Building Investor Risk Transparency Into Loan Originations

Building Investor Risk Transparency Into Loan Originations REQUIRED READING: What is the key to accurate secondary market pricing? For many people, the answer is the combination of risk transparency and data accuracy.

Investors that have enough data to accurately determine risk can set more accurate prices and avoid potentially costly mistakes. But there's a problem: Today's loan origination platforms insert more uncertainty into the system than necessary. Why is risk considered acceptable while uncertainty is not?

In the book ‘More Than You Know,’ Michael Mauboussin summarizes the differences between risk and uncertainty: ‘Risk has an unknown outcome, but we know what the underlying outcome distribution looks like. Uncertainty also implies an unknown outcome, but we don't know what the underlying distribution looks like. So games of chance like roulette or blackjack are risky, while the outcome of a war is uncertain.’

Uncertainty in the loan pipeline forces investors to be more cautious and turn down more deals. Or worse, investors may purchase a deal that is not going to be profitable based on faulty information or information received too late in the process.

The challenge for today's secondary marketers and investors is that the loan origination process is not built with the end purchaser in mind. Because the system evolved during a time when paper documents were necessary, the first generations of technology solutions grew up to mirror that workflow.

The impact of document-driven processes is costly. In the loan workflow, you have different silos – origination, secondary marketing, servicing – all working on a loan file in sequence while only seeing their small portion of the bigger picture.

It starts with origination: taking the application, pulling credit and running pre-qualification through an automated underwriting engine. Next, the loan enters processing, where the staff evaluates the application and automated underwriting findings, orders third-party fulfillment products, assembles the loan file and enters all of this data into the loan origination system (LOS). This can take anywhere from 10 to 70 days, depending on staffing, case loads and vendor performance.

Then, the underwriter reviews the loan file and evaluates borrower and collateral risk. This process can take up to 10 days or more.

In the next step, the loan file moves to the closer, who once again evaluates the loan file, orders closing docs and requests funding. Once closed, the file moves into post-closing, where another set of staff members evaluate the loan file, perform the quality-control check and prepare it for shipping.

Then, the investor can take a look at the finished file. At best, the investor can first begin to evaluate a loan after it has reached underwriting, but in some cases, data is not available until after closing.

Since originators rely on the investor's funds, they also want to ensure a loan meets the pricing guidelines. Without a clear data-centric process, valuable time is spent ensuring salability, which reduces the overall volume that can be handled.

Driving data

The beauty of machine-interpretable data, such as XML, is its readability by any modern technology system. Data-focused processing provides clearer transparency and more accurate risk analysis.

Once an application is entered into the lender's operation system, all data should be instantaneously available at every step of the loan process. Lenders and investors should be able to automatically scan for adherence to their guidelines and evaluate risk and pricing.

This provides them the ability and flexibility to evaluate risk, set pricing and arrange mortgage-backed securities packages while the loan is working its way to closing. When a data-centric loan platform is combined with comprehensive process orchestration, a lender can cut 30% or more off the time and cost needed to complete a loan.

The key is to use automated decisioning in order to streamline or eliminate the manual evaluations and quality checking at each step of the mortgage's journey to closing. Mortgage technology can also evaluate the loan data within the context of the investor's business rules to render a decision or suggested action. Business rules can be applied to automatically flag suspect loans or award premium pricing to stronger loans.

Once a decision is made, the investor can automatically take one or more of several actions: clear the check or condition, create a new task, request or obtain more data (e.g., additional property valuation or income verification) or notify someone of the decision.

Investors and secondary marketers do not need their closing partners to make the change all at once. The first step is moving from a document-centric loan file to a hybrid data and document electronic loan file format. MISMO has helped pave the way with digital mortgage field standards.

Next, lenders need to select a technology platform that can leverage the XML data to streamline mortgage processes and increase transparency. In the short term, utilizing a hybrid, data-driven electronic loan file enables lenders to leverage existing technology assets while still getting the benefits of a data-driven approach. Eventually, mortgage bankers will need to implement data-centric systems across the board.

The days of document-driven technology are coming to a close. Embrace the freedom data provides, and start looking at mortgage technology needs with clear eyes. The result will be more intelligent risk decisions and less uncertainty as investors and secondary marketers pave the way for the mortgage industry's recovery.

Rob Pommier is vice president at Irvine, Calif.-based Genpact Mortgage Services. He can be reached at


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