Mortgage Lending Performance Benchmarking (Whitepaper)


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Our Benchmarking Paper highlights the work Prime Alliance has done over the years with its customers and other lenders. Generally speaking the results and conclusions found here are based on the experience of a segment of the country’s top 500 mortgage lending credit unions. Our intent was to understand pull-through rates, lending productivity and what it costs to close a mortgage. What does it take to maximize the first two while minimizing the third? Read on. We’ll share what we’ve learned from the success of our clients, the most efficient lenders in the industry. For more info:

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Mortgage Lending Performance Benchmarking (Whitepaper)

  1. 1. Mortgage Lending Performance Benchmarking Briefing Paper
  2. 2. Table of Contents Mortgage Lending Performance Benchmarking Briefing Paper Executive Summary 1 What did we study? 2 What do we know? 3 What our customers know 5 What we can conclude 8 Summary 12 Afterword 13Have questions? Comments? Dan Green, EVP, Marketing, is happy totalk with you about this white paper and about benchmarking lendingperformance. Contact him at
  3. 3. Executive SummaryThe poet W.H. Auden, in his poem Archeology said: Guessing is more fun than knowing.Auden wasn’t talking about facts and figures. When it comes to measuring the work we do and how wellwe do it knowing is not only more fun than guessing, it’s essential.We simply have to know rather than guess when it comes to measuring mortgage lending performance.Fannie Mae knew it in the early days of the last decade, preparing and publishing its Mortgage FocusStudy for several years until 2006. The Mortgage Bankers Association (MBA) knows it too. From time outof mind the MBA has published its quarterly and annual Cost Studies1 for mortgage production as wellas loan servicing. The reason both organizations emphasize these studies is there is simply too much atstake to guess because financing homes for borrowers is every lender’s most profitable activity.2 Whilehistorically true, lending in the post-Dodd/Frank era puts an exclamation point on it. Dwindling revenuesources mandate squeezing every last nickel out of every last loan.Knowing rather than guessing is not about greed. Maximizing revenues by minimizing the cost toproduce mortgage loans builds the bottom-line. At the same time managing expenses provides lendersthe opportunity to fine-tune pricing for buyers and refinancers alike. Is it possible to make more moneyand offer borrowers more attractive financing? The answer is yes, but you must have a keen grasp ofperformance metrics and be willing to constantly improve upon them.Our Benchmarking Paper highlights the work Prime Alliance has done over the years with its customersand other lenders. Generally speaking the results and conclusions found here are based on theexperience of a segment of the country’s top 500 mortgage lending credit unions. Our intent was tounderstand pull-through rates, lending productivity and what it costs to close a mortgage. What does ittake to maximize the first two while minimizing the third? Read on. We’ll share what we’ve learned fromthe success of our clients, the most efficient lenders in the industry.1 Now known as the Performance Reports, produced both quarterly and annually.2 Is mortgage lending the most profitable loan in a lender’s arsenal? The answer is yes, and it’s true from multiple perspectives. First, mortgage loansplaced in portfolio, due to their size and their duration, generate more interest income than any other consumer loan. Interest income generationcombined with typically low delinquency rates make home loans a profitable endeavor. It is also important to note that loans placed in portfolio arethe most profitable mortgage loans, though sale options can be lucrative, too. Second, mortgage loans sold into the secondary market may generatea profit on sale, though this is not always the case. Profits here depend on market conditions as well as close attention to pipelines and sale execution.Third, mortgage loans sold with servicing released produce sale proceeds for the servicing rights. The point is mortgage loans are incredibly versatilewhich has a positive effect on their profitability potential. 1
