T-REX helps a warehouse lender reduce risk and increase capital investment.
Recent innovations in consumer finance have spawned new asset classes within the sector that have quickly gained momentum. One of them is buy now pay later (BNPL), which offers quick and easy installment payment plans for consumers at the point of purchase. By some estimates BNPL will grow to $39.4 billion globally by 2030. To fund this growth, BNPL firms are looking to warehouse financing typically leveraged by mortgage lenders to fund origination. Warehouse lenders seeking to capitalize on the opportunities their new borrowers present are also facing new risks that are potentially very costly.
Challenge:
A regional US-based bank approached T-REX for help with solving critical operational and risk mitigation processes for their newly formed warehouse lending division focused on esoteric assets, such as consumer lending, receivables financing, real estate, student loans, and others. They were bogged down with disparate data, error-prone borrower requests and a messy, manual data management process. These challenges slowed down their credit review and approval process, leading to high operating costs and unmanaged risk in their facility.
Solution:
T-REX deployed its Managed Data Services to build the critical quality control process the bank needed in order to reduce risk and scale operations. We standardized the bank’s data and automated the borrower data collection and review process, building a scalable process the bank needed to validate what they were receiving.
To help the bank manage their facility we designed an interactive dashboard delivering total transparency into their portfolio. Among its features are:
- a repository of data with time series
- facility metrics and collateral performance
- errors and discrepancies in borrower-based requests identified in the source data
- portfolio level view of borrower behavior and covenants
- concentration limits, and other risk exposure.
Our data management process and interactive dashboard reduced investment and operational risk, enabling the bank to make better investment decisions and freed up analysts time to focus on revenue-generating tasks.
Outcome:
Since becoming a client of T-REX and implementing the new automated QA process, the bank has been able to able to:
- Save ~$14.3 million related to errors and discrepancies in over- or under-reporting the borrower-base
- Reduce the QA time on new requests to 15-30 minutes
- Increase the number of facilities this new division managed from 5 to 15, representing $465 million in AUM