Data Validation Use Cases for Mortgage Lenders & Servicers
Mortgage companies are on a constant mission to reduce cost-per-loan. This crucial metric affects everything from customer service and loan volume all the way to regulatory reporting and strategic decision-making.
One method that every bank or lender can use to shrink their cost-per-loan is by improving data quality. Quality Assurance and Quality Control teams spend hours of manual work reviewing documents and spreadsheets to ensure their data is correct. That often requires dozens of full-time employees whose expertise is wasted on rote stare-and-compare tasks.
Lately, these enterprises are turning to automation software to validate data quality faster, with fewer resources. Still, automation is only one piece of the puzzle.
BaseCap combines automation with unique data transformation and document recognition capabilities, helping customers take complete control of their data quality while greatly reducing manual touch points.
Here are a few of the ways that mortgage companies can use BaseCap to reduce cost per loan through total data validation.
Whether the market is slow or fast, Mortgage lenders and servicers use data validation to reduce their overhead. Explore more mortgage use cases here.
Scenario #1: Automate Your GNMA Purchase Advice Process
In loan purchases, mortgage firms sell loans to the Government National Mortgage Association (GNMA, or Ginne Mae) in bundles called “pools.”
After the sales process, Ginne Mae sends two individual PDF files to the mortgage firm, the 11705 and 11706. The 11705 contains the pool data, and the 11706 has summarized and detailed loan-level data from the settlement.
From these two PDFs, approximately a dozen GNMA-generated details are hand-typed onto a spreadsheet for batch upload or typed directly into the servicing system. This process is entirely manual, sitting on desks throughout the industry.
Physically typing up the data on a pool can take anywhere from four to 15 minutes. That may seem pretty fast, but medium-sized firms have an average of four hundred pools to create each month. That’s 100 hours spent by a full-time employee just to transfer data into their system of record.
Aside from the sheer amount of time, this process presents scalability issues. Mortgage companies often throw bodies at the problem when their loan purchases increase, only to let go of employees in slow periods. Loss of institutional knowledge, low morale, and poor financial planning are only some of the costs the company suffers.
Moreover, manual data entry will always lead to human error. When data entered into the servicing system doesn’t match the original data from the GNMA PDFs, QC teams must be tapped to correct and clean the files.
Corrections add complexity in both time and bearing due to the impact of incorrect reporting and the direct time required to open each document to compare a dozen fields and retype them into the system of record.
BaseCap’s Solution
Leveraging an automated data validation solution like BaseCap helps drastically reduce the hours spent on GNMA data entry and correction, thus lowering the cost to service each loan.
Servicers leverage our Doc2Data solution, featuring Advanced Character Recognition (ACR), to process PDFs for data quality analysis. This unique feature reads GNMA 11705 and 11706 documents and creates the Purchase Advice (PA) output automatically. Whether you have twenty pools a month or thousands, Doc2Data removes all the manual work by generating the details in less than one minute and with 100% accuracy.
The ability to process and validate loan documents like payment letters and handwritten forms is critical for risk and compliance management. Read more about the new technologies enabling document validation.
Scenario #2: Identify FHA Over-Allowables Instantly With Non-Performing Loan Review
Many firms throughout the mortgage industry are required to onboard seasoned loans. These loans often come with a rich and complicated history, including challenges the borrower had with remaining current and the prior servicer(s) actions taken on behalf of the borrower (which may or may not have been accurate).
Bringing these loans in-house requires the new shop to evaluate each loan. For this task, the firm is required to determine if aspects of the loan or the servicing of the loan conflicted with any industry guidelines. These guidelines include federal, state, and regulatory rules, like those produced by the Federal Housing Authority (FHA).
Each set of guidelines governing loan servicing contains strict rules for determining whether actions were correct and whether the new firm can collect old fees from the prior servicer. Reviewing the entire portfolio helps determine which loans are currently delinquent and which actions were taken for each of those loans.
A non-performing loan review is used to evaluate timelines and advances. For instance, it allows a new servicer to identify areas of risk and request reimbursement from the prior servicer. However, seasoned loans come with a level of risk as the new servicer needs to properly identify outages within a limited window, or they lose the ability to request reimbursement for over-allowables. The entire process necessitates an expense-by-expense and transaction-by-transaction review for hundreds and even thousands of loans.
The time required is staggering and often exceeds the window for pursuing reimbursement. Ultimately, companies write off millions of dollars every year simply because they cannot review the loans quickly enough.
BaseCap’s Solution
Servicers use BaseCap to run unlimited data checks like non-performing loan reviews or FHA over-allowable reviews, in minutes compared to days. The firm can identify exceptions or risks in its portfolio and leverage the prior servicer’s data to reduce unnecessary financial losses from unidentified over-allowables. After the data check, BaseCap provides the firm’s teams with exceptions to be reviewed to determine if a reimbursement request is required. What’s more, all of these steps take place on the same day that the data becomes available.
By providing this information so rapidly, BaseCap Analytics maximizes your transparency on the acquired loan portfolio to allow proactive risk management within the 90-day timeframe. Servicers can reduce losses, increase scalability, and keep their business in stride with market shifts and investment opportunities.
Automating compliance management and risk identification allows servicers greater freedom to allocate their employees resources to value-adding functions. Learn more about compliance management in the BaseCap platform here.
Scenario #3: Servicing Transfers Made Easy
Transferring loans between companies is painful for everyone involved. The borrower has no say in the process and yet is the most significantly impacted.
Each servicer has to engage in significant mapping exercises to ensure the column names match and the right data goes into the right fields. Often, they simply cross their fingers, hoping that the underlying data is correct enough to make the result functional.
At its core, a servicer transfer is a data transfer from one servicer’s platform to another; moving this information is incredibly manual and complex. Issues commonly arise from the fact that the data has not been fully validated before moving systems, which causes it to have inaccuracies before, during, and after the transfer. Customers, in particular, bear the weight of these issues as payments get lost or duplicated, escrow gets incorrectly calculated, and customer service loses the ability to help. These data inaccuracies can cause significant regulatory, customer, and business impacts.
BaseCap’s Solution
Like most mortgage data quality processes, BaseCap makes servicing transfers faster, easier, and more accurate. Firms can now ensure data will be accurate before moving onto the receiving servicer’s system.
One of the greatest features that services enjoy in BaseCap is automapping; the platform can intelligently identify the correct columns and rows to map, saving the bulk of the tedious work involved in servicing transfers. Automapping also accelerates future servicing transfers by allowing firms to reuse existing mappings, compare previous ones, and apply them against new servicing transfer files
All the while, the platform evaluates each and every field (not just a sample) to identify exceptions and risks by leveraging hundreds of policies supporting Fannie Mae guidelines and industry standards.
By eliminating manual and complex data transformation processes, BaseCap has introduced a streamlined and automatic tool that cuts down the timeline from months to days/weeks to complete.
Sending large volumes of data introduces myriad opportunities for corruption, bottlenecks, and unexpected costs. Read more about how BaseCap approaches servicing transfers.
What’s your cost-saving scenario?
No matter how your company approaches data quality, data observability, and data governance, BaseCap can be a critical component of your modernization strategy. Reach out to an account executive to learn more about our platform, and how we can help you reduce your cost-per-loan.