  4. 4. What did we study?Prime Alliance Solutions was founded on two primary objectives, the first of which was improvingthe financing experience for home buyers and refinancers alike. The second of Prime Alliance’s twoobjectives is:Help lenders maximize efficiencies while lowering costs.Unchanged since 2001 when we released the first cloud-based loan origination system to do more thansimply take an application, we can factually say greater efficiency leads to lower operating expensesand reduced borrowing costs. Efficiency also leads to greater speed, which improves the borrowingexperience. Mortgage loans are a commodity; differentiation through a better process and better serviceyields a competitive advantage, which is important for today’s relationship-based lenders.Helping lenders maximize efficiencies while lowering costs is measurable more so than enhancing theborrowing experience, which directed our study toward what we believe to be three critical, high-levelmeasures of lending performance: • Pull-through rate is simply measured by dividing loans closed by loan applications taken. This high- level though important metric measures opportunity as well as lost opportunity. The higher the pull-through the better, generally speaking, though we recognize about 20% of today’s loans fall out due to a variety of factors including borrower credit, tight credit standards, property value or the borrower’s inability to find a property, or other conditions preventing approval. • Productivity is simply measured by the number of loans closed per mortgage team member3 in a given time period divided by the number of mortgage applications taken. Our preferred measure is loans per month, though loans per year also works. This measure is so important because personnel expense is the single biggest cost in every mortgage operation. Consequently striving for the highest number of closed loans per employee per month has a significant bearing on the third important metric, cost-to-close. Conversely, some strategies well worth pursuing may impede maximizing productivity. That does not make them bad nor does it mean they should not be pursued. Managing to metrics versus managing to strategy is a delicate, important balancing act. Trading one for the other often makes perfect sense given market conditions, borrower demographics or other factors. • Cost-to-Close is not simply measured. While the other two metrics lend themselves to quick calculation this one does not. Though not simple to derive, there can be no guesswork here. It is the most important of the three metrics because it has a direct bearing on profitability and competitive pricing/positioning. Once armed with this metric it is easier to make a plethora of decisions, the most important of which may be determining the rates and fees offered to borrowers.The first important decision was choosing what to study. How to conduct the study was the second.Comparing lender productivity and costs is historically difficult because no two organizations cost accountalike. Deriving directly comparable metrics meant standardizing both the data and the calculations. Whilethe first two metrics really are simple because they are the product of simple division, the definition ofwhat is included in their numerators and denominators is critical when comparison is the goal. The thirdmetric is much more difficult since there is not one agreed upon formula. This is where the MBA’s workand the Mortgage Focus Study come in handy: not their calculations per se but the way in which theypresent information provides valuable clues to formulizing an approach.Once the formulas were determined the next hurdle was normalizing the data. This is easier than it soundssince publicly available data is abundant. NCUA 5300 data, available for all credit unions annually andsome quarterly, combined with FFEIC data, provided every element save one. There is only one way ofobtaining the missing variable: by asking how many mortgage lending production4 staff a lender has.Armed with formulas and data, it is entirely possible to know rather than guess about lendingperformance which turns out to be both fun and informative.3 The denominator in this equation - mortgage team members - includes production staff and management. It does not include loan officers.4 See footnote 3. 2
  5. 5. What do we know?While some credit unions5 post remarkably high productivity and correspondingly low costs to close,there is significant room for improvement. It is also very important to note high productivity and lowcost-to-close is not the bastion of big credit union lenders, though several post impressive results.Strong performance is the result of interplay between people, process, technology and strategy, which isdiscussed in the What We Can Conclude section.Here’s what we know about each of the three metrics: 6• Pull-ThroughA fun credit union mortgage lending fact: the long-run average pull-through rate from applicationto closing is about 45%. Said another way, credit unions are losing as many as 35% of all mortgageapplications. The other 20% are loan denials, which is another fairly constant trend. Why is thishappening? Why can’t the industry get over the 45% pull-through barrier? Where are the missing35% going?There are at least two answers to the pull-through quandary. The first has to do with the housing crisisand the subsequent recession. Pull-through may have peaked at 50% in 2007. Then came the crash andan altogether different