Massachusetts Mutual Life Insurance Company v. DB Structured Products, Inc. et al

Filing 528

Judge Mark G. Mastroianni: MEMORANDUM AND ORDER entered. For the reasons, the Court ALLOWS Defts' Motion to Exclude the expert testimony of Dr. Kilpatrick insofar as it seeks to preclude him from testifying as to the original appraisers' state of mind but otherwise DENIES the motion - 355 . The Court also DENIES Defts' Motion to Exclude the expert testimony of Mr. Butler - 359 . (Finn, Mary)

UNITED STATES DISTRICT COURT
DISTRICT OF MASSACHUSETTS
MASSACHUSETTS MUTUAL LIFE
INSURANCE COMPANY,
Plaintiff,
v.
DB STRUCTURED PRODUCTS, INC., et al.
Defendants.

*
*
*
*
*
*
*
*
*
*
*

Civil Action No. 11-30039-MGM

MEMORANDUM AND ORDER REGARDING
DEFENDANTS’ MOTIONS TO EXCLUDE THE
EXPERT TESTIMONY OF JOHN A. KILPATRICK
AND STEVEN I. BUTLER
(Dkt. Nos. 355 and 359)
May 7, 2015
MASTROIANNI, U.S.D.J.
I.

INTRODUCTION

Massachusetts Mutual Life Insurance Company (“Plaintiff”) brought eleven related actions
against various defendants, asserting violations of Mass. Gen. Laws ch. 110A, § 410, the
Massachusetts Uniform Securities Act (“MUSA”), for misstatements and omissions contained in the
offering documents of certain residential mortgage-backed securities (“RMBS”). The instant action
(11-cv-30039-MGM), brought against Deutsche Bank Securities Inc. (“DBSI”), Anilesh Ahuja,
Michael Commaroto, Richard D’Albert, and Richard Ferguson (together, “Defendants”), was
designated a “bellwether” case by Judge Saris on December 4, 2013. (See Dkt. No. 225.) 1
Accordingly, it is scheduled to proceed through summary judgment and trial while the other cases
are stayed.

1

The second bellwether action, 11-cv-30215-MGM, was settled by the parties and closed by the court on December 24,
2014. (See 11-cv-30125, Dkt. No. 421.)

Presently before the court are Defendants’ motions to exclude the expert testimony of John
A. Kilpatrick and Steven I. Butler, under Federal Rule of Evidence 702 and Daubert v. Merrell Dow
Pharms., Inc., 509 U.S. 579 (1993). For the following reasons, the court will grant in part and deny
in part Defendants’ motion to exclude Dr. Kilpatrick, and deny the motion to exclude Mr. Butler.

II. BACKGROUND
Plaintiff brought these eleven actions in 2011, alleging that material misrepresentations were
made in the sale of RMBS in violation of MUSA. RMBS are securities entitling the holder to
income payments from pools of residential mortgage loans held by a trust. After the various
mortgage loans are aggregated into loan pools and securitized, certificates representing the
securitizations are sold to investors. Accordingly, the characteristics of the loans underlying the
certificates, such as the loan-to-value (“LTV”) and debt-to-income (“DTI”) ratios, as well as the
loan origination and underwriting standards, 2 affect the certificates’ value. In this case, Plaintiff
alleges the offering materials for the certificates contained misrepresentations regarding (1) the
underwriting guidelines and standards used to originate or acquire the mortgage loans underlying the
certificates; (2) the appraisal standards used to value the mortgaged properties; and (3) the LTV
ratios for the underlying loans. 3
On July 21, 2014, Plaintiff served the affirmative expert reports of Dr. Kilpatrick and Mr.
Bulter, among others. Dr. Kilpatrick prepared two expert reports: in one, he assessed the accuracy
of the original appraised values of a sample of properties underlying the certificates (“Sample
2

As explained in Assured Guaranty Municipal Corp. v. Flagstar, FSB, 920 F. Supp. 2d 475 (S.D.N.Y. 2013), “[m]ortgage
underwriting is the process of evaluating against guidelines established by a lender the collateral underlying a loan as well
as a borrower’s income, assets, and credit.” Id. at 480. “Mortgage underwriting guidelines control risk by requiring the
collection of documentation to support a borrower’s ability to repay the loan and setting limitations on various factors
relevant to a borrower’s risk of default.” Id. at 481.
3 Plaintiff had also alleged misrepresentations regarding the owner-occupancy rates for the properties, but these claims
were dismissed by Judge Ponsor. See Massachusetts Mut. Life Ins. Co. v. Residential Funding Co., LLC, 843 F. Supp.
2d 191, 204-205 (D. Mass. 2012).

2

Properties”) 4 using an automated valuation model (“AVM Report”); in the other, he evaluated, for
the subset of properties in the AVM Report which he found were significantly overvalued, whether
the appraisals adhered to applicable appraisal standards using a credibility assessment model (“CAM
Report”). Mr. Butler, for his part, prepared a report in which he analyzed, or “reunderwrote,” the
loans of the Sample Properties to determine whether they were originated or acquired in accordance
with applicable underwriting guidelines in compliance with representations in the offering
documents (“Butler Report”).

A.

Dr. Kilpatrick
Dr. Kilpatrick has over 30 years of experience in finance and financial analysis, real estate,

business development, statistical analysis, consulting, and teaching. (Dkt. No. 503, Decl. of John A.
Kilpatrick (“Kilpatrick Decl.”) ¶ 6; Ex. 1 (“AVM Report”) at 3.) He earned a Bachelor of Science in
business administration (accounting), a Master of Business Administration, and a Ph.D in real estate
finance from the University of South Carolina. (Kilpatrick Decl. ¶ 7; AVM Report at 5; Ex. 3 at 2.)
Dr. Kilpatrick currently teaches real estate finance as a visiting scholar at Baruch College, City
University of New York. (Kilpatrick Decl. ¶ 7; AVM Report at 5.) In addition, he is an MAI
designated member of the Appraisal Institute 5 and is a state-certified (general) real estate appraiser in
all 50 states as well as the District of Columbia. (Kilpatrick Decl. ¶ 8; AVM Report at 5.) In 2004,
the Appraisal Qualifications Board (“AQB”) designated Dr. Kilpatrick as one of approximately 500
nationally certified appraisal standards instructors. (Kilpatrick Decl. ¶ 9; AVM Report at 6.) Dr.
4

The samples were chosen by Dr. Charles Cowan in accordance with his April 12, 2013 expert report, which described
the statistical sampling methodology he used to select 100 sample loans from each of the 99 Supporting Loan Groups
for analysis of the rate of misrepresentation. See Massachusetts Mut. Life Ins. Co. v. Residential Funding Co., LLC, 989
F. Supp. 2d 165, 168-69 (D. Mass. 2013). Plaintiff sought to proceed in this manner rather than by analyzing each of the
278,609 individual loan files. See id. at 169. On December 9, 2013, Judge Saris denied a joint motion filed by the
various defendants in the related actions to exclude the opinions expressed in Dr. Cowan’s report. Id. at 176.
5 MAI is a professional designation for real estate appraisers who are experienced in the valuation and evaluation of
commercial, industrial, residential, and other types of properties, and who advise clients on real estate investment
decisions. (Kilpatrick Decl. ¶ 8, Ex. 1 at 5.)

