Fintech

Recommendation Engine

Project by Sirajuddin Mohammed

The business problem and approach

Developed a recommendation engine for a financial marketplace using market basket analysis (MBA) to identify and suggest the next best service for clients. Leveraged purchase history and behavioral patterns to extract actionable insights, empowering sales and marketing with targeted, data-driven product suggestions. Deployed as a Flask API on AWS for real-time, accessible recommendations.

Implementation highlights

Built a recommendation model using MBA for next-service suggestions, Analyzed client purchase behavior to enable actionable cross-sell and up-sell, Enabled real-time recommendations for sales and marketing with AWS deployment

Delivery and outcomes

20% Conversion rates

Technologies used

Python
Market Basket Analysis
Flask
AWS
API
SQL

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