story unfolds. In the depths of the crisis it was only possible to close 40% of allapplications. Some recovery came with the refinance boom of 2009, when pull-through rose to almost48%. On the mend? Not so fast. The ratio of closed loans to applications decreased in 2010 and again in2011, no doubt as a result of tight credit standards, lack of housing stock and increased regulation.The second answer to the question is pipeline poaching. From the largest lenders to community lendersincluding credit unions, buyers and refinancers alike are automatically targeted within 48 hours of theirinitial application. The race is on. Big banks, when hungry for home loans, turn on their marketingmachines and their call centers. They go to work as soon as a potential home buyer or refinancer makesan application. Follow-through is relentless because closing every possible loan drives profits everhigher. He who is most persistent gets the loan is the positive way of saying he who hesitates is lost.Credit unions should play this game even though poaching and outbound calling may seem anathemato their business model. Thirty-five percent fallout due to inattention is expensive. Outbound marketing,in the form of drip email campaigns and regular check-in phone calls, could easily and inexpensivelyincrease pull-through. As explained in the Summary section, application or lead nurturing is the nextgreat mortgage lending frontier.• ProductivityProductivity, measured in closed loans per employee per month, ranges widely from a low of just under2 to more than 14, with the most highly productive lenders consistently achieving 8 to 10 closed loansper month per employee.5 While this study concerns credit union lending performance, the methodology used here as well as the results are likely not lender-type specific,meaning there is a high probability the same metrics would produce similar results in other deposit-taking mortgage lenders.6 The analysis and the results shown here are the work of Prime Alliance Solutions. We’ve been collecting data since 2009 and built our firstbenchmarking model in that year. While the model and the analysis have been continually updated, the subjects of study: pull-through, productivityand cost-to-close have remained the same. 3
  6. 6. One of the key differences between the most productive and the least is the technology they use. Our study began in 2009 and included lenders that use theOne System traditional multi-system approach: one web- or enterprise-based system is usedcan replace at the point of sale while a different enterprise-based loan processing system isthe traditional used to complete the mortgage cycle. While some level of integration typicallyuse of multiple exists between these two disparate systems, the combination of different platformssystems to does not typically yield strong productivity. On the other hand, those lenders usingsupport all one complete system (see the sidebar and Afterword) for applications and loanmortgage processing typically achieve higher productivity. Generally speaking the results of ourlending study are as follows:operations.What makes Closed loans per employee per month multi-system lenders: 2-6one system Closed loans per employee per month one system lenders: 5-14complete andable to replace Variables other than technology are also at play; otherwise the range of results wouldmultiple be much narrower. Using the right technology is important, in fact, very While mortgage lending is possible without it, doing without is costly and hazardous: costly from the perspective of low productivity as well as lost opportunity and hazardous in that it is all but impossible to be compliant without systems that helpThese eight enforce today’s rapidly changing rules.functions:1. Loan People, process and strategy play equallyOrigination important roles and are discussed in the What2. Loan We Can Conclude section.Processing Second, those who remember Mortgage Focus may remember the most productive3. Service lenders during the period of 2002 through 2006 closed as many as 17 loans perOrdering employee per month. Tighter credit standards, increased regulation and the necessary compliance focus make such an accomplishment all but impossible today.4. Loan Even with perfect interplay between people, process, technology and strategy,Underwriting closing a loan takes more effort today than it did before the housing crisis began in 2007, a fact reinforced in the following section, What Our Customers Know.5. Product and Regardless, 14 loans per employee per month is remarkable. Over time it mayPricing be possible to once again reach or surpass the 17 loans per employee per month achieved in the early years of the last decade. Technology will play a significant role6. Documents in edging productivity higher. In this environment of complex regulation and intricate pricing, sophisticated systems are absolutely essential for productivity to increase.7. SecondaryMarketing • Cost-to-Close8. Imaging Productivity and cost-to-close are highly correlative. The higher the productivity, generally speaking, the lower the cost-to-close. There’s a broad range here, too.For a full The lowest cost producers can close a loan for $830.7 The highest cost lenders aredescription of burdened with a cost per loan of more than $3,200.each function,see the Here, too, the one-system / two-system dynamic is in play. Generally speaking theAfterword, at results of our study are as follows:the end of thePaper. Cost-to-Close two system lenders: $1,500 - $3,200+ Cost-to-Close one system lenders: $830 - $2,400 It takes more than systems to lower costs, which is covered in the next section. 