3

Kilpatrick also was nominated to the AQB and was named a Fellow of the Faculty of Valuation of
the British Royal Institution of Chartered Surveyors. (Id.) He has authored numerous books and
articles on real estate and serves as an editorial board member of two peer-reviewed publications: the
Journal of Sustainable Real Estate and The Appraisal Journal. (Kilpatrick Decl. ¶ 10; AVM Report
at 6.)
With regard to automated valuation models in particular, Dr. Kilpatrick has authored or coauthored several peer-reviewed publications on the subject. (Kilpatrick Decl. ¶ 12.) In addition to
teaching, Dr. Kilpatrick is the Managing Director of Greenfield Advisors LLC, a real estate appraisal
and economic consulting firm headquartered in Seattle, Washington. (AVM Report at 6.) Dr.
Kilpatrick and the Greenfield Advisors staff have written and lectured extensively on the application
of mass appraisal and statistical methods in class action litigation. (Id. at 6-7.) 6 Moreover, Dr.
Kilpatrick has testified as an expert in 41 actions in the past four years for both plaintiffs and
defendants, and he has been qualified as a mass appraisal and real estate valuation expert in a
number of cases. (Kilpatrick Decl. ¶ 13; AVM Report at 7; Ex. 5.)
Dr. Kilpatrick’s AVM Report describes his use of the Greenfield Automated Valuation
Model (“GAVM”), an AVM he previously developed but adapted for this action, to assess the
accuracy of the original appraised values of a sample of properties underlying the certificates. AVMs
are computer programs that use statistical models to reach objective estimates of the market value of
real property. (AVM Report at 27.) GAVM in particular uses a statistical hedonic regression model 7

6 In particular, a 2007 white paper, Certifying the Real Estate Damages Class—An Appraiser’s Perspective, is widely
considered the authoritative writing on the subject. (Id.)
7 As explained in Hartle v. FirstEnergy Generation Corp., 2014 WL 1317702 (W.D. Pa. 2014), “[h]edonic regression is a
type of multiple regression analysis that attempts to determine mathematically the value or price of the various
components or characteristics that add up to the total value or utility.” Id. at *8. “For example, a hedonic model for a
house might include variables such as square footage, number of bathrooms, and quality of neighborhood.” Id. Dr.
Kilpatrick describes hedonic valuation models similarly in his AVM Report: “Appraisers and AVMs following the
hedonic model assign a value to individual components of the property, such as square footage, number of bathrooms,
and lot size, and consolidate those individual values to come up with the value to be attributed to the property as a
whole.” (AVM Report at 29 n.66.) Dr. Kilpatrick’s analysis is also considered a “mass appraisal,” which the Uniform

4

to perform retrospective real estate appraisals. (Kilpatrick Decl. ¶ 15.) Similar to a traditional
appraisal, GAVM uses the sales prices of comparable properties to generate a value for the subject
property. (Id. ¶ 18.) Unlike a traditional appraisal, however, GAVM uses 100 to 2,000 sales
transactions as comparables, rather than only three or six. (Id. ¶ 17; AVM Report at 30.) These
comparable sales transactions are from the same county as the subject property, and the model
limits the sales observation data to the geographically nearest sales transactions in the year preceding
the effective date of the Sample Property’s appraisal. (Kilpatrick Decl. ¶ 19; AVM Report at 32.)
As Dr. Kilpatrick explains in his AVM Report, “[b]ecause it relies on a larger number of
comparisons and uses uniform computing logic, an AVM’s valuation results are inherently more
accurate and objective” than a traditional appraisal, which is prone to subjectivity in selecting
comparable properties and adjusting sales data. (AVM Report at 29-30.)
GAVM consists of two valuation sub-models: an ordinary least squares regression model
(“OLS valuation model”), and an OLS model with a trend surface component (“OLSXY valuation
model”). (Kilpatrick Decl. ¶ 19; AVM Report at 32.) The use of the trend surface component
allows the model to incorporate spatial effects, i.e., value impacts due to location, into the valuation.
(Id.) The required variables for the OLS model are tax assessed value, days between an origin date
and sale, and days between an origin date and sale squared. (Kilpatrick Decl. ¶ 20; AVM Report at
41.) The OLS model can also accept home size, year built, lot size, and number of bathrooms, if
sufficient data about these variables are available. (Id.) The required variables for the OLSXY
model are tax assessed value, days between an origin date and sale, days between an origin date and
sale squared, latitude, longitude, latitude squared, longitude squared, and latitude multiplied by
longitude. (Kilpatrick Decl. ¶ 21; AVM Report at 41-42.) The OLSXY model can also accept home

Standards of Professional Appraisal Practice (“USPAP”) defines as “the process of valuing a universe of properties as of
a given date using standard methodology, employing common data, and allowing for statistical testing.” (Id. at 26
(quoting USPAP 2014-2015)).

5

size, year built, lot size, and number of bathrooms, again, if these variables are available. (Id.) The
data used to run the models was obtained from CoreLogic, which maintains the largest, most
comprehensive property databases in the United States, as well as the loan tapes and loan files for
the Sample Properties. (Kilpatrick Decl. ¶ 22; AVM Report at 20-22.) This data included previous
sales prices, previous sales data, property characteristics such as footage, baths, age, and lot size, and
location on a county-by-county basis, from January 1, 1998 through December 31, 2008. (Kilpatrick
Decl. ¶ 22; AVM Report 22-23.)
Before running the Sample Properties through GAVM, Dr. Kilpatrick both calibrated and
filtered the model using only the comparable properties. First, Dr. Kilpatrick “calibrated” GAVM,
or tested its accuracy, using approximately 1.53 million sales from throughout the country.
(Kilpatrick Decl. ¶¶ 26-27; AVM Report at 48.) For each of the 2,783 counties in the dataset, he
randomly split sales into a 10% set and a 90% set. (Id.) Then, he ran the 10% set through GAVM
using the 90% set as the comparables. (Kilpatrick Decl. ¶ 28; AVM Report at 48.) Dr. Kilpatrick
removed the following from his calibration analysis: transactions where the home was constructed
after the sales date, because this indicated the sale was likely a land sale; transactions outside the
middle 70th percentile of sales price to assessed value ratio, to eliminate suspect data and/or nonarm’s-length transactions; and properties with “errors” 8 over 100%, because these likely indicated
data errors. (Kilpatrick Decl. ¶ 28; AVM Report at 48-49.) Using his 10% set, Dr. Kilpatrick
calculated GAVM’s coverage, or “hit rate,” which measures how many of the properties the model
was able to value, as well as the forecast standard deviation (“FSD”), which measures the model’s
ability to predict known sales prices. (Kilpatrick Decl. ¶¶ 30-31; AVM Report at 50-52.) GAVM’s
hit rate, without applying the 100% error filter, was 98.0%, which is much higher than the 80% hit

8

As Dr. Kilpatrick explains in his AVM Report, “the term error refers to the difference between the AVM value and the
actual sales price divided by the actual sales price (so that the results are expressed as a percentage of the AVM value to
the known sales price).” (AVM Report at 53.)

