Automatic Underwriting In Home Equity

Automatic Underwriting in Home Equity: Preparing for Opportunities in the Gray Area Jim Leath BenchMark Consulting International Over the past 20 years, institutions have undergone massive structural, regulatory, social and technological changes that have changed the very nature of the underwriting function. Recent data indicate that industry leaders, particularly in the home equity sector, are relying more heavily on automated systems for their underwriting and decisioning functions. At the same time, the environment in which lenders operate is becoming more competitive and may be forcing them outside the traditional A-paper space into riskier credit grades. Lenders are approaching a fork in the road that will force them to choose to rely more heavily on human underwriters or on technology to underwrite their lending business in the future. The question may have serious implications when institutions lose internal underwriting expertise.

At the same time, technology was making it easier for credit repositories to track and supply consumer credit information. Decisioning engines were developed that could take this credit information, primarily the Fair, Isaac and Company FICO score, along with the institution’s established lending guidelines and determine automatically whether a loan or line should be accepted, denied or investigated further.

A Brief History of Underwriting

Automated Decisioning on the Rise

Prior to the 1990s, the bank underwriter was the individual upon whose authority the institution would enter into a lending agreement with a borrower. The recommendation of the underwriter was of utmost importance. Each branch employed professional underwriters that examined the specifics of each borrower and property in order to make a lending decision every time a customer entered the bank.

The trend toward greater levels of automated decisioning in the institution is well documented and expected to continue. In BenchMark’s home equity lending program the numbers clearly indicate that auto decisioning is on the rise, especially among the industry’s leaders.

But by the 90s, lending was big business and larger organizations realized that it was dangerous to have a different interpretation of the institution’s credit policy being used in each branch. With many banks operating hundreds of branches, this was a critical concern. Centralized credit was the answer. By sending every deal to a single department, staffed by a much smaller group of highly trained underwriters well versed in the company’s policy, banks were able to ensure that the same rules were applied to every deal. In addition, more deals could be completed with fewer people because underwriting personnel were no longer shared by other departments, but were rather dedicated to that single operation.

Today, automated underwriting engines are used industrywide on nearly every type of lending product. Additional automation, primarily built into the origination and processing system, makes it possible for processors to complete most applications and shepherd them to the closing table without an underwriter ever getting involved.

BenchMark also performs the annual CBA Home Equity Lending Survey, which further validates this trend (see Figure 1). While the institutions studied change from year to year, we have found that more home equity lenders are relying more heavily on these automated systems each year. Institutions that use auto decisioning 2004 – 48% (n=10) 2003 – 44% (n=14) 2002 – 43% (n=15) 2001 – 34% (n=12) Source: CBA Home Equity Lending Survey Figure 1

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There is also a positive financial reason that some lenders, particularly home equity and subprime lenders, would rather find a way to profit from a riskier deal through risk-based pricing than to deny the application outright. Consequently, the lenders will utilize their technology to place the loan or line in a gray area and create an exception for review by an underwriter.

But the fact that a lender uses an automated underwriting system does not necessarily mean that the company is making underwriting decisions in an automated fashion. There is a clear distinction between auto decisioning and auto recommend. Many lenders assume that since they have an engine that helps them make decisions that they have auto decisioning in their shop. What most actually have is a system that automatically returns a recommendation. While the system may recommend that a lender approve a deal, a human underwriter still concurs with the deal before it is approved.

Every institution has a different appetite for risk. Likewise, each underwriting department is made up of professionals with different backgrounds and experience. Since there is no legal standard for how these technologies are employed, each institution is free to use them as they see fit. Today, many lenders are using their automated technology to make recommendations. But that is changing.

Automated underwriting systems evaluate all criteria relating to an application and then return one of three recommendations: approve, decline or underwriter review (gray area) that is sometimes referred to as caution. Auto decisioning systems automatically approve and or deny applications based on the findings of these systems and either move them on to the processing department or send out a rejection letter. The exceptions left in the gray area are sent to underwriters. All applications that pass through an auto recommend system end up on the underwriter’s desk.

How Lenders Use Technology Today While the data generally indicate that the use of technological systems for auto decisioning is on the rise in institutions, that conclusion does not hold generally for all lenders. In our own studies of the home equity sector, we received a vast range of responses to our questions about automated underwriting. Most of the firms we studied auto decisioned very few of their equity applications.

