Michael Sachdev, CEO of Snapdocs, recently shared his insights on the transformative potential of AI in the mortgage industry, focusing on practical applications over theoretical discussions. Sachdev emphasized that while AI technology is fascinating, its real value lies in its ability to address specific operational challenges. Here’s a closer look at how Sachdev sees AI reshaping the mortgage landscape.
The current mortgage market presents significant challenges, with both the purchase and refinance markets experiencing historic lows. According to Sachdev, only 4.3% of owner-occupied homes are currently selling, a stark contrast to the nearly 12% in 2005. This slowdown is attributed to a combination of factors, including high prices, a long period of rate reductions, and the recent rate lock effect, leading to a broader affordability crisis.
Despite these challenges, there is optimism for the future. A report from JP Morgan Private Bank suggests that housing affordability could return to more traditional levels within three years, driven by adjustments in home prices, mortgage rates, and average compensation. Additionally, expected rate reductions from the Federal Reserve could potentially ease the market further, although the impact may be modest.
With lenders facing financial losses—averaging $600 per loan according to MBA data—Sachdev argues that AI's potential lies in streamlining back-office operations rather than cutting frontline sales costs. He points out that the industry’s headcount is not yet right-sized, leading to inefficiencies. The real opportunity for cost savings, he suggests, is in the operational aspects of mortgage processing.
Sachdev identifies several areas where AI can significantly reduce costs and improve efficiency:
Workflow and Task Automation: Many lenders already use task-based tools, but there is still room for improvement. Automating routine processes can free up resources and reduce errors.
Document Classification and Indexing: AI can efficiently handle the classification, annotation, and e-foldering of documents, tasks traditionally done manually. This not only speeds up the process but also reduces the likelihood of human error.
Quality Control (QC): Automated QC processes can ensure documents are accurate and complete before they reach the secondary market, enhancing compliance and reducing risk.
Complex Calculations and Data Extraction: For example, AI can assist in the accurate balancing of Closing Disclosures (CDs), a time-consuming task that could benefit from automation.
While the benefits of AI are clear, Sachdev cautions that successful implementation requires careful planning. He stresses the importance of setting clear benchmarks for performance and being willing to invest in the necessary internal changes. He also advises against relying solely on existing tech stack vendors, urging lenders to seek best-in-class solutions that genuinely meet their needs.
As the mortgage industry navigates through challenging times, the strategic use of AI offers a path to greater efficiency and profitability. Sachdev’s insights serve as a call to action for lenders to look beyond immediate market conditions and invest in technologies that can deliver long-term benefits. By focusing on the back-office operations, lenders can unlock significant savings and improve their overall business processes.