Just like in baseball, where stats reign supreme, mortgage lending relies on metrics and statistics to measure performance. Lenders track their equivalent of batting averages and runs batted in (RBIs), whether it’s pull-through rates, costs-per-loan, time-to-process, defects-per-loan, servicing inquiries per employee, or any other mortgage lending units of measurement.
But winning in the mortgage game goes beyond measuring and tracking performance data. Just as baseball managers scrutinize player stats to build a championship team, lenders and servicers need deep insights from their data to navigate an increasingly complex financial playing field. In today’s challenging market, data analysis is the ultimate fastball to lower costs and boost efficiency.
Why Numbers Matter
Despite the promises of various technologies, origination costs continue upward. Whether it’s supporting new loan programs and regulatory needs, or making do with manual processes during spikes in demand, lenders manage operations in an environment of constantly changing industry pressures. By leveraging comprehensive analytics, however, lenders can identify operational bottlenecks and uncover ways to streamline loan processing, underwriting, closing and post-closing workflows—and bolster their competitive edge.
Servicers rely on statistics at the loan and portfolio level, too. With every basis point counted, servicers require meticulous portfolio management and efficient loss mitigation strategies to keep costs down. Whether it’s loan onboarding, MSR transfers, investor and insurer audits, or borrower and other customer engagement, having the correct data for the process (and confidently knowing it’s correct) are key to managing processes efficiently. By being able to compare data from different systems with data from source documents and datasets, servicers can reduce costs to locate or confirm “the right answer” and improve the quality of their loan files and portfolios.
Where Issues Arise
In essence, as both origination and servicing costs escalate, the value of insightful reporting and performance metrics also rises. By harnessing data-driven insights, mortgage organizations can mitigate operational risks and cultivate resilience to market fluctuations.
But here’s the catch: these data-driven insights are hard to come by. For one thing, many mortgage organizations still rely on manual processes for handling loan documents and data. This approach is costly and increases the likelihood of errors and inefficiencies that increase risk or hamper overall productivity.
This situation is compounded by the prevalence of document technology providers that don’t deliver the promised results shown in their demos. As a result, many lenders and servicers invest in them, but don’t receive their expected ROI. Stuck with inefficient workflows and lower than expected automation results, they feel trapped in a cycle of increasing manual costs. Lacking reliable metrics to identify operational logjams and accurately measure their operational efficiency compounds the situation, even when everyone agrees “our processes are not working as well as they need to be.”
However, there is a way to turn this situation around.
AI to the Rescue
Paradatec’s AI-based automation technology is the ultimate designated hitter for lenders and servicers. We have the stats to prove it—and so do our clients.
By leveraging advanced machine learning models and a vast pre-trained library of over 850 mortgage-specific document types, our AI-Cloud solution ensures unparalleled accuracy and efficiency in document processing. With the latest in advanced AI models—pre-trained on hundreds of thousands of examples—AI-Cloud enables remarkable automation for document classification, versioning, data extraction and data evaluation.
Our monitoring and reporting tools empower lenders and servicers to measure Paradatec’s document processing accuracy, automation rates and other critical success metrics, so they can evaluate operational improvements and cost savings with pinpoint precision. For example, one of our large independent mortgage lender clients uses our technology to slash the average amount of time spent reviewing and correcting loan documents from 40 minutes to 5 minutes.
We make the same reports we use to measure the AI-Cloud platform available to customers, so we can both assess its performance in real time. But our metrics don’t stop at Paradatec’s system performance.
Along with detailed reporting that includes end user engagement and usage, customers use our SLA Dashboard to manage their own service levels with real-time information. With the ability to manage priorities both within each of their Paradatec processing queues or across all of their Paradatec queues, customers can quickly adjust to operational demands and support special projects like data mining all while optimizing results.
And that’s not all. Our Analytics Module for the AI-Cloud platform improves overall data accuracy even further through automated data evaluation. It automatically compares extracted data from multiple source documents to data stored in various systems and flags unusual data or missing documents, allowing lenders and servicers to further improve the quality of their loan files while enhancing their issue detection capabilities. It’s like having your own video replay system to catch any potential baserunning errors.
If you’re looking to start filling up your stat sheet and ignite your growth and efficiency strategies with Paradatec’s robust system reporting and statistics, drop us a note at info@paradatec.com.
