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

The client requires an advanced personal finance management system that automates the categorization and labeling of customer transactions, improving user experience in online banking. Current manual processes are inefficient, leading to inaccurate classifications and limited insights into customer spending habits, thereby hindering personalized financial services and analysis.

A mid-to-large-sized banking institution seeking to enhance customer online banking experience through advanced transaction categorization and analytics.

• Achieve at least 95% accuracy in automated transaction classification.
• Enable users to track and analyze their spending patterns through intuitive graphical representations.
• Provide actionable insights based on customer spending habits to support targeted marketing and personalized financial advice.
• Improve overall online banking user engagement and satisfaction.
• Establish a scalable solution capable of handling increasing transaction volumes with high reliability.

• AI-based classification engine to assign transactions to categories such as food, entertainment, loans, and mortgages with high accuracy.
• A user-friendly online dashboard displaying graphical representations of spending patterns and financial summaries.
• Ability for users to review, edit, and refine transaction categories as needed.
• Real-time data processing to ensure up-to-date transaction analytics.
• Secure user authentication and data privacy measures to protect sensitive financial data.

• Banking transaction data feeds via APIs.
• Secure authentication systems (OAuth, SAML).
• Data visualization tools or libraries for graphical analytics.

• Transaction classification accuracy of at least 95%.
• System response time under 2 seconds for user interactions.
• High system availability with 99.9% uptime.
• Data security compliant with banking industry standards (e.g., encryption, access controls).

The implementation of the AI-driven personal finance management system aims to significantly improve transaction classification accuracy, achieving over 95%, and enhance customer engagement through detailed, graphical data insights. This will help the client better understand customer spending behaviors, support targeted marketing efforts, and elevate their overall digital banking competitiveness.