7 Multiple year average. Single-year cost-to-close figures are actually lower. 4
  7. 7. What Our Customers KnowGeneralizing results is interesting and even helpful for comparative purposes. Knowing more aboutspecific credit union lenders is far more instructive. In this section the results of one credit union/CreditUnion Service Organization (CUSO), Wright-Patt/myCUmortgage, and a credit union, Mid-MinnesotaFederal Credit Union, provide valuable insights into business models, productivity, cost-to-close andchanges in the lending environment over the last several years.Wright-Patt Credit Union/myCUmortgageMore is not always better except when more is describing data. In the case of Wright-Patt CreditUnion, Ohio’s largest, and its CUSO myCUmortgage, six years of valuable data was available. It tells aninteresting story of the evolution of a growing business model during some of the best and worst timesfor mortgage lenders.Wright-Patt started myCUmortgage in the early part of the last decade with the idea that all creditunions, regardless of size or capability, should offer mortgages to their members. The CUSO openedits doors at about the same time cloud-based mortgage origination and processing was beginning. Asthe CUSO began to grow, Wright-Patt’s mortgage business did too. The need for easily distributabletechnology that enabled mortgage origination and processing became apparent. By 2006 both thecredit union and the CUSO were fully utilizing Prime Alliance’s complete, cloud-based mortgageplatform.A picture’s worth a thousand words, so the old saying goes. So it is with Graph I which juxtaposesWright-Patt’s mortgage lending growth with the productivity of its mortgage team: 5
  8. 8. Growth in closed loans is shown on the right axis and can be tracked by the green line. Fromapproximately 1,000 closings in 2006 to just under 7,500 in 2011, the trajectory of this credit union andits CUSO through some of the most trying times in mortgage lending is noteworthy. As importantly,productivity, shown on the left axis and illustrated by the red line, has increased from approximately6 closed loans per employee per month to just under 10, proving that rapid growth need not bedetrimental to process and productivity improvement.Making this performance all the more remarkable is the time period in which it occurred. The largestspike in year-over-year growth took place between 2008 and 2009, the deepest period of the recession.The largest gains in productivity took place during the same period amidst increasing regulation andever-tightening credit standards, though these factors, combined with RESPA-mandated changes toinitial disclosures in January 2010, began to take their toll that same year. Productivity began declining in2010 for the first time in four years and has yet to rebound to its 2009 high.Productivity and cost-to-close are highly correlative and should move inversely to one another. Ina perfect world volume and cost-to-close should behave the same way. As volume increases, scaleincreases and the cost-to-close decreases. While Graph II does not contrast productivity versus cost-to-close, it does show the relationship between volume and cost-to-close:Cost-to-close, depicted on the left axis and illustrated by the orange line, was over $1,200 in 2006.By the end of 2011 it had declined to just under $975, a 20% drop amidst average annual lendinggrowth of over 40% and a less than favorable mortgage climate, proving people, process, strategy andtechnology have more influence over performance than external market factors.Strategy is the primary component driving growth. Mortgage lending is a core strategy for Wright-Patt Credit Union which focuses on affordable housing, first-time home buyers, Realtors®, outside loanofficers and, this year, HARP. “Prime Alliance enables us to serve members faster than our competitors.The system helps us get through a loan from start to finish quicker, meaning the member gets to theclosing table faster,” said Tim Mislansky, chief lending officer of Wright-Patt Credit Union and president 6
