Quick Overview
Banks analyze transaction and behavioral data using AI to recommend relevant financial products such as travel credit cards, premium accounts, and loan upgrades. Personalized offers build trust, increase product uptake, and enhance cross-product engagement.
Various banks globally
Company Size
Large financial institutions
Revenue Range
Multi-billion dollar revenues
Primary Challenge
Increasing cross-product sales and customer trust through personalized recommendations
Key Metrics
\- Higher product uptake\- Increased customer trust\- More cross-product engagement
The Problem
Traditional product recommendations were generic and lacked personalization, reducing effectiveness
The Solution
AI models analyze customer data to personalize financial product offers and optimize timing and channel delivery
Results
\- Increased sales and customer satisfaction\- Enhanced customer loyalty\- Improved product portfolio utilization
Details
Industry
Finance & Banking
Departments
Sales & Lead Generation
Account Management & Client Success
Use Cases
Upsell & Cross-sell
Tags
Predictive Modeling
Recommendation Engine
Enhanced Decision-Making
AI Tools Used
No items found.
Sources
https://www.creatio.com/glossary/ai-for-cross-selling-and-upselling
More Case Studies
See All
How Bank of America Uses AI and the Metaverse in “The Academy” to Revolutionize Employee Training and Customer Service Skills
Finance & Banking
How H&H Purchasing Automated Invoice Processing with zenphi’s AI Document Processing
Manufacturing
How Tapestry Transformed Enterprise Knowledge Management Using Generative AI on AWS
Retail & E-commerce
How Stitch Fix Uses AI to Deliver Hyper-Personalized Fashion Recommendations and Optimize Inventory
Retail & E-commerce
How NielsenIQ Combines AI and Retail Data to Deliver Real-Time Shopper Behavior Insights and Boost Sales
Retail & E-commerce
How Bizzabo Uses AI to Personalize Hybrid Event Experiences and Optimize Resources
Hospitality & Tourism