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 Reveals Every 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 Agents TP 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 Fintech Banking and payments typically lead BFSI adoption cycles because consumers transact with payment products daily, while insurance interactions are infrequent and purpose-driven. That frequency gap means consumer expectations hit banking and fintech firms first, forcing faster response times and creating pressure that insurance companies eventually absorb as a fast follower. Living On Cash Taught Product Thinking One of the sharpest product leadership lessons came from spending an entire month using only cash, no cards, no checks, no electronic payments, to understand what consumers actually experience when they lack access to modern payment tools. That hands-on immersion shaped a framework for understanding customer pain points from the inside out, a method still applied today when onboarding new clients by finding internal employees who already use the client's products. The Real Meaning Of Data The phrase "so what of the data" reframes the entire conversation around why raw data collection means nothing without a clear connection to personalization, spend analysis, and predictive outcomes. Combining multiple data sources with analytics can reveal buying power, transaction patterns, location behavior, and propensity to pay, turning passive information into active intelligence that drives customer engagement and retention. Storytelling Aligns Stakeholders Faster Complex enterprise sales involving operations, product, and executive teams require more than technical specs to move forward, and framing solutions around a clear North Star with a human impact story accelerates buy-in. Using a collections call as an example, the narrative centers on saving a customer relationship rather than recovering a balance, which reframes cost of acquisition against breakage and makes the ROI case emotionally and financially persuasive. Banks Now Seek Outside Perspective A year ago, most banking clients told TP they would solve AI and CX challenges internally within their own teams and systems. In the last twelve months, that posture has shifted sharply toward requesting peer group insights, consortium-style knowledge sharing across 350+ global BFSI clients, and collaborative problem solving that treats the current wave of change as an industry-wide learning curve. Culture Shapes Customer Experience Strategy Three years of living and working in India reinforced that cultural context directly affects how customers respond to service interactions, communication styles, and engagement approaches across different regions. Global CX strategies that ignore cultural layers risk delivering a technically sound but emotionally flat experience, which is why regional adaptation matters as much as the tech stack powering the interaction. Hidden Fraud Detection Through Biometrics Beyond standard two-factor and three-factor authentication, financial services firms are now layering behavioral biometrics that track how a person physically handles their device during a transaction. Screen touch patterns, movement signatures, and Face ID verification create a composite identity profile that runs silently behind every interaction, catching anomalies that traditional password-based security would miss entirely. Meeting People Where They Are Cross-functional leadership across global teams starts with something as simple as asking a new direct report which communication channel they prefer, whether that is Viber, WhatsApp, text, or another platform. That small signal of respect sets the tone for a people-first management approach where multiple perspectives are actively solicited, because the operating principle is that one brain is never as effective as seven or eight working together. Five Key Takeaways1️⃣ Bring Cross-Functional Teams To Every Pilot Sending one department to evaluate AI or data analytics tools is how pilots die quietly after 90 days. Get your operations lead, product owner, IT or data leader, and digital officer in the same room with one shared problem statement before you commit budget. That combination forces the real blockers to surface early, things like legacy system constraints, rule adjustments, and use case selection, so you can design around them instead of discovering them after you have already spent the money. 2️⃣ Use Your Own Products Before Selling The fastest way to understand a customer's pain is to become one. Before pitching a solution or onboarding a new client, find people inside your own organization who already use that client's product and pull them into the conversation. You will learn more about friction points, feature gaps, and real user behavior in one week of hands-on product use than in six months of reading market research decks. 3️⃣ Arm...