  9. 9. of myCUmortgage. Another important element of the credit union’s strategy is helping credit unions ofall sizes prosper as mortgage lenders. By the end of 2011 myCUmortgage was serving more than 150credit unions, a number that is rapidly growing.What strategy is to growth, technology is to productivity and cost. “We fully implemented PrimeAlliance in time for the 2006 lending year as an integral component of our growth and efficiencystrategies. The technology has obviously helped on both counts,” said Mislansky. Prior to the burstinghousing bubble Wright-Patt’s costs were on a downward trajectory while productivity progressively rose.“Even though underwriting now takes about two hours longer per loan than it did prior to 2008, Wright-Patt and myCUmortgage’s efficiencies continue growing while our costs continue to decrease. ThroughmyCUmortgage we pass our low-cost structure on to our 150 credit unions customers, a number thatis growing rapidly, thanks to the value we offer. Just as importantly, our extremely competitive positionhas helped Wright-Patt gain a 10% share of the local purchase-money market. This just would not bepossible without the Prime Alliance platform,” concluded Mislansky.Mid-Minnesota Federal Credit UnionMembership in Mid-Minnesota Federal Credit Union is open to anyone who lives, works, or worships inseven of Minnesota’s north central counties. The fifteenth largest credit union in the state with assets of$236 million, its size and model is very different than Wright-Patt Credit Union’s, except for one thing:mortgage lending is a core strategy and has been for more than 20 years. “We are and have been atop lender in our markets for a number of years,” said Jon Tomlinson, director of mortgage services, aposition he has held for 19 years. Mid-Minnesota fully implemented the Prime Alliance platform in timefor the 2006 mortgage lending year, just as Wright-Patt did.As Graph III illustrates, Mid-Minnesota FCU’s bet on the Prime Alliance platform has paid off andcontinues to do so:Productivity, read on Graph III’s left axis and depicted by the red line, started at just under 10closed loans per employee per month in 2006, increasing to more than 14 in 2010. Mid-Minnesota’sproductivity achievement is among the best in the credit union industry. What is more remarkable isconsistent, year-over-year improvement during some of mortgage lending’s toughest times.The cost-to-close trend tells a similar story. Read on the right axis and depicted by the green line,the metric stood at just under $1,000 per loan in 2006, decreasing to under $800 per loan in 2010, agood story as well. Graph III tells two other important tales. First, productivity and cost-to-close arehighly correlative and should always move inversely to one another. Second, achieving superior cost 7
  10. 10. and productivity performance such as this takes patience and perseverance. Getting to the inflectionpoint, the period in time where the two lines cross, does not happen overnight, nor does it happen insix months. The reason for this is technology’s co-conspirators: strategy, people and process must bemade to work in concert, a reckoning that takes place over time.What can we conclude?We draw five conclusions from this iteration of our Benchmarking Study:1. The Cost of Producing a Loan, Representedby the Cost-to-Close, Remains High.Significant savings, pricing and revenue opportunities existany time cost-to-close exceeds $1,500. What could begained by reducing the cost of loan production by $850?There are least two ways to look at this question. First is fromthe perspective of how mortgage loans are priced. What dowe charge the borrower? How do we make that determination?Table I approaches this question from the fairly standard pricingequation all mortgage lenders learn early in their careers: Table I Cost-to-Close Savings Estimator Mortgage Rates Offered to Borrowers Column Column Column One Two Three Loan Amount $ 175,000 $ 175,000 $ 175,000 Cost-to-Close $ 1,500 $ 850 $ 850 Pass-Through Rate 3.625% Secondary Market Price 101.7116 101.7116 101.8931 Add: Sales Premiums 1.7116 1.7116 1.8931 Warehouse Spread 0.0800 0.0800 0.0800 Servicing Value 0.2000 0.2000 0.2000 Points 0.0000 0.0000 0.0000 Fees 0.0000 0.0000 0.0000 Sub Total 1.9916 1.9916 2.1731 Subtract: Cost-to-Orginate 0.8571 0.4857 0.4857 Hedge Cost 0.0000 0.0000 0.0000 Sub Total 0.8571 0.4857 0.4857 Total: 102.8461 103.2175 103.5805 Potential Price Improvement, in basis points 0.0.3714 0.7344 Price-to-Ratio 4 4 Rate Improvement Potential, in basis points 9.29 18.36 8
