Key facts
- The mortgage brokerage model's value is challenged by operational complexity and fragmented systems.
- Handoffs between specialized roles in mortgage origination lead to lost information, errors, and delays.
- Growth in brokerages often increases complexity due to more handoffs and coordination needs.
- A proposed solution involves organizing work around the loan itself, rather than traditional roles.
- AI has the potential to manage coordination and context, allowing skilled individuals to take on broader responsibilities.
- The author will explore a new operating model in a future piece.
The traditional operating model for mortgage brokerages, while offering valuable choice in lenders, products, and pricing, is facing significant limitations due to inherent complexity and a lack of evolved operational structures. The author argues that the industry's reliance on a series of handoffs between specialized roles—from loan officer to processor to underwriter—introduces inefficiencies, increases costs, and creates unpredictability in closing timelines. Each transfer of information between individuals or systems represents a potential point of failure where context can be lost, leading to errors, miscommunications, and the need for additional oversight.
As brokerages grow, this problem is compounded. The common solution of adding more staff, such as loan officer assistants and operational support, paradoxically increases the number of handoffs and management overhead, consuming some of the added capacity. The author suggests that the industry's focus on defined roles, rather than the loan itself, has limited the effective application of technology. Instead of applying tools to make existing tasks faster, a more effective approach would be to organize work around the loan's lifecycle, identifying which tasks require human judgment and which can be coordinated or executed by technology, particularly AI.