Maximizing wallet share is critical for financial institutions. Banks and credit unions often offer a wide range of products from checking and savings accounts to credit cards, loans, and investments but matching the right product with the right customer at the right time is a persistent challenge. Traditional manual reviews are slow, error-prone, and inconsistent. With Decisions, financial institutions can automate data-driven recommendations to detect customer needs, trigger real-time offers, and deliver scalable cross-sell engagement.
Challenge
Prior to automation, the company encountered several obstacles:
- Missed Opportunities: Eligible customers were not consistently offered complementary products.
- Manual Effort: Relationship managers manually reviewed accounts, limiting scalability.
- Inconsistent Recommendations: Criteria varied by branch and employee judgment.
- Customer Frustration: Generic, irrelevant offers reduced trust and engagement.
- Limited Visibility: Leadership lacked insight into campaign performance and conversions.
Solution
The company deployed a Cross-Sell Recommendation Engine in Decisions with the following capabilities:
- Rules-Driven Matching: Automated logic aligned customers with products based on balances, transaction history, demographics, and behavior.
- Real-Time Triggers: Recommendations surfaced in response to specific activity, such as recurring deposits or high account utilization.
- Data Integration: Unified view of the customer through connections to core banking systems and CRM platforms.