Financial ServicesSolution
Loan Conversion Optimization
Lift loan booking rates with better targeting and a personalized contact strategy across the funnel (conversion, not approval speed).
Solution
Machine Learning
Industry
Financial Services
Company Size
Solution Overview
industry
Financial Services
solution
Machine Learning
technologies
Azure Machine Learning, Microsoft Fabric, Dynamics 365 Customer Insights, Power Automate, Power BI, Azure OpenAI
The Challenge
Banks generate large volumes of pre-approved and pre-qualified offers that never convert, because targeting is based on eligibility rather than intent and outreach happens on the campaign calendar rather than at the moment the customer is receptive.
- 1Pre-approved offers targeted on eligibility rather than intent, so most never convert
- 2Outreach timed to the campaign calendar, not to customer receptiveness
- 3Application abandonment mid-journey with no systematic recovery
Our Approach
CloudGate models conversion likelihood across the full funnel (offer response, application start, completion and drawdown), and recommends the contact strategy, channel and timing most likely to convert each customer.
- Conversion-likelihood scoring at each funnel stage from offer to drawdown
- Optimal contact timing and channel recommendation per customer
- Automated recovery journeys for abandoned applications
Typical Outcomes
+15-30%
LOAN BOOKING RATE
Optimized
CONTACT CHANNEL AND TIMING
Lower
ACQUISITION COST PER BOOKED LOAN
Typical outcomes for this solution pattern, not the results of a named client engagement.
Technologies Used
Azure Machine LearningMicrosoft FabricDynamics 365 Customer InsightsPower AutomatePower BIAzure OpenAI


