Marketing
Predictive Marketing
Train highly efficient promotional recommendation algorithms to improve customer recommendations and optimize purchase behavior.
Challenge
- The bank lacked adequate user behavioral data to predict credit card promotions to users geographically using their service around the world.
- Privacy concerns and sovereignty regulations inhibited the centralization of PII.
- Decreased accuracy in financial projections due to a lack of purchase history and user activity data.
Solution
- Devron deployed algorithms at the user level to preserve the privacy of underlying user data.
- Devron trained highly efficient promotional recommendation algorithm to recommend restaurants, events, and credit cards to optimize user purchase behavior.
- Decentralized model training resulted in a 30% increase in customer onboarding and retention from increased service adoption and better product recommendations.
Outcomes
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Increased Customer Acquisition
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More Efficient Promotions
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More Data for Analysis
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Reduced Time to Insight
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View Additional Use Cases
Marketing
Expanding Banking Loan Base
Banks desire to expand their customer loan base to drive revenue, manage risk, expand services per customer, and maintain competitiveness. As a result, banks are turning to AI to better segment their customers for new and cross-selling opportunities and to improve their overall customer acquisition process.
