future must put its customers front and centre in everything that it does. It must learn to know each of us by name and understand our individual emotional and financial needs. It must focus on our long-term financial health and care passionately about how we feel. The bank of the future will harness the immense power of AI to regain its empathy and deliver service with a human touch.