Lenders are attracted to automatic decisioning because it offers them significant competitive advantages. By allowing technology to underwrite the majority of the applications received, lenders can do more with the same number of full time employees, lowering their fixed expenses. In addition, turnaround times are reduced, allowing the company to move deals to the closing table more quickly than competitors while still mitigating risk.

Lender Code approved auto-decisioned auto-approved auto-declined booked

1 65.6% 52.1% 52.1% 0.0% 53.0%

2 68.7% 1.4% 0.0% 1.4% 55.0%

The data below (see Figure 2) were taken from our most recent home equity lending program and provide an indication of how lenders are employing their technology in regards to home equity products. Five of the anonymous clients represented in the accompanying table are current home equity sector leaders. While these companies relied far more heavily on technology – with two clients handling about half of their applications in an automated fashion – not all leaders were operating at this level.

3 4 5 72.9% 76.1% 70.6% 22.6% 11.5% 13.0% 14.5% 8.0% 0.0% 8.0% 3.5% 13.0% 51.4% 65.5% 53.0%

6 60.9% 46.2% 35.3% 10.9% 49.9%

7 70.8% 0.0% 0.0% 0.0% 66.7%

8 68.3% 0.0% 0.0% 0.0% 41.4%

9 10 77.5% 79.1% 6.1% 0.0% 4.3% 0.0% 1.9% 0.0% 66.9% 68.6%

11 70.0% 5.3% 0.0% 5.3% 51.7%

12 70.8% 15.8% 0.0% 15.8% 53.5%

Source: 2005 Home Equity BenchMark Program Figure 2

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Automatic Underwriting – April 2005

This is perhaps the best evidence for the conclusion that lenders will continue to move in the direction of more auto decisioning in the future. As they do so, they are less likely to depend upon professional underwriters.

If we look at all of the data BenchMark has gathered in this area since 2001, we find that lenders operating in the 80th percentile are auto decisioning roughly a quarter of their home equity volume (See Figure 3). But the median is still only 3.4 percent.

It is conceivable that some institutions will find themselves without an underwriting staff in the future, relying completely on automation to determine whether a particular deal falls within the acceptable guidelines and then counting on processors to collect the documents that verify the facts on the application.

As we would expect, given the current legislative and regulatory climate, home equity lenders are far more likely to auto approve an application than auto decline one. Lenders in the 80th percentile are more than twice as likely to auto approve than decline. Lenders that rely less heavily on these technologies will auto approve even smaller percentages, with those in the 75th percentile approving roughly three times as many.

Implications for the Future Since the largest home equity firms appear to be embracing auto decisioning most rapidly, it seems clear that these technologies are part of a strategy that is effective in the short term. But will it always be so?

Interestingly, those lenders operating around the median did tend to use auto decline more often than auto approve. However, the low incidence of use (less than half of one percent) indicates that these applications may have been outlying deals that were so far away from an acceptable borrower that the technology could easily cull them.

We think there are a number of reasons lenders should be thinking about this now. First of all, auto decisioning involves the auto approved and auto declined applications, but those applications that fall in the gray area between these extremes must still be underwritten. Technology is improving, to be sure, but it is unlikely that it will squeeze this gap to zero in the near term.

These data also indicate that equity lenders that use automated decisioning tend to approve more loans and lines, as a percentage of total applications, and book a higher percentage of those applications they approve. Those lenders in the 80th percentile will approve, on average, 77.6 percent of the equity applications they see and eventually book 65.8 percent, losing only 11.8 percent (77.6% - 65.8%) of the deals. Those in the 75th percentile will approve slightly fewer applications, but lose more, 12.7 percent (76.3% - 63.6%). Finally, the lenders operating around the median will approve only 72.9 percent of the applications and book only 53.4 percent. These lenders are losing one in five deals (72.9% - 53.4%).

However, higher levels of competition, particularly in the A-credit home equity business, will force lenders to seek out business in other credit grades. As FICO scores drop, it is realistic to expect more loans and lines to fall out of the auto decisioning range and into the gray area where manual underwriting is required. This means that institutions, if they wish to get this business, will have to find some way to underwrite it. Lenders will have basically two options, they can outsource it or they can hire, train and maintain a staff of in-house underwriters that can handle this work for them.

