AI Cross-Selling for NovaBank S.P.A
A project leveraging artificial intelligence to enhance cross-selling strategies, maximize customer lifetime value, and position NovaBank as a leader in personalized financial services.
Artificial IntelligenceProject Objective
Develop a predictive model to identify cross-selling opportunities, providing personalized recommendations based on customer behavior and financial consumption trends.
Project Phases
These are the steps we followed to achieve our objective.
Initial Data Analysis
Evaluated historical data to assess quality and relevance, identifying key variables like purchased products, usage frequency, demographics, and interactions.
AI Model Design
Proposed a Random Forest-based model for effective classification, with SHAP tools for transparent recommendations.
Data Flow Preparation
Designed an automated ETL process for real-time, accurate data handling.
Validation and Simulation
Used accuracy, recall, and F1-score metrics for validation and Monte Carlo simulations for scenario testing.
Model Benefits
Increased Sales
Identifies additional products or services for customers, enhancing cross-selling opportunities.
Resource Optimization
Focuses efforts on high-conversion customers, improving marketing efficiency.
Enhanced Customer Experience
Delivers personalized recommendations aligned with customer preferences, fostering loyalty.
Data-Driven Insights
Offers strategic insights to sales and marketing teams, backed by advanced data analysis.
Current Status
The project is currently on hold due to insufficient data quality and quantity at NovaBank. Once adequate data becomes available, the project will resume to build a scalable, transparent solution.
Conclusion
The AI Cross-Selling project for NovaBank represents a transformative opportunity to optimize sales processes and personalize financial services. With the groundwork laid, the company is poised to leverage AI for unparalleled customer engagement once data readiness is achieved.