This document provides a summary of a study on mortgage lending performance benchmarking. It analyzes key metrics like pull-through rate, productivity, and cost to close for credit unions. The study found that pull-through rates average around 45% but can be increased through better follow up. Productivity varies widely from 2 to over 14 loans per employee per month. Lenders using a single, integrated system tend to be more productive. Cost to close also varies significantly from around $830 to over $3,200 depending on productivity and use of technology. Case studies on specific credit unions provide examples of how productivity and costs have changed over time in different environments.

1. Mortgage Lending
Performance
Benchmarking
Briefing Paper

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 13
Have questions? Comments? Dan Green, EVP, Marketing, is happy to
talk with you about this white paper and about benchmarking lending
performance. Contact him at dgreen@primealliancesolutions.com.

3. Executive Summary
The 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 well
we 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 Focus
Study for several years until 2006. The Mortgage Bankers Association (MBA) knows it too. From time out
of mind the MBA has published its quarterly and annual Cost Studies1 for mortgage production as well
as loan servicing. The reason both organizations emphasize these studies is there is simply too much at
stake to guess because financing homes for borrowers is every lender’s most profitable activity.2 While
historically true, lending in the post-Dodd/Frank era puts an exclamation point on it. Dwindling revenue
sources mandate squeezing every last nickel out of every last loan.
Knowing rather than guessing is not about greed. Maximizing revenues by minimizing the cost to
produce mortgage loans builds the bottom-line. At the same time managing expenses provides lenders
the opportunity to fine-tune pricing for buyers and refinancers alike. Is it possible to make more money
and offer borrowers more attractive financing? The answer is yes, but you must have a keen grasp of
performance metrics and be willing to constantly improve upon them.
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.
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 loans
placed in portfolio, due to their size and their duration, generate more interest income than any other consumer loan. Interest income generation
combined with typically low delinquency rates make home loans a profitable endeavor. It is also important to note that loans placed in portfolio are
the most profitable mortgage loans, though sale options can be lucrative, too. Second, mortgage loans sold into the secondary market may generate
a 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 versatile
which has a positive effect on their profitability potential.
1

4. What did we study?
Prime Alliance Solutions was founded on two primary objectives, the first of which was improving
the financing experience for home buyers and refinancers alike. The second of Prime Alliance’s two
objectives is:
Help lenders maximize efficiencies while lowering costs.
Unchanged since 2001 when we released the first cloud-based loan origination system to do more than
simply take an application, we can factually say greater efficiency leads to lower operating expenses
and reduced borrowing costs. Efficiency also leads to greater speed, which improves the borrowing
experience. Mortgage loans are a commodity; differentiation through a better process and better service
yields 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 the
borrowing experience, which directed our study toward what we believe to be three critical, high-level
measures 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 account
alike. Deriving directly comparable metrics meant standardizing both the data and the calculations. While
the first two metrics really are simple because they are the product of simple division, the definition of
what is included in their numerators and denominators is critical when comparison is the goal. The third
metric is much more difficult since there is not one agreed upon formula. This is where the MBA’s work
and the Mortgage Focus Study come in handy: not their calculations per se but the way in which they
present 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 sounds
since publicly available data is abundant. NCUA 5300 data, available for all credit unions annually and
some quarterly, combined with FFEIC data, provided every element save one. There is only one way of
obtaining 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 lending
performance 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. 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 low
cost-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 is
discussed in the What We Can Conclude section.
Here’s what we know about each of the three metrics: 6
• Pull-Through
A fun credit union mortgage lending fact: the long-run average pull-through rate from application
to closing is about 45%. Said another way, credit unions are losing as many as 35% of all mortgage
applications. The other 20% are loan denials, which is another fairly constant trend. Why is this
happening? Why can’t the industry get over the 45% pull-through barrier? Where are the missing
35% going?
There are at least two answers to the pull-through quandary. The first has to do with the housing crisis
and the subsequent recession. Pull-through may have peaked at 50% in 2007. Then came the crash and
an altogether different story unfolds. In the depths of the crisis it was only possible to close 40% of all
applications. Some recovery came with the refinance boom of 2009, when pull-through rose to almost
48%. On the mend? Not so fast. The ratio of closed loans to applications decreased in 2010 and again in
2011, 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 lenders
including credit unions, buyers and refinancers alike are automatically targeted within 48 hours of their
initial application. The race is on. Big banks, when hungry for home loans, turn on their marketing
machines and their call centers. They go to work as soon as a potential home buyer or refinancer makes
an application. Follow-through is relentless because closing every possible loan drives profits ever
higher. 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 anathema
to 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 inexpensively
increase pull-through. As explained in the Summary section, application or lead nurturing is the next
great mortgage lending frontier.
• Productivity
Productivity, measured in closed loans per employee per month, ranges widely from a low of just under
2 to more than 14, with the most highly productive lenders consistently achieving 8 to 10 closed loans
per 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 first
benchmarking model in that year. While the model and the analysis have been continually updated, the subjects of study: pull-through, productivity
and cost-to-close have remained the same.
3