Lenders that utilize a higher level of automation will move their deals to the closing table faster than those that don’t rely as heavily on these systems. In the home equity business, where access to the cash locked up in the borrower’s home is the primary reason for the transaction, speed is of the essence. Therefore, auto decisioning constitutes a significant competitive advantage and our data bear that out, with the larger lenders utilizing more technology and closing a higher percentage of the deals they approve.

% Equity applications auto-decisioned % Equity applications auto-approved % Equity applications auto-declined % Equity applications approved % Equity applications booked

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Contract underwriters could potentially handle this business more cheaply and perhaps faster than originators could themselves, making it attractive to send that business outside of the institution. Increased competition, especially in the home equity sector, could push originators in the direction of outsourcing.

Includes '05, '03 and '01 Data High Low 80th % 75th % Median 52.5% 0.0% 22.6% 16.2% 3.4% 52.1% 0.0% 16.3% 15.2% 0.0% 15.8% 0.0% 8.0% 5.3% 0.4% 87.8% 54.4% 77.6% 76.3% 72.9% 79.4% 45.4% 65.8% 63.6% 53.4% 2001, 2003, and 2005 Home Equity BenchMark Programs Figure 3

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In the end, we believe lenders will eventually settle on one of these two options.

If lenders embrace increased technology with outsourced underwriting as the solution of choice for the future, will it lead to fewer qualified underwriters in the marketplace? If it does, underwriters could command higher fees for their services. Likewise, the costs associated with outsourced underwriting could rise. Under this scenario, the institutions that maintained and trained a core workforce of professional underwriters could be at a competitive advantage.

Those lenders that see auto decisioning handling fewer of their applications as they move away from the easy Acredit loans and lines and into riskier territory, but that are averse to sending the underwriting function outside the company, will want to re-evaluate their plan for hiring, training and maintaining professional underwriters.

In the meantime, and perhaps for all time if outsourced underwriting becomes commoditized and prices remain low, institutions that choose to shoulder the additional costs of FTE in the underwriting department could find themselves suffering from an unnecessary drain on resources.

Those lenders that see technology handling an increasing percentage of their overall application load and that believe contract underwriting will become more commoditized over time will begin to exhibit behavior similar to that seen among the larger home equity lenders today. We can expect those firms to invest more heavily in technology, to forge strong relationships with outsourcers and to pay more attention to the processors who will inherit some of the risk mitigation work that was previously performed by the underwriters.

These questions are not simply dependent upon economic elements in the future, such as the cost of personnel or outsourcing services. They are also dependent on the decisions these lenders make about their business, their appetite for risk and the level of their investment in technology. In fact, these questions cannot be answered until these additional factors are taken into consideration. Furthermore, the correct answers for one institution will differ from the correct answers for another.

Either strategy could be utilized effectively in the days ahead, allowing lenders to profit by originating more of the loans and lines that fall into this gray area. Not settling on one could pose a significant threat to institutions as these trends play out in the future.

Jim Leath is the Mortgage and Consumer Lending practice manager at BenchMark Consulting International. He has extensive background in mortgage and consumer lending, strategic planning, consolidations and corporate restructuring. BenchMark Consulting International has specialized in improving the financial services industry since 1988. The company is a management consulting firm that improves the profitability of its financial services clients through the delivery of management decision making information and change management services to realize the benefits of business process changes. BenchMark Consulting International’s expertise is in the measuring, designing and managing of operational processes. The firm has worked with 36 of the top 50 (in asset size) commercial banks, all 14 automobile captive finance corporations, several of the largest consumer finance corporations and many regional banks throughout the United States. Internationally, BenchMark Consulting International has worked with the five largest Canadian commercial banks, more than 40 European organizations in 11 different countries, in addition to financial institutions in Latin America, Asia and Australia. The company is a wholly owned subsidiary of Fidelity Information Services, Inc., with clients in more than 50 countries and territories, providing application software, information processing management, outsourcing services and professional IT consulting to the financial services and mortgage industries. BenchMark has dual headquarters in Atlanta, GA and Munich, Germany. For more information please go to www.benchmarkinternational.com

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