Casap advances AI in banking with award-winning fraud solutions. Casap's recent award win highlights its commitment to innovation in fraud prevention. CEO Shanthi Shanmugam will reveal key insights into the impactful application of Agentic AI at the upcoming MoneyLIVE event. Key facts. * Casap's AI tech reduced fraud losses, enhancing operational efficiency in banking workflows. * Award win reflects Casap's strong market position in transaction fraud monitoring and decisioning. * Focus on regulatory explainability addresses banks' compliance needs, boosting AI adoption potential. * Expansion into broader fraud prevention increases Casap's addressable market among banks and fintechs. * Participation in industry events enhances credibility, signaling strategic commitment to AI integration. Summary. Casap, an AI-first financial technology company, faced the challenge of enhancing fraud monitoring and dispute operations for banks. By deploying its Agentic AI within a bank's dispute operations, Casap achieved significant improvements in fraud loss reduction and operational efficiency. The company was recognized with the 2026 Datos Insights Impact Award for its innovative approach to transaction fraud monitoring. Background. Casap operates in the financial technology sector, focusing on fraud monitoring and dispute operations for regulated institutions. Before deploying its Agentic AI, the company aimed to address the growing concerns of banks regarding compliance, transparency, and risk control in their operations. Challenge. The primary challenge was to improve fraud monitoring and dispute handling processes within banks, which were often hindered by inefficiencies and a lack of real-time decision-making capabilities. Stream Crime Documentaries Solution. Casap implemented its Agentic AI within a bank's dispute operations, emphasizing regulatory explainability, human oversight, and trust. This deployment was designed to enhance the bank's ability to monitor transactions in real-time and improve the accuracy of fraud detection. Results. The deployment of Agentic AI led to measurable impacts on fraud losses and dispute handling efficiency, although specific metrics were not provided in the source material. The recognition from the 2026 Datos Insights Impact Award further validated the effectiveness of Casap's technology in transaction fraud prevention. Key insights. Companies in regulated industries can benefit from integrating AI solutions that prioritize compliance and transparency. Focusing on operational efficiency and measurable outcomes can enhance credibility and support wider adoption of AI technologies. Customer testimonial. No direct customer testimonial was provided in the source material. Agentic AI Shanthi Shanmugam Organizations Datos FCCF Datos Insights Key concepts. Agentic AI fraud monitoring dispute operations transaction fraud prevention regulatory explainability human oversight risk management Definitions. * Agentic AI - A type of artificial intelligence focused on decision-making in regulated environments, emphasizing human oversight and regulatory compliance. * fraud monitoring - The process of tracking and analyzing transactions to detect and prevent fraudulent activities. * dispute operations - The procedures and processes involved in managing and resolving disputes related to financial transactions. * transaction fraud prevention - Strategies and technologies employed to identify and mitigate fraudulent transactions before they occur. * regulatory explainability - The ability of AI systems to provide clear and understandable explanations for their decisions, ensuring compliance with regulatory standards. Use cases. * | Fraud prevention in banking * | Dispute handling in financial institutions * | Real-time monitoring of transactions * | Integration of AI into financial workflows * | High-stakes decision-making in finance Frequently asked questions. What is Agentic AI? Agentic AI is a specialized form of artificial intelligence designed for decision-making in regulated environments. It emphasizes human oversight and regulatory compliance to ensure trust and transparency. Try Productivity Apps How does Casap contribute to fraud prevention? Casap focuses on fraud monitoring and dispute operations, utilizing its Agentic AI technology to enhance transaction fraud prevention. Their solutions aim to reduce fraud losses and improve operational efficiency. What recognition has Casap received? Casap was awarded the 2026 Datos Insights Impact Award for Best Transaction Fraud Monitoring and Decisioning Innovation. This award highlights their effectiveness in real-time monitoring and detection accuracy. What events is Casap participating in? Casap is participating in the MoneyLIVE event and the Datos FCCF event in Charlotte. These events provide opportunities for the company to engage with industry stakeholders and showcase its AI solutions. What are the core differentiators of Casap's offerings? Casap emphasizes regulatory explainability, human oversight, and trust as core differentiators of its Agentic AI offerings. These factors are crucial for banks operating in highly regulated financial environments.

