The client’s Default Management Function was broken into four separate business units: Pre-Foreclosure, Foreclosure, Bankruptcy, and Loss Mitigation. Within the Pre-Foreclosure business unit lies an important activity called ‘Breach’ that involves the servicer aggregating all loan data that warrants a Mortgage Breach Letter and compiling that data into a State-specific format that accommodates for requirements by individual U.S. States. Due to the vast number of loans being serviced, the servicing provider had broken this ‘Breach’ activity into three separate processes: Automated, Hybrid, and Manual. By doing this, the client was able to better accommodate for volume increases in cases of mortgage portfolio acquisition. However, even with this added functionality, the client was still facing resource constraints causing Service Level Agreements (SLAs) not to be met and employees having to work overtime to accommodate for volume.
- Understanding the Input: By ‘modularizing’ our initial input and validating the efficacy, we were able to provide immediate lift to the business and reduce development time for downstream modules
- Determining Scope: Gathering all process-specific volume data provided a clear understanding of where the majority of effort was being spent, identifying that 89% of volume came from 6 States
- Data Point Consolidation: We created a map of all the data points required for each State and utilized back-end integration to circumvent, having to use the User Interface for a majority of items
- Phased Solution Integration: Strategically developing modules that would be used by each State’s variation and implementing them in a phased approach compounded benefits as integration increased
Accelirate’s automation framework encompassed a Waterfall Matrix approach for analysis with an agile methodology for development, providing all the benefits of the Waterfall in the ‘requirements gathering’ phase while having it still be adaptable to change during development. By utilizing the data map created in analysis, we were able to strategically develop modules that would be used by each State’s variation and implement them in a phased approach where benefits would be compounded as their integration to production increased. Our approach allowed us to both empathize with the business in terms of data integrity and provide the most efficient solution possible given the circumstances.