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 the
One System traditional multi-system approach: one web- or enterprise-based system is used
can replace at the point of sale while a different enterprise-based loan processing system is
the traditional used to complete the mortgage cycle. While some level of integration typically
use of multiple exists between these two disparate systems, the combination of different platforms
systems to does not typically yield strong productivity. On the other hand, those lenders using
support all one complete system (see the sidebar and Afterword) for applications and loan
mortgage processing typically achieve higher productivity. Generally speaking the results of our
lending study are as follows:
operations.
What makes Closed loans per employee per month multi-system lenders: 2-6
one system Closed loans per employee per month one system lenders: 5-14
complete and
able to replace Variables other than technology are also at play; otherwise the range of results would
multiple be much narrower. Using the right technology is important, in fact, very important.
systems? 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 help
These eight enforce today’s rapidly changing rules.
functions:
1. Loan
People, process and strategy play equally
Origination important roles and are discussed in the What
2. Loan We Can Conclude section.
Processing
Second, those who remember Mortgage Focus may remember the most productive
3. Service lenders during the period of 2002 through 2006 closed as many as 17 loans per
Ordering 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 may
Pricing 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 role
6. Documents in edging productivity higher. In this environment of complex regulation and intricate
pricing, sophisticated systems are absolutely essential for productivity to increase.
7. Secondary
Marketing • Cost-to-Close
8. 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 are
description 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 the
Afterword, at results of our study are as follows:
the end of the
Paper. 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. What Our Customers Know
Generalizing results is interesting and even helpful for comparative purposes. Knowing more about
specific credit union lenders is far more instructive. In this section the results of one credit union/Credit
Union Service Organization (CUSO), Wright-Patt/myCUmortgage, and a credit union, Mid-Minnesota
Federal Credit Union, provide valuable insights into business models, productivity, cost-to-close and
changes in the lending environment over the last several years.
Wright-Patt Credit Union/myCUmortgage
More is not always better except when more is describing data. In the case of Wright-Patt Credit
Union, Ohio’s largest, and its CUSO myCUmortgage, six years of valuable data was available. It tells an
interesting story of the evolution of a growing business model during some of the best and worst times
for mortgage lenders.
Wright-Patt started myCUmortgage in the early part of the last decade with the idea that all credit
unions, regardless of size or capability, should offer mortgages to their members. The CUSO opened
its doors at about the same time cloud-based mortgage origination and processing was beginning. As
the CUSO began to grow, Wright-Patt’s mortgage business did too. The need for easily distributable
technology that enabled mortgage origination and processing became apparent. By 2006 both the
credit union and the CUSO were fully utilizing Prime Alliance’s complete, cloud-based mortgage
platform.
A picture’s worth a thousand words, so the old saying goes. So it is with Graph I which juxtaposes
Wright-Patt’s mortgage lending growth with the productivity of its mortgage team:
5

8. Growth in closed loans is shown on the right axis and can be tracked by the green line. From
approximately 1,000 closings in 2006 to just under 7,500 in 2011, the trajectory of this credit union and
its 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 approximately
6 closed loans per employee per month to just under 10, proving that rapid growth need not be
detrimental to process and productivity improvement.
Making this performance all the more remarkable is the time period in which it occurred. The largest
spike 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 and
ever-tightening credit standards, though these factors, combined with RESPA-mandated changes to
initial disclosures in January 2010, began to take their toll that same year. Productivity began declining in
2010 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. In
a perfect world volume and cost-to-close should behave the same way. As volume increases, scale
increases 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 lending
growth of over 40% and a less than favorable mortgage climate, proving people, process, strategy and
technology 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 loan
officers 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 the
closing table faster,” said Tim Mislansky, chief lending officer of Wright-Patt Credit Union and president
6

9. of myCUmortgage. Another important element of the credit union’s strategy is helping credit unions of
all sizes prosper as mortgage lenders. By the end of 2011 myCUmortgage was serving more than 150
credit unions, a number that is rapidly growing.
What strategy is to growth, technology is to productivity and cost. “We fully implemented Prime
Alliance in time for the 2006 lending year as an integral component of our growth and efficiency
strategies. The technology has obviously helped on both counts,” said Mislansky. Prior to the bursting
housing 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. Through
myCUmortgage we pass our low-cost structure on to our 150 credit unions customers, a number that
is growing rapidly, thanks to the value we offer. Just as importantly, our extremely competitive position
has helped Wright-Patt gain a 10% share of the local purchase-money market. This just would not be
possible without the Prime Alliance platform,” concluded Mislansky.
Mid-Minnesota Federal Credit Union
Membership in Mid-Minnesota Federal Credit Union is open to anyone who lives, works, or worships in
seven 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 a
top lender in our markets for a number of years,” said Jon Tomlinson, director of mortgage services, a
position he has held for 19 years. Mid-Minnesota fully implemented the Prime Alliance platform in time
for 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 and
continues to do so:
Productivity, read on Graph III’s left axis and depicted by the red line, started at just under 10
closed loans per employee per month in 2006, increasing to more than 14 in 2010. Mid-Minnesota’s
productivity achievement is among the best in the credit union industry. What is more remarkable is
consistent, 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, a
good story as well. Graph III tells two other important tales. First, productivity and cost-to-close are
highly correlative and should always move inversely to one another. Second, achieving superior cost
7