How Casap is rethinking dispute resolution with agentic AI. * Casap was named AI Company of the Year at the Tearsheet AI Innovation Awards 2026. * CEO Shanthi Shanmugam discusses how the agentic AI-powered dispute platform works, where human judgment remains essential, and the future of agentic AI in dispute management. Javarya Kamran | September 10, 2026 Payment disputes can take up to 90 days to resolve. Casap, an AI-native dispute and fraud platform, sees an opportunity to compress that timeline with agentic AI. Its AI agents work across the dispute lifecycle, handling tasks from claim intake and evidence gathering to fraud detection, chargeback filing, and customer communications. The result is faster resolution, with institutions using the platform cutting resolution times from months to days while maintaining compliance and an auditable record of every decision. At Chartway Federal Credit Union, average resolution times fell from up to 3 months to 12 days, while per-claim costs dropped nearly 90%, write-offs declined 72%, and chargeback win rates improved by 95%. As a result of implementing Casap, the credit union generated $875,000 in first-year savings. For this work, Casap was named AI Company of the Year at Tearsheet's AI Innovation Awards 2026. Tearsheet spoke with Shanthi Shanmugam, CEO of Casap, to explore how the agentic AI-powered dispute platform works, where human judgment remains essential, and where agentic AI is headed in dispute management. Q: How does an AI-native foundation change what Casap can do versus incumbents retrofitting AI onto legacy systems? Shanthi Shanmugam, Casap: Tearsheet built Casap with agentic AI from the ground up, including the first publicly available dispute model and API. Casap isn't a workflow tool that routes tasks between people. It works more like an investigator who already has everything in front of them. Dispute data has always been scattered across systems, which is a big part of why this work is so hard on the teams doing it. Tearsheet bring it into one place. That's what makes it possible to see patterns of first-party fraud that legacy infrastructure with an AI layer bolted on simply can't see, and to score that risk before a provisional credit goes out the door. Being AI-native also means compliance logic is foundational rather than layered on top. Reg E, Reg Z, NACHA, and card network rules are all embedded in the workflow. That's why automation and auditability grow together for Tearsheet, rather than pulling against each other. Q: What signals tell Casap's AI agents when they can act on their own and when a case needs human judgment? Shanthi Shanmugam, Casap: Two signals: a predictive win score that gauges the strength of the case and its first-party score. Both come from models built on proprietary, institution-specific dispute data to determine confidence in a given case. When confidence is high, and the dispute is clear-cut and low risk, the platform supports an instant provisional credit decision, which is exactly what someone waiting on their money deserves. When a case is more complex or carries higher risk, human review is recommended by design. If the platform sees a serial bad-faith disputer, it flags that to the investigator on the case, because those calls need real judgment and a person's read on the situation. With its managed service, you can outsource the investigation to Tearsheet. The models are there to guide case handling and decision-making, not to take it over. Q: How do you make an AI agent's reasoning defensible when a financial institution needs to explain a decision months later? Shanthi Shanmugam, Casap: Every dispute lives in a centralized case record that tracks required actions, supporting documentation, and regulatory deadlines from intake through resolution. That gives you a full audit trail for every automated decision. And because predictive win scores guide rather than replace human decision-making on complex cases, there's always a documented rationale tied to the record. Tearsheet also monitor model performance for accuracy and bias on an ongoing basis so that institutions can point to the validation process behind a decision, not just the decision itself. Say an examiner comes back to a claim from nine months ago. The compliance team pulls up the case and reads it start to finish. How the claim came in, what the agent found in the account and transaction history, why it scored and routed the way it did, when provisional credit went out against the Reg E deadline, and what the consumer was told at the end. The platform tracks deadlines, and dispute data can be exported for regulatory reporting into the systems the compliance team already uses. Q: Where do you see the biggest untapped opportunity for AI across the dispute lifecycle today? Shanthi Shanmugam, Casap: Most AI investment has gone toward making the decision faster. Its experience is that the front end matters just as much, and it's the part people tend to overlook: the very first interaction with the customer. Casap's intake is adaptive and conversational, and it does more than collect information. It assesses claim validity in real time and often resolves the situation by pointing the consumer to the merchant before a formal dispute is ever filed. Everyone comes out ahead when that happens. The consumer-facing transparency layer is the other overlooked opportunity. Its customers love the dispute tracker, and it's more than a nice service touch. Poor dispute experience and opaque timelines are the second-leading reason customers leave their financial institution. Keeping someone in the loop is a retention lever, not just a courtesy. Q: How do you see agentic AI reshaping dispute management over the next three years, and where does Casap fit into that evolution? Shanthi Shanmugam, Casap: Dispute management will stop being reactive. Today, it's case-by-case, and it starts at the point of dispute. Over the next few years, Tearsheet expect it to become a proactive risk intelligence function, where fraud scoring happens earlier and runs continuously. AI decisioning is already the baseline expectation in other industries. Its job is to keep proving that regulated, high-stakes financial workflows can be automated end-to-end without sacrificing auditability, and that fraud losses can be a fraction of what they are today. Institutions on Casap are already cutting fraud losses by half. That's what excites me most, because it opens the door for smaller institutions to access capabilities that were once reserved for the largest, best-resourced banks.