Development of an AI-Driven Personal Finance Management System for Banking Digitization

Traditional online banking platforms often lack user-centric functionalities, making navigation, transaction categorization, and spending tracking cumbersome for customers. The client aims to overhaul its digital banking interface by automating transaction labeling, data management, and integrating a personal finance management (PFM) module to improve usability and data-driven customer insights.

A mid-sized retail bank seeking to modernize its online banking platform with intelligent financial management tools to enhance customer experience and gain insights into customer spending patterns.

• Achieve high accuracy in transaction categorization, targeting at least 95% correct labeling of customer transactions.
• Support processing of at least 150 transactions per second per core to ensure system scalability and responsiveness.
• Integrate a comprehensive PFM system that facilitates custom reports, budgeting tools, and notifications based on customer spending behavior.
• Improve overall customer satisfaction and engagement through userfriendly and intelligent financial management features, setting a new standard in digital banking.

• Advanced AI algorithms for real-time transaction classification and labeling with 95% accuracy.
• High-throughput data processing capable of handling 150 transactions per second per core.
• User interface components for generating custom financial reports and visualizations.
• Budgeting modules that allow users to set and track financial goals.
• Notification system to alert users of spending patterns, anomalies, or budget breaches.
• Secure data handling in compliance with financial data privacy standards.

• Core banking systems for transaction data retrieval.
• Data analytics platforms for generating insights and reports.
• Notification and alert systems for customer engagement.
• Security and authentication systems ensuring data integrity and privacy.

• System scalability to support increasing transaction volume without performance degradation.
• High system throughput, supporting at least 150 transactions per second per core.
• Reliability with minimal downtime and robust error handling.
• Security compliance with financial data protection standards.
• User interface responsiveness optimized for multiple devices.

Successful implementation of the AI-driven PFM system is expected to significantly enhance customer engagement and satisfaction by providing highly accurate transaction categorization and customized financial insights. The system aims to boost data quality for user experience, achieving at least 95% accuracy in transaction labeling, and handle over 150 transactions per second per core, positioning the bank as a market leader in digital financial services and enriching customer data analytics for strategic decision-making.