Challenge
In the competitive landscape of financial services, customer acquisition is no longer about reaching the most people—it’s about reaching the right people. Banks were increasingly struggling with inefficient marketing spend and poor conversion rates due to generic targeting. Without behavioral intelligence, traditional credit and loan offers often missed high-potential customers or targeted unqualified leads, increasing financial risk.
Our Solution
IOS introduced a robust, telco-data-enhanced propensity modelling solution to refine how banks target prospective customers. Instead of relying solely on static financial metrics, we layered in behavioral and mobility signals that reflect real-life customer patterns. The model enabled financial institutions to:
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Score Propensity with Precision
Rank customers based on likelihood to adopt loans or credit services, using mobile behavioral traits. -
Integrate Mobility Insights
Understand user routines and commuting patterns, which often correlate with lifestyle and credit demand. -
Predict Spending Behavior
Combine location and digital activity to forecast financial readiness and service affinity. -
Reduce Risk Exposure
Exclude low-propensity or high-risk profiles early in the funnel, reducing approval friction and defaults.
Impact
The implementation led to significantly higher conversion rates and a drop in cost-per-acquisition. Campaigns became leaner and more effective, empowering banks to focus resources on prospects most likely to convert—and stay. This data-driven shift also improved risk management, allowing financial institutions to operate with greater confidence and agility in a fast-changing market.