6

rate Freddie Mac has noted is considered high in the industry. (Kilpatrick Decl. ¶ 30; AVM Report
at 51.) Regarding FSD, of the approximately 1.53 million sales transactions valued by GAVM,
72.7% of the valuations were within 13% of the actual sales prices. (Kilpatrick Decl. ¶ 34; AVM
Report at 52.) The FSD for GAVM was 15.1%, and the mean absolute error was 10.45%. (Id.)
Second, Dr. Kilpatrick used a “Cross-Validation Filter” to ensure that the comparable
properties used in GAVM were properly valued. (Kilpatrick Decl. ¶ 42.) This filter eliminated
comparable properties from GAVM if the sales price was at least 25% higher or lower than
estimated using GAVM based on the remaining comparable properties in the same county. (Id.;
AVM Report at 59-60.) Dr. Kilpatrick used this filter because he concluded that such properties
either were not sold in arm’s-length transactions or had certain characteristics that significantly
impacted the sales price which either were not knowable using the available data or which the
GAVM model did not use. (Kilpatrick Decl. ¶ 42.) Accordingly, the Cross-Validation Filter was an
attempt to remove outlier comparable properties which would unduly skew the analysis. (Id. ¶¶ 4243.)
Dr. Kilpatrick then ran 924 9 of the 998 Sample Properties through both the OLS and
OLSXY sub-models of GAVM. (AVM Report at 35-37, 60-62.) If only one sub-model produced a
value, then that value constituted the final GAVM value prediction for the Sample Property, but if
both sub-models produced a value, then the two values were averaged together to produce a final
value prediction. (Id. at 35-36.) Using this process, Dr. Kilpatrick found the original appraised
values of 211 of the 924 Sample Properties were more than 15.1% (the FSD discussed above) higher
than their true, credible appraised values. (Kilpatrick Decl. ¶ 47; AVM Report at 62 n.158.) In

9

Dr. Kilpatrick eliminated 42 loans because they lacked an appraised value, effective date, county data, sales data,
address, or other required data. (AVM Report at 58; Kilpatrick Decl. ¶ 40.) Another 27 loans could not be valued by
GAVM based on the model’s required parameters. (AVM Report at 60; Kilpatrick Decl. ¶ 47.) Five additional loans
were also removed after running GAVM because “the appraisals were not representative of a valid appraisal or had
incorrect data because of miscoding in assessor records.” (AVM Report at 60-61; Kilpatrick Decl. ¶ 47.)

7

addition, Dr. Kilpatrick found the original appraisals for the Sample Properties were systemically
overvalued by a statistically significant average of 6.40% and that the 10% of supporting loan groups
which were overvalued the most were overvalued by an average of 9%. (Kilpatrick Decl. ¶¶ 3, 47;
AVM Report at 4, 63.) From this, Dr. Kilpatrick concluded that the LTV ratios for the Sample
Properties were significantly higher than represented in the offering documents for the
securitizations. (Id.) Dr. Kilpatrick further concluded that “no reasonable, competent appraisal
professional adhering to appraisal standards applicable at the time could, in my opinion, validate the
Deutsche Bank Appraisals as reliable, unbiased, or accurate.” (Kilpatrick Decl. ¶ 58; AVM Report at
66.)
In addition to his GAVM Report, Dr. Kilpatrick also prepared a CAM Report, in which he
assessed the appraisals for 206 10 of the 211 Sample Properties identified in the GAVM Report as
significantly overvalued. (Kilpatrick Decl. ¶¶ 59-60; Ex. 2 (“CAM Report”) at 2.) The purpose of
the CAM Report was to determine whether these appraisals were “credible,” i.e., whether they
adhered to appraisal standards and practices pursuant to the Uniform Standards of Professional
Appraisal Practice (“USPAP”). (Id.) To do this, Dr. Kilpatrick developed a Credibility Assessment
Model (“CAM”) which evaluates the frequency and magnitude of an appraisal report’s deviation
from settled appraisal standards and practice. (Kilpatrick Decl. ¶ 61; CAM Report at 2-3.) The
CAM scores appraisals using a list of 31 questions based on USPAP and other professional guidance
applicable to residential appraisals at the time. (Kilpatrick Decl. ¶ 67; CAM Report at 40.) The
questions are phrased to elicit a “yes” or “no” response based on a review of information derived
from loan tapes, loan files, and third-party sources. (Id.) A “no” response, which indicates that an
appraisal process was not properly followed, is also given a specific weight or score based on the
degree to which it affects the credibility of the appraisal. (Kilpatrick Decl. ¶ 69; CAM Report at 4010

Dr. Kilpatrick and his staff were unable to obtain sufficient data to analyze the remaining five Sample Properties.
(Decl. ¶ 65.)

8

41.) Thus, a “no” response to one question may result in a score of 2.54, while a “no” response to
another question may result in a score of 9.2. (Kilpatrick Decl. ¶ 72; CAM Report at 72, 89; Ex. 28.)
Dr. Kilpatrick also developed a scoring threshold, based on USPAP Standards Rules 1-1(b)
and 1-1(c), 11 beyond which he concluded the adherence to applicable appraisal standards was so
poor as to render the appraisal not “credible.” (Kilpatrick Decl. ¶ 74; CAM Report at 41, 98.) He
concluded that a total score of 14.13 could render an appraisal not credible under USPAP due to
either one major and one minor “no” response or a series of minor “no” responses. (Kilpatrick
Decl. ¶ 76; CAM Report at 99.) In order to evaluate the appraisals in the most conservative light,
Dr. Kilpatrick then raised this threshold score to 20, which means that an appraisal must elicit at
least three “no” responses, two of which would have to be major questions, to be deemed not
credible under the CAM. (Kilpatrick Decl. ¶ 80; CAM Report at 100-101.)
Of the 206 Sample Properties found to be overvalued by more than 15.1% using GAVM,
Dr. Kilpatrick found 168 appraisals (81.55%) were not credible using CAM. (Kilpatrick Decl. ¶ 80;
CAM Report at 101.) Dr. Kilpatrick explained that these appraisals contain sufficient errors such
that, in his opinion, “no reasonable appraiser adhering to the appraisal standards and practices at the
time could have believed the appraisals were credible.” (Kilpatrick Decl. ¶ 80; CAM Report at 101.)
On average, the appraisals contained 6.38 errors, or “no” responses. (Kilpatrick Decl. ¶ 81; CAM
Report at 102.)
In addition to using the CAM, Dr. Kilpatrick also had Recovco Mortgage Management, LLC
(“Recovco”), a separate entity, independently review 205 of the appraisals for the Sample Properties
found by GAVM to be significantly overvalued. (Kilpatrick Decl. ¶ 82; CAM Report at 103.)
11

USPAP Standards Rule 1-1(b) prohibits appraisers from committing a “substantial error of omission or commission
that significantly affects the appraisal.” USPAP Standards Rule 1-1(c) prohibits a “series of errors that . . . in the
aggregate affects the credibility of those results.” Accordingly, Dr. Kilpatrick identified certain questions which, in his
opinion, could by themselves lead to a “substantial error” impacting the credibility of the appraisal under Rule 1-1(b) as
well as other questions which would require a combination of less egregious errors to impact the appraisal’s overall
credibility. (CAM Report at 98.)

