Fintrix: An Agentic AI Powered Customer Service Solution for the Banking Sector

Abstract

The fast pace of adoption for AI is creating a new landscape in financial services where intel ligent automation, improved decision-making, and powerful defenses against increasingly sophisticated digital attacks are now possible. This thesis introduces Fintrix, anAgentic AI-wielding intelligent banking assistant that consolidates various AI functionalities in a unified, self-contained entity. Fintrix is composed of three main modules: (i) a Customer Support Agent which provides efficient, contextual and personalized counseling using advanced natural language understanding; (ii) a Financial Advisory Agent, based on predic tive analytics, time series modeling and behavior analysis that offerspersonalized financial advice and insights; nd (iii) a Fraud De- tection Agent which employs machine-learning techniques together with anomaly-detection methods to recognize fraudulent activities in real-time. Fintrix is grounded on modular, scalable and explainable (XAI) methods for natural language understanding with the intuition behind Agentic AI, Large Language Models (LLMs), andXAI approaches. These are just a few possible advantages of suchan inter-relation of operations, which provides the systems with self-management to per form ultra complex economic operations on their own responsibility and anyway always give content clear and understandable to the end user. Synchronous running of multiple agents "Fintrix ensures that rendezvous between the state rooms can be accomplished bad decision making and overall accounting overhead onthe bank’s computer. In summary, Fintrix demonstrates the practicalitiesand relevance of a decentralised MAS approach in the modern financial sector. It also demonstrates how Agentic AI drives improved customer service, better riskmanagement and data-driven financial planning