AI in customer experience, fraud prevention, and back-office operations is moving fast in banking and financial services, and the firms that fall behind risk losing both customers and competitive ground. Tedd Huff, CEO of fintech advisory firm Voalyre and founder of Fintech Confidential, sits down with Mamta Rodrigues, Chief Client Officer of Banking, Financial Services and Insurance at TP, one of the largest employers in the world with over 500,000 people globally. Mamta brings decades of hands-on experience across American Express, MasterCard, Visa, and Synchrony, and she holds a patent, a signal that she has spent real time building products, not just advising on them. The conversation covers practical AI use cases in fraud, collections, and compliance, along with what separates clients who get results from those who stall out after a pilot.The pressure on banks and fintechs right now comes from two directions at once. Consumer expectations keep rising because people interact with payment products every single day. At the same time, fraud is accelerating. Every time the industry catches up, fraudsters adapt faster and the cycle resets. That means fraud teams, product teams, and customer experience teams are all fighting for resources and attention at the same time. For treasury managers, CFOs, and compliance leaders, this creates a real tension: how do you invest in AI-powered fraud prevention and still deliver a smooth experience that keeps customers loyal?The numbers from inside TP's client work tell a clear story. Fifty percent of TP's solutions are now AI-led, with the heaviest concentration in back-office operations like fraud, financial crime, and claims management. Mamta describes a recent deployment of TP's AI blueprint, tp.ai fab, layered into an existing client's operations to prevent and predict fraud. The results showed significant improvement in key metrics. On the collections side, predictive analysis now arms agents before a call even starts with propensity to pay, likely timing, expected recovery percentage, and recommended remediation paths. That kind of preparation changes the entire tone of a collections interaction from adversarial to solution-oriented, and the outcome is measurable: increased repayment, stronger loyalty, product expansion, and reduced breakage.One of the clearest signals Mamta uses to gauge whether a client will actually get results versus abandon the effort after a test: the composition of who shows up. When the cross-functional team walks through the door, operations, product, IT, and data leaders together, that's when real progress happens. She describes a design thinking approach where the client provides a problem statement in advance, both sides bring the right people, and in a single day they can shape a solution direction. The typical pattern is that they start with one problem statement and end the session with additional problem statements and new opportunities they had not considered. Clients who send a single department to "explore AI" without bringing the other stakeholders rarely make it past the pilot stage.Looking three to five years out, Mamta expects advanced AI and predictive analytics to fundamentally reshape how customer experience operates, powered by stronger data foundations and more mature tech stacks. She predicts continued growth in AI-led back-office solutions, deeper fraud protection capabilities, and a rising focus on elevating talent rather than replacing it. The human factor, she says, will always remain because both the customers and the agents serving them are still people. Her single piece of advice to fintech executives and founders: "Be comfortable with the uncomfortable." The firms that try, pivot, learn, and avoid the belief that they already know everything will be the ones that pull ahead.Key HighlightsFraud Signals Your Phone RevealsEvery mobile transaction generates thousands of hidden data points including gyroscope movement, touch pressure patterns, key press timing, and screen angle behavior that machine learning models use to verify identity. IP address matching combined with geolocation checks can confirm whether the person making a payment is physically located where their device says they are, adding layers of fraud protection most consumers never realize exist.Automation Is Not Replacing AgentsTP proposes automation first in every client engagement, yet the goal is augmenting agent performance through AI-powered training, quality assurance, and workforce management tools. Mundane tasks like balance inquiries have already moved to apps, while new roles in data analysis, predictive modeling, financial crime investigation, and fraud prevention are growing faster than the positions being phased out.Consumer Behavior Now Drives FintechBanking and payments typically lead BFSI adoption cycles because consumers transact with payment products daily, while insurance interactions are infrequent and purpose-driven. That ...
Más
Menos
42 m
1 h y 8 m
41 m
59 m
49 m
58 m
35 m
26 m