9

Recovco performed its standard collateral review to evaluate whether the appraisals adhered to
USPAP, Fannie Mae, and industry standard appraisal guidelines. (Kilpatrick Decl. ¶ 83; CAM
Report at 103.) Based on its evaluation, Recovco rendered a conclusion as to whether the appraisal
was “weak” (not credible), “moderate” (of questionable credibility), or “strong” (credible).
(Kilpatrick Decl. ¶ 83; CAM Report at 104.) It found 95.1% of the 205 appraisals were “weak” and
demonstrated significant discrepancies indicative of a non-credible appraisal. (Kilpatrick Decl. ¶ 86;
CAM Report at 104.) Recovco found the remaining appraisals were “moderate.” (Kilpatrick Decl. ¶
87.) According to Dr. Kilpatrick, Recovco’s review “validated” his CAM findings. (Id. ¶ 88.)

B.

Mr. Butler
Mr. Butler has over 43 years of experience in residential mortgage lending, including fifteen

years of experience underwriting and originating mortgage loans and supervising the origination and
approval of mortgage loans at multiple banks. (Dkt. No. 499, Decl. of Steven I. Butler (“Butler
Decl.”) ¶ 2.) He has also worked as a consultant in the banking industry since 1986. (Id.) This
work has included reviewing, or “reunderwriting,” residential mortgage loans to determine whether
they were originated and underwritten in accordance with applicable underwriting guidelines and
industry standards. (Id.; Ex. 1 (“Butler Report”) at 8-11.) In addition, Mr. Butler has served as an
expert in a number of cases, including as a mortgage loan reunderwriting expert in ten RMBS cases
since 2009. (Butler Decl. ¶ 5; Butler Report at 12.)
In his Report, Mr. Butler reunderwrote loan files underlying certificates at issue in this action
to determine whether they complied with representations in the offering documents, including
representations regarding compliance with applicable underwriting guidelines and the borrowers’
ability to repay. (Butler Report at 1-2.) Using the representative Sample Properties selected by Dr.
Cowan, Mr. Butler reunderwrote loans for which files were available that contained over 100 pages.
10

(Id. at 115 n.343.) If a loan file was not produced or contained fewer than 100 pages, Mr. Butler
used a loan from the supplemental random sample of 100 loans for each supporting loan group, in
accordance with Dr. Cowan’s sampling methodology. (Id.) See Massachusetts Mut. Life Ins. Co.,
989 F. Supp. 2d at 170. Mr. Butler ended up using 167 such supplemental loans and reunderwrote a

total of 998 loans. (Id.)
Before reunderwriting the loans, Mr. Butler instructed his team of experienced underwriters
to match the loans with the applicable underwriting guidelines in effect at or near the time of loan
origination whenever they were available. (Butler Decl. ¶ 13; Butler Report at 116.) If the applicable
originator underwriting guidelines were not available, however, he instructed the reunderwriting
team to use the applicable aggregator underwriting guidelines—i.e., underwriting guidelines of an
entity other than the originator, such as the securitization sponsor or an affiliate of the sponsor—in
effect at or near the time of origination. (Id.) Mr. Butler explained that, based on his experience,
“aggregator guidelines are appropriate to use when the originator guidelines are not available
because it is the aggregator that acquires the loans that are to be securitized and, in many instances,
either approves the guidelines used by the originator or instructs the originator to use the
aggregator’s guidelines” and, “[t]ypically, the guidelines of the originator and the aggregator have
similar parameters and metrics.” (Butler Decl. ¶ 13.)
If neither the applicable originator nor aggregator underwriting guidelines were available, or
if the applicable guideline was silent on an issue, 12 Mr. Butler directed his team to use “Minimum

12

Mr. Butler explained:
For example, underwriting guidelines sometimes do not explicitly instruct the underwriter to
investigate red flags that suggest the borrower provided false, misleading, or inaccurate statements
about important items such as income, employment, housing history, or debt obligations. However,
any competent underwriter should reject a loan application if it contained indications that the
borrower knowingly provided false information with respect to any of those items, and no reasonable
originator would originate a mortgage to a borrower who provided false information. The minimum
industry standards are designed to address fundamental requirements such as these and others, which
may not be expressly addressed in the underwriting guidelines but are common and essential.
(Butler Report at 113.)

11

Industry Standards” to reunderwrite the loan file. (Butler Decl. ¶ 15; Butler Report at 111.) The
Minimum Industry Standards, Mr. Butler explained, were basic industry standards which constituted
lenient standards found in underwriting guidelines in the mortgage industry from 2005 to 2007.
(Butler Decl. ¶ 16; Butler Report at 112.) “In other words, they were the minimum requirements
necessary for even the most lenient of originators to assess a borrower’s ability to repay the
mortgage and adequacy of the collateral.” (Butler Report at 112.) The Minimum Industry Standards
include verifying employment, investigating potential borrower misrepresentations, and taking steps
to ensure the borrower has the ability to repay the loan, among others. (Butler Decl., Ex. 8.)
Mr. Butler gleaned the Minimum Industry Standards from (1) his experience in the industry
and knowledge of standards used from 2005 to 2007; (2) discussions with underwriters on his staff
and members of the reunderwriting team who worked in the mortgage loan industry at that time; (3)
a review of underwriting guidelines, including manuals, references, matrices, and guides, used by
originators during that time; and (4) discussions with other experts he knows and with whom he
worked. (Butler Decl. ¶ 17; Butler Report at 112.) To confirm the accuracy of the Minimum
Industry Standards, Mr. Butler compared them to the guideline requirements of four significant
originators of loans between 2005 and 2007 that were known in the industry as having relatively
lenient underwriting standards: Countrywide Home Loans, Inc., Long Beach Mortgage Company,
New Century Financial Corporation, and WMC Mortgage Corp. (Butler Decl. ¶ 18; Butler Report at
112.) 13 He determined that the Minimum Industry Standards were generally consistent with these
four originators’ guidelines. (Id.)
Mr. Butler and his team found 3,539 individual underwriting guideline breaches in the 998
reunderwritten loans; most loans had multiple breaches. (Butler Decl. ¶ 7.) He determined that 744
of the 998 loans were originated with one or more breaches that meaningfully and substantially

13

Three of these originators contributed loans to the securitizations at issue in this action. (Butler Decl. ¶ 18.)

12

increased the credit risk associated with the loan. (Id. ¶ 7; Butler Report at 4.) The breaches
included LTV or DTI ratios that exceeded guidelines; absence of necessary documentation; failure
to investigate red flags, such as multiple loan applications with different stated incomes, recent credit
inquiries, and high stated income with low assets and bank deposits; and failure to investigate the
reasonableness of stated income. (Butler Decl. ¶ 7; Butler Report at 131-148.) Of those 744
materially defective loans, 475 (over 65%) were reunderwritten using the originators’ guidelines; 205
(over 27%) were reunderwritten using the aggregator’s guidelines; and 64 (8.6%) were
reunderwritten using either the Minimum Industry Standards only or Minimum Industry Standards
in combination with other sources such as representations in the offering documents. (Butler Decl.
¶¶ 14, 20.)14

C.