  11. 11. Starting with the market price of a loan at a rate thought to be attractive to borrowers, sales premiums, warehouse spreads, servicing value, rates and fees are added to the price while the cost to originate and hedge costs are subtracted. The result is the amount of profit the loan will produce. Column One shows the cost-to-originate as $1,500 and assumes the loan is priced for 60 day delivery. Other than the sales premium of 171 basis points, and over which lenders have no control, the cost- to-originate is the single largest variable in the pricing equation as well as the single largest expense. It is also the most significant variable over which lenders have control and, therefore, drastically affects profitability. The result is a net gain of 285 basis points.8 Column Two holds all else equal save for cutting the cost-to-close in half to $850 which reduces origination expenses by 37 basis points. Given the standard secondary market price-to-rate ratio of four to one, such savings, rendered in basis points, means a potential for an almost 10 basis point decrease in borrower rate. Column Three introduces a third possibility. The hypothesis goes something like this: an efficient, highly productive lender moves loans through the mortgage cycle faster closing loans more quickly. Therefore loans are available for sale sooner which means rather than a 60 day delivery price the lender could, instead, take advantage of the more favorable 45 day delivery price. The 60 day price in this example is 101.7116; the 45 day price is 101.8931, for an improvement of 18 basis points. The result in this scenario yields the potential for an 18 basis point improvement in the rate presented to the borrower. Improving borrower rates and, therefore, competitive positioning is certainly one way to view the benefits of improving the cost-to-close. Another angle is pure profitability. Returning to Table I, look again at the line labeled Total and the one immediately underneath, Potential Price Improvement. The potential improvement is 37 basis points or, simply, the difference in basis points between a $1,500 cost- to-close and an $850 cost. That’s 37 basis points to the bottom-line, pure profitability. The message is clear: competitive pricing is largely a function of efficient operations. Efficient operations yield profitable lending operations. Table II helps put this in perspective, juxtaposing cost savings per loan with the number of loans closed per month: Table II Cost-to-Close Savings Estimator Mortgage Rates Offered to Borrowers 50 Loans Closed per Month 75 100 150 200 300 350 Reduction in Cost-to-Close $ 150 $7,500 $11,250 $15,000 $22,500 $30,000 $45,000 $52,500 $ 200 $10,000 $15,000 $20,000 $30,000 $40,000 $60,000 $70,000 $ 250 $12,500 $18,750 $25,000 $37,500 $50,000 $75,000 $87,500 $ 300 $15,000 $22,500 $30,000 $45,0004 60,000 $90,000 $105,000 $ 350 $17,500 $26,250 $35,000 $52,500 $70,000 $105,000 $122,500 $ 400 $20,000 $30,000 $40,000 $60,500 $80,000 $120,000 $140,000 $ 500 $25,000 $37,500 $50,000 $75,000 $100,000 $150,000 $175,500 $1,000 $50,000 $75,000 $100,000 $150,000 $200,000 $45,000 $350,000 $1,200 $60,000 $90,000 $120,000 $180,000 $240,000 $360,000 $420,000 $1,500 $75,000 $112,500 $150,000 $225,000 $300,000 $450,000 $525,000 8 102.8461 expressed represents a gain of 284.61 basis points. 9
  12. 12. A lender closing 50 loans per month saving $300 per loan reduces expenses by $15,000, therebyincreasing revenue by the same amount. Annual savings/revenue enhancement in this scenariois $180,000.2. Technology Matters.One-system lenders, those whose on-line mortgage application and loan origination systems are one inthe same, are more efficient and enjoy a lower cost-to-close than lenders who rely on multiple systemsto originate and close mortgage loans.Moreover, having one, cloud-resident system appears to produce the highest efficiencies due to thefact lending teams are able to access their pipelines from any internet-connected computer. Members,too, can make application from wherever they are at their convenience. With these systems, originatingand processing mortgage loans becomes an anytime, anywhere proposition. Lenders using enterprisesystems, in contrast, typically process loans during normal business hours since their platforms are noteasily web-accessible.3. The Cost of Technology Does Not Matter.The cost of technology in the singular context is irrelevant. Technology expense is only important in lightof its ability to increase productivity and lower the cost-to-close. Said another way, judging the cost ofmortgage lending technologies without assessing their impact on productivity and cost-to-close is toonarrow a view of the overall cost equation. A complete knowledge of existing performance metrics andhow they are calculated with the goal of improving results is the context in which to judge an investmentin mortgage technologies.Another means of judging the cost of technology is the Technology Multiple: how much lower in cost dooperations become once the investment in technology is made? Divide total annual savings, as derivedfrom Table II, by the investment in lending technology. A multiple of 1.5 to 4 means the new lendingtechnology has paid for itself that many times over. This is also a means of objectifying the decision tochange technologies. ROI is one important measure. The technology multiple is another. Using bothtogether yields the best financial and operational decision.4. People, Process and Strategy Matter, Too.No more than buying a horse makes one a cowboy does buying technology make one an efficient,low-cost mortgage lender. The best technology must be coupled with extreme attention to processengineering and re-engineering, training and coaching mortgage teams on new technologies andprocesses, and employing focused strategy. People, process, strategy and technology are integral tomaximizing productivity while lowering costs.People, Process, Strategy and Technology (PPST) workingin concert result in the greatest efficiencies and the lowestcost-to-close. 10
