Machine learning: technology that learns from experience to predict the behavior of each individual.
— 2.6 billion cards globally. By detecting fraud with ML, a medium-sized bank could save about $16 million and, at the same time, improve the customer experience by decreasing the fraud its cardholders experience by about 60,000 cases . I consider Falcon one of the world’s most successful and widely impactful commercial deployments of ML.
This operation mostly goes unseen, but such unseen efficiencies often do more for the customer experience than the predictive operations that garner the most attention. FICO Falcon affects each consumer much more frequently than the most famous ML system, one that’s commonly known among consumers: the FICO Credit Score, a household name and a major factor in your power to borrow. Many understandably feel that their FICO Score is an important part of their identity as a consumer.
Of course, by helping the customer, companies also help themselves. These improvements to customer experience aren’t only a nice-to-have, pleasant side-effect of profit-driven ML deployments. They pursue theof the company — to serve customers — and will ultimately translate into further benefits for the business. After all, a happier customer is a more loyal customer, and a higher customer retention rate means a higher customer growth rate.
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