Procedural History
Defendants filed the instant motions to exclude the expert testimony of Dr. Kilpatrick and

Mr. Butler (“Daubert Motions”) on November 21, 2014. Plaintiff filed its oppositions on December
22, 2014 and included new declarations from Dr. Kilpatrick and Mr. Butler in support. On January
15, 2015, Defendants filed, along with their reply briefs, a motion to strike the declarations pursuant
to Rules 26(a)(2) and 37(c)(1) on the grounds that they included new and previously undisclosed
opinions. On March 27, 2015, the court held a hearing on the motion to strike as well as a nonevidentiary hearing on the Daubert Motions, as requested by the parties. At the hearing, the court
inquired as to the possibility of re-opening discovery regarding any “new” material included in the
declarations and the effect that might have on the Daubert Motions. Defendants’ counsel
represented that regardless of the court’s resolution of the motion to strike, including any re-opening

14

Only 39 of the 744 loans (less than 5.25%) had a material breach based solely on the Minimum Industry Standards,
and 25 loans (less than 3.4%) had material breaches based on a combination of Minimum Industry Standards and other
sources such as representations in the offering documents. (Butler Decl. ¶ 20.)

13

of discovery, Defendants wished to go forward with the Daubert Motions. On March 31, 2015, the
court denied Defendants’ motion to strike, concluding most of the content in the declarations
constituted proper expert supplementation in response to new criticisms raised after the experts
provided their original reports. (See Dkt. No. 439.) The court did, however, re-open discovery on a
limited number of issues which it found to constitute improper expert supplementation, but
explained that it would not await the close of the new expert discovery before ruling on the Daubert
Motions in light of Defendants’ counsel’s representation at the March 27, 2015 hearing. (See id.)

III.

STANDARD OF REVIEW

The admission of expert evidence is governed by Federal Rule of Evidence 702, which
codified the Supreme Court's holding in Daubert v. Merrell Dow Pharms., Inc., 509 U.S. 579 (1993),
and its progeny. See United States v. Diaz, 300 F.3d 66, 73 (1st Cir. 2002). Rule 702 provides:
If scientific, technical, or other specialized knowledge will assist the trier of fact to
understand the evidence or to determine a fact in issue, a witness qualified as an
expert by knowledge, skill, experience, training, or education, may testify thereto in
the form of an opinion or otherwise, if (1) the testimony is based upon sufficient
facts or data, (2) the testimony is the product of reliable principles and methods, and
(3) the witness has applied the principles and methods reliably to the facts of the
case.
Fed. R. Evid. 702. The trial court must determine whether the expert's testimony “both rests on a
reliable foundation and is relevant to the task at hand” and whether the expert is qualified. Daubert,
509 U.S. at 597; Diaz, 300 F.3d at 73. An expert's methodology is the “central focus of a Daubert
inquiry.” Ruiz-Troche v. Pepsi Cola of P.R. Bottling Co., 161 F.3d 77, 81 (1st Cir. 1998). “In short,
a court must answer three questions: ‘Is this junk science?’ ‘Is this a junk scientist?’ Is this a junk
opinion?’” First Choice Armor & Equipment, Inc. v. Toyobo America, Inc., 839 F. Supp. 2d 407,
416 (D. Mass. 2012) (quoting McGovern ex rel. McGovern v. Brigham & Women’s Hosp., 584 F.
Supp. 2d 418, 424 (D. Mass. 2008)).
14

The Daubert Court identified four factors which might assist a trial court in determining the
admissibility of an expert’s testimony: (1) whether the theory or technique can be and has been
tested; (2) whether the technique has been subject to peer review and publication; (3) the technique's
known or potential rate of error; and (4) the level of the theory's or technique's acceptance within
the relevant discipline. Milward v. Acuity Specialty Products Group, Inc., 639 F.3d 11, 14 (1st Cir.
2011). “These factors,” however, “‘do not constitute a definitive checklist or test.’” Id. (quoting
Kumho Tire Co. v. Carmichael, 526 U.S. 137, 150 (1999)). “Given that ‘there are many different
kinds of experts, and many different kinds of expertise,’ these factors ‘may or may not be pertinent
in assessing reliability, depending on the nature of the issue, the expert’s particular expertise, and the
subject of his testimony.’” Id. (quoting Kumho Tire Co., 526 U.S. at 150.)).
While expert testimony may be excluded if there is “too great an analytical gap between the
data and the opinion proffered,” id. at 15 (quoting Gen. Elec. Co. v. Joiner, 522 U.S. 136, 146
(1997)), “[t]his does not mean that trial courts are empowered ‘to determine which of several
competing scientific theories has the best provenance,’” id. (quoting Ruiz-Troche, 161 F.3d at 85.)).
“Daubert does not require that a party who proffers expert testimony carry the burden of proving to
the judge that the expert’s assessment of the situation is correct.” Id. (quoting Ruiz-Troche, 161
F.3d at 85)). Rather, “[t]he proponent of the evidence must show only that ‘the expert’s conclusion
has been arrived at in a scientifically sound and methodologically reliable fashion.’” Id. (quoting
Ruiz-Troche, 161 F.3d at 85)). As long as an expert’s scientific testimony rests upon “‘good
grounds,’ based on what is known,” Daubert, 509 U.S. at 590, “it should be tested by the adversarial
process, rather than excluded for fear that jurors will not be able to handle the scientific
complexities,” Milward, 639 F.3d at 15. Thus, “[v]igorous cross-examination, presentation of
contrary evidence, and careful instruction on the burden of proof are the traditional and appropriate
means of attacking shaky but admissible evidence.” Daubert, 509 U.S. at 596.
15

IV.
A.

ANALYSIS

Motion to Exclude Dr. Kilpatrick’s Testimony
Defendants seek to exclude Dr. Kilpatrick’s testimony on a number of grounds. They

challenge his qualifications as an expert and the lack of independent validation, peer review or
publication, and industry acceptance of GAVM and CAM. In addition, regarding GAVM,
Defendants assert it overstates LTV; is not an appraisal and, thus, is being misused by Dr.
Kilpatrick; improperly ignores sales data; produces inconsistent results between the OLS and
OLSXY sub-models; improperly uses tax assessed value as a variable, but omits other important
variables; and employs dubious filtering techniques. Regarding CAM, Defendants assert Dr.
Kilpatrick improperly opines as to the original appraisers’ state of mind, bases his analysis on
unreliable information, provides no support for the 31 questions or weighting used, and improperly
relies on Recovco’s analysis. In response, Plaintiff asserts Defendants’ attacks on GAVM and CAM
are meritless and, at most, go to the weight, rather than the admissibility, of Dr. Kilpatrick’s
opinions.
As an initial matter, the court finds Dr. Kilpatrick is sufficiently qualified as an expert. He
has extensive experience regarding real estate appraisals and automated valuation models.
Defendants have not cited a single case in which a court has excluded Dr. Kilpatrick’s testimony
based on a lack of expertise or qualification, despite numerous Daubert challenges. Moreover, while
Defendants point to Dr. Kilpatrick’s false statements on his Certified Real Estate Appraiser
applications for two states and his purported difficulty testifying at his deposition without referring
to his materials, these are, at most, issues of credibility for the jury and do not warrant excluding Dr.
Kilpatrick’s testimony. See, e.g., Seahorse Marine Supplies, Inc. v. Puerto Rico Sun Oil Co., 295
F.3d 68, 81 (1st Cir. 2002) (“The ultimate credibility determination and the testimony’s accorded
weight are in the jury’s province.”).
16

1.