10. and productivity performance such as this takes patience and perseverance. Getting to the inflection
point, the period in time where the two lines cross, does not happen overnight, nor does it happen in
six months. The reason for this is technology’s co-conspirators: strategy, people and process must be
made 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, Represented
by the Cost-to-Close, Remains High.
Significant savings, pricing and revenue opportunities exist
any time cost-to-close exceeds $1,500. What could be
gained by reducing the cost of loan production by $850?
There are least two ways to look at this question. First is from
the perspective of how mortgage loans are priced. What do
we charge the borrower? How do we make that determination?
Table I approaches this question from the fairly standard pricing
equation 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
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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.
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12. A lender closing 50 loans per month saving $300 per loan reduces expenses by $15,000, thereby
increasing revenue by the same amount. Annual savings/revenue enhancement in this scenario
is $180,000.
2. Technology Matters.
One-system lenders, those whose on-line mortgage application and loan origination systems are one in
the same, are more efficient and enjoy a lower cost-to-close than lenders who rely on multiple systems
to originate and close mortgage loans.
Moreover, having one, cloud-resident system appears to produce the highest efficiencies due to the
fact 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, originating
and processing mortgage loans becomes an anytime, anywhere proposition. Lenders using enterprise
systems, in contrast, typically process loans during normal business hours since their platforms are not
easily 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 light
of its ability to increase productivity and lower the cost-to-close. Said another way, judging the cost of
mortgage lending technologies without assessing their impact on productivity and cost-to-close is too
narrow a view of the overall cost equation. A complete knowledge of existing performance metrics and
how they are calculated with the goal of improving results is the context in which to judge an investment
in mortgage technologies.
Another means of judging the cost of technology is the Technology Multiple: how much lower in cost do
operations become once the investment in technology is made? Divide total annual savings, as derived
from Table II, by the investment in lending technology. A multiple of 1.5 to 4 means the new lending
technology has paid for itself that many times over. This is also a means of objectifying the decision to
change technologies. ROI is one important measure. The technology multiple is another. Using both
together 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 process
engineering and re-engineering, training and coaching mortgage teams on new technologies and
processes, and employing focused strategy. People, process, strategy and technology are integral to
maximizing productivity while lowering costs.
People, Process, Strategy and Technology (PPST) working
in concert result in the greatest efficiencies and the lowest
cost-to-close.
10

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 period
of 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. Moving
the pull-through needle above 50% means paying more attention to every borrower who makes an
application. Fortunately, automation can help. Technology is every bit the answer here that it is in the
mortgage process itself. Increasing pull-through, which equates to increased market share, decreased
cost, improved productivity and higher profitability, is dependent on solid lead/application-nurturing
technology, processes and strategy. Application nurturing, which combats pipeline poaching, is one of
the next big mortgage lending frontiers and one in which the competition is already intense.
Failing to Close Loans is Expensive. For that Reason
Alone the Pull-Through Dilemma has to be Addressed.
11

14. Summary
Guessing is more fun than knowing, though knowing is more powerful than guessing, especially when
it comes to something as strategically important as mortgage lending. Yet pursuing lower cost-to-close
and 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
www.primealliancesolutions.com and at www.cuhousingroundtable.com.
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 enables
members to apply any time, anywhere and loan officers to take applications regardless of the time of
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15. day, day of week or their location, is simply another included tool that accesses the same database as
the loan origination system, the platform used to process, underwrite, close and fund loans. Adding
secondary 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 of
improved productivity and reduced cost-to-close. For further thoughts on functions ‘one-system’ should
include, see the Afterword.
Interested in knowing more?
Prime Alliance Solutions is happy to help. We take the guesswork out of mortgage lending, and we
provide the only true cloud-based, one-system lending solution available today.
Afterword
One-System v. Multiple Systems.
The very traditional, very long-standing practice in mortgage lending operations is connecting or integrating
multiple systems in order to provide loan officers, processors, underwriters, closers, funders, shippers, secondary
market managers and operations managers the tools they need to move a loan from origination through closing
and into the secondary market and loan servicing systems. The one-system approach, on the other hand, doesn’t
look at these as separate systems. Rather, it considers them the tools required to create a complete, preferably
cloud-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 approach
includes the eight, though most integrations require maintenance as well as extra time managing data and data
integrity. The other difficulty with integration tends to be the data transparency that’s easily accomplished with
the one-system approach. When one-system includes all functions, sharing data with everyone who has a need to
see it, including the borrower, is easy.
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16. @ 2012 Prime Alliance Solutions, Inc. A Mortgage Cadence, LLC Company. All Rights Reserved.