  13. 13. 5. Costs Also Remain High Thanks to Stagnant Pull-Through Rates.The pull-through rate for mortgage loans throughout the credit union industry is stagnant at the mid-40% mark. The calculation used here is purposefully overly simple for the sake of easy comparison.Dividing the total number of closed loans by the total number of applications taken over a long periodof time yields the result. What’s the next step?Most lenders do a poor job of following through on applications, especially pre-approval applications.Buyers and refinancers alike are as easily distractible as they are convertible by other lenders. Movingthe pull-through needle above 50% means paying more attention to every borrower who makes anapplication. Fortunately, automation can help. Technology is every bit the answer here that it is in themortgage process itself. Increasing pull-through, which equates to increased market share, decreasedcost, improved productivity and higher profitability, is dependent on solid lead/application-nurturingtechnology, processes and strategy. Application nurturing, which combats pipeline poaching, is one ofthe next big mortgage lending frontiers and one in which the competition is already intense.Failing to Close Loans is Expensive. For that ReasonAlone the Pull-Through Dilemma has to be Addressed. 11
  14. 14. SummaryGuessing is more fun than knowing, though knowing is more powerful than guessing, especially whenit comes to something as strategically important as mortgage lending. Yet pursuing lower cost-to-closeand higher productivity outside the context of an overall mortgage strategy and the people, skills,processes and technologies necessary to implement that strategy is likely to do more harm than good.The journey from guessing to knowing, therefore, should follow these steps: 1. Define mortgage lending strategy. There is no one-size-fits-all strategy for every mortgage lender let alone every credit union. Market, community, member demographics and a host of other factors impact the ultimate strategy definition. Starting here provides an aiming point. It also guides the other decisions that make sure the bullseye is hit. 2. Define the people and skills necessary to implement strategy. Does the defined strategy call for internal loan officers? External loan officers? How are loan officers compensated? How do Realtors® factor into the strategy? What type of support will origination staff require? How will production staff responsibilities be divided? What will be required of underwriters? How many underwriters will be necessary? Will loans be sold direct to the secondary market or through a correspondent? Which loans will be placed in portfolio? What will become of servicing? These are just a few of the questions that help determine the people and skills required to fulfill the defined strategy. Additional helpful reference material is available at and at It is important to note, too, that strategy, once defined, may result in additional compliance obligations. A myriad of laws, regulations and GSE requirements impact the ways in which home loans are originated, processed, underwritten, closed, funded and serviced. Once strategy is defined, the next step is to discuss potential implications with compliance specialists. With identified obligations in hand it is time to ensure technology, process and people are compliant. Here, too, technology can be a significant help. 3. Measure existing operations. This is the guessing to knowing step. Measure pull-through, cost-to-close and closed loans per employee. These are benchmark numbers; the key metrics upon which improvements will be made and measured. 4. Establish new measures. Once strategy is defined, necessary people and skills are determined and existing metrics are known, it’s time to establish goals for improvement. Improvements should be expected to progress over time: 6 months on the short end, to as long as 18 months or more. The speed at which improvement occurs is a function of how rapidly an organization implements strategy, enhances skills and improves process. In other words, improving productivity from 4 closed loans per employee per month to 8 in a month or two is probably unrealistic. 5. Choose a technology. The benchmarking work described in this paper points to one-system technologies producing better results. Such systems enable speed and efficiency because data integrity / data integration is no longer an operational requirement. Staff spend their time closing loans as opposed to managing technology.To be clear, one-system means the mortgage point-of-sale technology, the technology that enablesmembers to apply any time, anywhere and loan officers to take applications regardless of the time of 12