GAVM

As for Dr. Kilpatrick’s testimony regarding GAVM, the court finds his opinion is relevant
and rests upon sufficiently reliable grounds for admissibility purposes. First, contrary to
Defendants’ assertions, peer review and independent validation are not necessarily required. See
Daubert, 509 U.S. at 593 (explaining that the four identified factors are not “a definitive checklist or
test” and noting that peer review and publication “does not necessarily correlate with reliability”);
Granfield v. CSX Transp., Inc., 597 F.3d 474, 486 (1st Cir. 2010) (“The mere fact of publication, or
lack thereof, in a peer-reviewed journal is not a determinative factor in assessing the scientific
validity of a technique or methodology on which an opinion is premised.”). In any event, it is clear
that AVMs have been subject to peer review and are accepted within the real estate appraisal and
underwriting industry, although this exact model is particular to Dr. Kilpatrick. (Kilpatrick Decl. ¶
12, Ex. 4.) See Assured Guar. Mun. Corp. v. Flagstar Bank, FSB, 920 F. Supp. 2d 475, 505
(S.D.N.Y. 2013) (noting that the methodology applied by the plaintiff’s expert, which included the
use of an AVM, “is the same kind of methodology underwriters apply in the field”); In re Katrina
Canal Breaches Consol. Litig., 2007 WL 3245438, at *13 (E.D. La. Nov. 1, 2007) (“Clearly, mass
appraisal is an accepted methodology. . . . This approach is used in appraiser’s offices all over the
country to determine value.” (internal citation omitted)); Turner v. Murphy Oil USA, Inc., 2006 WL
91364, at *5 (E.D. La. Jan. 12, 2006) (“Dr. Kilpatrick is qualified and is using generally-accepted
methodology.”). In fact, Deutsche Bank itself used AVMs as part of its valuation due diligence for
loans at issue in this action. (Dkt. No. 507, Decl. of Jennifer J. Barrett (“Barrett Decl.”), Ex. 20 at
84, Ex. 21 at 99.) Moreover, as Plaintiff’s counsel explained at the hearing, unlike commercially
available AVMs, which are proprietary and thus cannot be tested or reverse-engineered, Dr.
Kilpatrick provided the computer code for GAVM and the CoreLogic database to Defendants,
whose experts were able to replicate its results. (Barret Decl., Ex. 5 at 59-60, Ex. 10.) Accordingly,
17

Dr. Kilpatrick’s methodology can be adequately tested on cross examination. See Assured Gaur.
Mun. Corp., 920 F. Supp. 2d at 505.
Defendants’ other arguments for excluding Dr. Kilpatrick’s opinion regarding GAVM all go
to weight rather than admissibility. In particular, while Defendants argue Dr. Kilpatrick improperly
recalculated the LTV ratios for the Sample Properties by using the lower of the GAVM value, sales
prices, or original appraised value, he did so because the Prospectus Supplements stated LTV ratios
were calculated in this manner. (Kilpatrick Decl. ¶ 52; AVM Report at 67 n.164; Dkt. No. 374, Ex.
1 at 7, Ex. 4 at 8, Ex. 5 at 8, Ex. 6 at 108, Ex. 7 at 121, Ex. 8 at 36, Ex. 9 at 165, Ex. 10 at 127.) The
cases Defendants cite for the proposition that Dr. Kilpatrick improperly omitted sales data from his
analysis are distinguishable. In Exxon Mobil v. Albright, 71 A.3d 30, 102 (Md. 2013), for example,
the Court of Appeals of Maryland held the trial court should have excluded Dr. Kilpatrick’s
testimony regarding assessment of diminished property values because he did not take into account
“the comparable sales data of the nearly 180 real estate sales” in the area at the relevant time. See
also Palisano v. Olin Corp., 2005 WL 6777561, at *5 (N.D. Cal. July 5, 2005). Here, in contrast,
GAVM does consider comparable sales data.
As for the use of tax assessed values and omission of other variables, the Supreme Court has
explained:
While the omission of variables from a regression analysis may render the analysis
less probative than it otherwise might be, it can hardly be said, absent some other
infirmity, that an analysis which accounts for the major factors must be considered
unacceptable as evidence . . . . Normally, failure to include variables will affect the
analysis’ probativeness, not its admissibility.
Bazemore v. Friday, 478 U.S. 385, 400 (1986) (internal citation and quotation marks omitted).
Defendants’ own expert testified that tax assessed data is commonly used in the AVM industry.
(Barrett Decl., Ex. 4 21-22.) Indeed, other courts have rejected challenges to Dr. Kilpatrick’s and
other expert’s analyses regarding the use or omission of similar variables. See Hartle v. FirstEnegery
18

Generation Corp., 2014 WL 1317702, at *9 (W.D. Pa. March 31, 2014) (“Kilpatrick had ‘good
grounds’ for his choices in applying the hedonic regression analysis. . . . For example, even if the
data relied on by the expert is imperfect, and more (or different) data might have resulted in a better
or more accurate estimate in the absolute sense, it is not the district court’s role under Daubert to
evaluate the correctness of facts underlying an expert’s testimony.” (internal citation and quotation
marks omitted)); Federal Housing Agency v. Nomura Holding America, Inc., --- F.Supp.3d ----,
2015 WL 568788, at *11 (S.D.N.Y. Feb. 11, 2015) (“[T]he reliance by FHFA experts on tax records
from 2013 and 2014 in their assessment of property valuations during the period of 2005 to 2007
may be entirely appropriate. Post-origination evidence is admissible if it tends to show the existence
or non-existence of a fact during the relevant period of time. Thus, the defendants’ complaint about
the use of an AVM which relied on recent tax assessed values misses the mark.”). Moreover, Dr.
Kilpatrick indicated that including additional variables would have necessitated excluding large
numbers of comparable properties. (Kilpatrick Decl. ¶ 23.)
Dr. Kilpatrick’s filtering and calibration techniques also do not render his analysis
inadmissible. Defendants’ own expert testified that filtering techniques in a regression analysis are
common, are “often reported in the literature,” and that he uses them himself. (Barrett Decl., Ex. 5
at 126; see also Barrett Decl., Ex. 4 at 48-51.) As Dr. Kilpatrick explains, some filtering is necessary
for regression models, which are especially sensitive to outliers. (Kilpatrick Decl. ¶ 43.) Moreover,
the Cross-Validation Filter is not applied to the Sample Properties but only to the comparables, and
it is only when the filter is entirely removed that the analysis changes significantly. 15 (Id. ¶ 44.)
While Defendants assert Dr. Kilpatrick’s filtering and calibration constitute manipulation of the data

15

In his declaration, Dr. Kilpatrick explains that he ran GAVM using relaxed cut-off filters of 40%, 60%, 80%, 100%,
and, finally, no filter, in addition to the 25% filter originally used. (Kilpatrick Decl. ¶ 44.) Only when he completely
removed the filter did the R-squared statistic, which measures the predictiveness of the model, fall substantially. (Id.)

19

to reach a desired result, this, again, is fodder for cross-examination and not an appropriate ground
for excluding his opinion. 16
2.

CAM

The admissibility of Dr. Kilpatrick’s opinion regarding CAM is, in the court’s view, a closer
question. Nevertheless, the court finds his analysis was sufficiently reliable for admissibility
purposes, except for one minor aspect of his report. See Federal Housing Finance Agency v.
Nomura Holding America, 2015 WL 353929, at *4-6 (Jan. 28, 2015) (denying the defendants’
motion to exclude Dr. Kilpatrick’s nearly identical methodology and opinions regarding GAVM and
CAM, but excluding Dr. Kilpatrick’s opinions as to the subjective beliefs of the original appraisers).
First, contrary to Defendants’ assertion, Dr. Kilpatrick does provide support for his 31
questions and the weight assigned to each. He points to the USPAP standards, commonly used
appraisal forms, and his own knowledge and experience in the field. (Kilpatrick Decl. ¶¶ 67-70, Ex.
24.) See Milward, 639 F.3d at 19 (“In concluding that the weight of the evidence supported the
conclusion that benzene can cause APL, Dr. Smith relied on his knowledge and experience in the
field of toxicology and molecular epidemiology and considered five bodies of evidence drawn from
the peer-reviewed scientific literature on benzene and leukemia.”). Defendants argue many of the
cited sources do not support Dr. Kilpatrick’s specific questions. And while the court struggles at
times to see the connection between a given source and the CAM question, “[t]he soundness of the
factual underpinnings of the expert’s analysis and the correctness of the expert’s conclusions based
on that analysis are factual matters to be determined by the trier of fact.” Id. at 22 (quoting Smith v.
Ford Motor Co., 215 F.3d 713, 718 (7th Cir. 2000)). Defendants’ reliance on Barletta Heavy Div.,
Inc. v. Travelers Ins. Co., 2013 WL 5797612, at *8-9 (D. Mass. Oct. 25, 2013), is misplaced. There,

16

Defendants’ arguments regarding the purported inconsistent results between the OLS and OLSXY sub-models are
similarly unconvincing. The two sub-models have a statistical correlation of .996, despite the hand-picked outliers
Defendants cite, and there is nothing inherently unreliable in averaging two sub-models. (Kilpatrick Decl. ¶ 46.)

20

the expert failed to identify “any insurance manuals, industry publications or any other sources in
support of his opinion. He has pointed to no objective sources for his opinions nor identified any
definable set of insurance industry ‘best practices’ against which he measures Traveler’s conduct.”
Id. at *8. In addition, the expert “offer[ed] a series of unanchored conclusions.” Id. at *9. That is
not the case here.
Second, other questionnaires similar to CAM are relied upon in the market. (Kilpatrick
Decl. ¶ 73.) In fact, Defendants’ expert uses such tools and attached ten commonly used appraisal
review forms to his report. (Barrett Decl., Ex. 9, Ex. 16 at 185-197.) Again, unlike those
commercially available tools, Defendants can replicate and test Dr. Kilpatrick’s analysis. Moreover,
in a sense, the CAM is similar to a survey, which courts have found are generally admissible. See,
e.g., United States v. American Express Co., 2014 WL 2879811, at *10 (E.D.N.Y. June 24, 2014)
(“As a practical matter, there is no such thing as a perfect survey. . . . Accordingly, errors in a
survey’s methodology . . . generally bear upon the probative weight to be afforded the survey, rather
than it admissibility.” (internal citation and quotation marks omitted)).
Third, Recovco’s review somewhat corroborated CAM’s results. Although that review does
not constitute independent validation of Dr. Kilpatrick’s methodology and he likely will not be able
to testify about it at trial, see U.S. v. Zolot, 968 F. Supp. 2d 411, 426 n.27 (D. Mass. 2013), courts
may consider otherwise inadmissible evidence in the context of a Daubert challenge. See Fed. R.
Evid. 104(a); Celebrity Cruises Inc. v. Essef Corp., 434 F. Supp. 2d 169, 190 (S.D.N.Y. 2006)
(“Accordingly, ‘in determining whether to admit scientific testimony the court may consider
materials not admissible in evidence.’” (quoting Ruffin v. Shaw Indus., Inc., 149 F.3d 294, 297 (4th
Cir. 1998)). 17

17

Defendants’ other arguments for exclusion, namely, the inconsistencies between some of the CAM questions, while
no doubt bearing on the persuasiveness, or weight, of the analysis, do not render it inadmissible. See Milward, 639 F.3d

21

As for Defendants’ argument that Dr. Kilpatrick should not be permitted to testify as to the
original appraisers’ state of mind, the court agrees. See Holmes Grp., Inc. v. RPS Prods., Inc., 2010
WL 7867756, at *5 (D. Mass. June 25, 2010) (“An expert witness may not testify as to another
person’s intent. No level of experience or expertise will make an expert a mind-reader.”). Judge
Cote’s analysis of this issue in Federal Housing Finance Agency v. Nomura Holding America, 2015
WL 353929, which involved similar passages from the report Dr. Kilpatrick submitted in that case, is
particularly on point:
FHFA will apparently attempt to establish that at least some appraisers did not
actually believe at the time that they submitted their appraisals that the appraisals
accurately reflected the property values. But, while it may be able to accomplish this
task through circumstantial evidence, it may not do so by proffering an opinion of its
expert on the subjective beliefs of the appraisers.
Accordingly, passages such as the following are stricken from the Report, and FHFA
may not elicit equivalent testimony from Kilpatrick during his direct testimony:
“I conclude that it is highly doubtful whether a reasonable appraiser adhering to the
appraisal standards and practices applicable during the relevant time period could
have concluded that the original appraised values . . . .”
“I conclude that it was highly questionable whether a reasonable appraiser could
have believed that the appraisal values . . . were credible . . . .”
“[I]n my opinion, no reasonable appraiser adhering to appraisal standards applicable
at the time could believe the appraisal credible.”
“[N]o reasonable appraiser adhering to the appraisal standards and practices
applicable at the time could have believed the appraisals were credible.”
FHFA argues that Kilpatrick is simply offering classic standard-of-care testimony
about the degree to which certain Nomura Appraisals deviated from USPAP and
applicable appraisal practice, and from which a fact finder may reasonably infer that
an appraiser did not believe that the appraisal was accurate at the time it was made.
FHFA is correct that Kilpatrick may opine about the degree to which the historically
performed appraisals deviated from the standards established by USPAP. What the
expert may not do, however, is take that analysis further and fashion an opinion
about the appraisers’ subjective state of mind. As Kilpatrick acknowledged during

at 22 (“There is an important difference between what is unreliable support and what a trier of fact may conclude is
insufficient support for an expert’s conclusion.” (emphasis in original)).

22

his deposition, he is not in a position to opine on the state of mind of any of the
appraisers.
Id. at *5-6. Judge Cote, however, permitted Dr. Kilpatrick to opine as to the appraisals’
“credibility,” a defined USPAP term which “reflects an objective assessment of an appraisal.” Id. at
*6. The court reaches the same conclusion here. Accordingly, Dr. Kilpatrick may not directly testify
as to the original appraisers’ state of mind, but he may testify as to the appraisals’ “credibility.”

B.