  15. 15. day, day of week or their location, is simply another included tool that accesses the same database asthe loan origination system, the platform used to process, underwrite, close and fund loans. Addingsecondary marketing functionality into the equation further increases efficiency and profitability.Disparate ‘integrated‘ systems do not, as our research shows, produce the same results in terms ofimproved productivity and reduced cost-to-close. For further thoughts on functions ‘one-system’ shouldinclude, see the Afterword.Interested in knowing more?Prime Alliance Solutions is happy to help. We take the guesswork out of mortgage lending, and weprovide the only true cloud-based, one-system lending solution available today.AfterwordOne-System v. Multiple Systems.The very traditional, very long-standing practice in mortgage lending operations is connecting or integratingmultiple systems in order to provide loan officers, processors, underwriters, closers, funders, shippers, secondarymarket managers and operations managers the tools they need to move a loan from origination through closingand into the secondary market and loan servicing systems. The one-system approach, on the other hand, doesn’tlook at these as separate systems. Rather, it considers them the tools required to create a complete, preferablycloud-based system. How many systems does it take to close a mortgage loan? At least eight: Loan Origination. In the early days this was a paper 1003. When technology became common this step in the process migrated to desktops and laptops. The internet took origination to the cloud. Loan Processing. Paper files, typewriters, fax machines, couriers, calculators were all replaced by typically centralized processing systems by the late 1990s. Most of these systems remain enterprise- based, though there is movement toward the cloud and toward paperless systems. Service Ordering. Phone calls, fax machines, email, scanning are all methods of ordering and processing the service orders needed to close a mortgage loan. Either an off-line process or tasks within the loan processing system, even today they seldom happen in real-time and are typically not readily available to the borrower or, for that matter, every member of the mortgage team who may need them. Loan Underwriting. Most loans are underwritten through either Fannie Mae’s DeskTop Underwriter or Freddie Mac’s Loan Prospector. Most, if not all systems today, are designed to send loans to and receive findings from these two systems. Integration depth varies, however, from simple send and receive to sending, receiving, parsing findings and using findings to drive workflow. Product and Pricing. Pricing loans has become increasingly complex, especially as GSE guidelines change and evolve. Consequently systems that manage loan level price adjustments in real-time along with proprietary pricing rules are absolutely essential in assuring borrowers get the right loan rate and pricing every time. Documents. Like underwriting systems, documents are typically provided by a third party, either as an integration or off-line. The best integrations make disclosures and closing documents available on-line in minutes. Secondary Marketing. It is uncommon to find secondary marketing tools integrated with most loan processing systems. These capabilities are typically expensive third-party add-ins that rely on one or two-way integrations or data downloads that then manage the function off-line, resulting in less than best execution and profitability. Imaging. Imaging systems for document and workflow management have been around the mortgage industry for many years, though until recently have they been tightly integrated with loan processing systems. Good imaging systems enable paperless lending, the most efficient, most cost- effective means of producing a mortgage.The one-system approach includes all eight functions and more in one package. The multi-system approachincludes the eight, though most integrations require maintenance as well as extra time managing data and dataintegrity. The other difficulty with integration tends to be the data transparency that’s easily accomplished withthe one-system approach. When one-system includes all functions, sharing data with everyone who has a need tosee it, including the borrower, is easy. 13
  16. 16. @ 2012 Prime Alliance Solutions, Inc. A Mortgage Cadence, LLC Company. All Rights Reserved.