Motion to Exclude Mr. Butler’s Testimony
Defendants seek to exclude Mr. Butler’s expert testimony on the grounds that he improperly

relied on the Minimum Industry Standards, used the wrong guidelines at times, based many findings
on missing documents, used post-origination information, and relied wholesale on Dr. Kilpatrick’s
analysis. Plaintiff, again, asserts Defendants’ challenges are meritless and, at most, go to the weight,
not the admissibility, of Mr. Butler’s opinions.
Defendants argue forcefully that Mr. Butler cannot base his material misrepresentation
findings on the Minimum Industry Standards because it is only the failure to comply with the
specific underwriting guidelines described in the offering documents which is relevant. Plaintiff
argues, on the other hand, the Minimum Industry Standards are relevant when the applicable
guidelines cannot be found or are silent on important issues. Plaintiff may be correct that the
Minimum Industry Standards have some relevance under certain circumstances, but the court will
defer deciding the issue at this time. For now, the court concludes that Mr. Butler’s preparation of
the Minimum Industry Standards was sufficiently reliable because they are based on specific
standards and experts may opine as to industry customs and practices, if sufficiently qualified. See
Federal Housing Finance Agency v. Nomura, 2015 WL 930276, at *4 (S.D.N.Y. Jan. 29, 2015)
(“FHFA has shown that the process that [the expert] employed to identify the minimum
underwriting standards that prevailed in the industry during the relevant timeframe is sufficiently
23

reliable to make his testimony admissible. It is not novel for an expert to opine on customs and
practices within an industry.”); Assured Guarn. Mun. Corp., 920 F. Supp. 2d at 505 (“[E]xperts
qualified by their experience may testify to their conclusions as long as they exhibit ‘in the
courtroom the same level of intellectual rigor that characterizes the practice of an expert in the
relevant field.’ . . . Walzak articulated the sources of information on which she relied . . . and applied
her experience in the underwriting industry to the resultant findings to make a determination as to
whether the deficiencies in a particular loan rose to the level of materiality.” (quoting Kumho Tire,
526 U.S. at 152)). If the court precludes Mr. Butler from testifying about Minimum Industry
Standards, it will not be because he is insufficiently qualified or prepared them in an unreliable
manner but, rather, because those standards are not relevant to the task at hand. See Federal
Housing Finance Agency v. Nomura, 2015 WL 930276, at *3-4.
Defendants next argue Mr. Butler’s opinion should be excluded because he applied the
wrong guidelines at times. As an initial matter, the court will not take Plaintiff’s invitation to
preclude this argument based on Defendants’ alleged discovery violation of failing to identify the
applicable guidelines in response to an interrogatory, although it does take into consideration the
seeming unfairness of refusing to provide this information but then faulting Plaintiff for applying
the wrong guidelines. Plaintiff, the court finds, waited too long to raise this issue, despite its
awareness of Defendants’ refusal to provide the discovery for some time. See Monteagudo v.
Asociacion de Empleados del Estado Libre Asociado de Puerto Rico, 554 F.3d 164, 172 n.8 (1st Cir.
2009) (“[T]his was a discovery issue that AEELA should have addressed earlier either by way of a
motion to compel or a request for sanctions under Fed.R.Civ.P 37(c).”). In any event, only a small
portion of the loans were reunderwritten using the purported wrong guidelines, and Mr. Butler has
since explained that his analysis does not materially change even when using the guidelines to which
Defendants point. (Bulter Decl. ¶¶ 23-25.) Any error on Mr. Butler’s part does not render his
24

analysis inadmissible. See In re Washington Mut. Mortg. Backed Sec. Litig., 2012 WL 2995046, at *6
(W.D.Wash. July 23, 2012) (“Defendants have raised some question as to whether Holt properly
applied each of the guidelines. But this hardly requires exclusion of his report, particularly where
both sides seem to agree that application of the underwriting guidelines requires some discretionary
decision-making. It is up to a jury to determine whether the purported flaw’s in Holt’s analysis
renders his opinion unworthy of merit.”).
Defendants also fault Mr. Butler for basing many of his findings on documents missing from
the loan files, contending that this does not demonstrate non-compliance with guidelines at the time
of the original underwriting because there could be a variety of reasons why those documents are
missing now. The court concludes missing loan documents at this time may provide circumstantial
evidence that those documents were also missing at the relevant time. Ultimately, the trier of fact
will have to make that determination. But it is not a reason to exclude Mr. Butler’s opinion. See
Milward, 639 F.3d at 22 (“When the factual underpinning of an expert’s opinion is weak, it is a
matter affecting the weight and credibility of the testimony—a question to be resolved by the jury.”
(quoting U.S. v. Vargas, 471 F.3d 255, 264 (1st Cir. 2006)).
Defendants’ arguments regarding Mr. Butler’s use of post-origination information are
similarly unavailing. As Plaintiff asserts, the guidelines generally required underwriters to verify the
reasonableness of information and to follow up on red flags. Thus, post-origination sources may
provide circumstantial evidence of failures in that regard, as many courts have held. See, e.g.,
Federal Housing Agency v. Nomura Holding America, Inc., 2015 WL 568788, at *10 (“The
defendants are wrong [that post-origination information is irrelevant]. Direct or circumstantial
evidence, regardless of when that evidence first became available, would be relevant if it helped to
demonstrate that an Originator did or did not follow its own underwriting guidelines or that the loan
did or did not qualify under the Originator’s guidelines.”). Defendants’ specific criticism of the use
25

of Bureau of Labor Statistics (“BLS”) data likewise fails. Mr. Butler referenced BLS data because
other sources do not maintain historical data but BLS does. Moreover, similar to the expert in
Assured Guar. Mun. Corp., 920 F. Supp. 2d at 506, Mr. Butler adequately accounted for the
potential that BLS data might understate incomes by finding a borrower’s stated income
unreasonable only when it exceeded the 90th percentile of the BLS index for the borrower’s
occupation, position, and geographic location. See also Cummings v. Standard Register Co., 265
F.3d 56, 64 (1st Cir. 2001) (“Duffy offered sufficient explanations for why he chose to use BLS data
and Cummings’ 1997 salary in his calculations.”).
Lastly, the court finds no issue with Mr. Butler’s reliance on Dr. Kilpatrick’s data for his
conclusion that loans violated the guidelines’ LTV requirements. Mr. Butler did not simply parrot or
rehash Dr. Kilpatrick’s finings but, rather, reached independent conclusions as to breaches of
underwriting guidelines and whether those breaches substantially increased the loans’ credit risk. See
Ferrara & DiMercuio v. St. Paul Mercury Ins. Co., 240 F.3d 1, 9 (1st Cir. 2001) (“[T]he opinion he
rendered was his own . . . . Federal Rule of Evidence 703 allows Malcolm to have taken
O’Donnell’s report and opinion into account when forming his own expert opinion.”) Moreover, as
the First Circuit has explained, “when an expert relies on the opinion of another, such reliance goes
to the weight, not to the admissibility of the expert’s opinion.” Id.

V.

CONCLUSION

For these reasons, the court ALLOWS Defendants’ motion to exclude the expert testimony
of Dr. Kilpatrick insofar as it seeks to preclude him from testifying as to the original appraisers’ state
of mind but otherwise DENIES the motion. (Dkt. No. 355.) The court also DENIES Defendants’
motion to exclude the expert testimony of Mr. Butler. (Dkt. No. 359.)
It is So Ordered.
26

_/s/ Mark G. Mastroianni________
MARK G. MASTROIANNI
United States District Judge

27