`
`UNITED STATES PATENT AND TRADEMARK OFFICE
`______________
`
`BEFORE THE PATENT TRIAL AND APPEAL BOARD
`______________
`
`LIBERTY MUTUAL INSURANCE CO.
`Petitioner
`
`v.
`
`PROGRESSIVE CASUALTY INSURANCE CO.
`Patent Owner
`______________
`
`Case CBM2012-00004
`Patent 6,064,970
`______________
`
`Before the Honorable JAMESON LEE, JONI Y. CHANG, and MICHAEL R.
`ZECHER, Administrative Patent Judges.
`
`REBUTTAL DECLARATION OF MARY L. O’NEIL ON BEHALF OF
`PETITIONER LIBERTY MUTUAL INSURANCE CO. REGARDING U.S.
`PATENT NO. 6,064,970
`
`I, Mary L. O’Neil, hereby declare under penalty of perjury:
`
`I have previously been asked by Liberty Mutual Insurance Co. (“Liberty
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`Mutual”) to testify as an expert witness in this action. For purposes of this rebuttal
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`declaration, I have been asked by Liberty Mutual to respond to certain assertions and
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`opinions offered by Michael Miller and Progressive Casualty Insurance Co.
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`(“Progressive”) concerning U.S. Patent No. 6,064,970 (“the ‘970 patent”) in this
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`matter.
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`
`
`
`
`
`
`Liberty Mutual Exhibit 1022
`Liberty Mutual v. Progressive
`CBM2012-00004
`Page 00001
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`1.
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`I am the same Mary L. O’Neil who provided a Declaration in this matter
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`executed on September 14, 2012 as Exhibit 1011.
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`2. My information regarding experience, qualifications, and compensation
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`are provided along with my prior Declaration and Curriculum Vitae and case list
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`(Exhibit 1012).
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`I.
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`Scope of Rebuttal Declaration
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`3.
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`I have been asked to respond to certain assertions and opinions of Mr.
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`Michael Miller expressed in his declaration of May 1, 2013 as Exhibit 2011, his
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`supplemental declaration of May 22, 2013 as Exhibit 2020, and certain assertions of
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`Progressive in its Patent Owner’s Response of May 1, 2013.
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`4.
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`In developing my opinions below, and in addition to the materials
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`identified in my prior declaration at paragraph 14, I have considered the following
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`materials:
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` Herrod Reference, GB2286369 (Ex. 1007);
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` Declaration of Michael Miller (Ex. 2011);
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` Supplemental Declaration of Michael Miller, including a document
`entitled “Actuarial Standard of Practice No. 12” (Ex. 2020);
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` Document entitled “Risk Classification Statement of Principles” (Ex.
`2012);
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` Patent Owner’s Response (Paper 25) (“Opposition” or “Opp.”);
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`2
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` Board’s Decision on Institution of Covered Business Method Review
`(Paper 10);
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` All other materials referenced as exhibits herein.
`II. Analysis and Opinions
`A. Mr. Miller’s Opinions and Progressive’s Assertions Regarding
`“Actuarial Classes” and Determining Auto Insurance Premiums
`
`5.
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`In providing a definition of “actuarial class,” Mr. Miller states:
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`In the field of motor vehicle insurance as of 1996, a person or ordinary
`skill in the art would have understood that “actuarial class” had the same
`meaning as risk class. . . . This definition is consistent with the definition
`in the Risk Classification Statement of Principles of the American
`Academy of Actuaries. A person of ordinary skill in the art in 1996
`would have adhered to this Statement of Principles.”
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`Ex. 2011 ¶ 16 (Emphasis added).
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`6. Mr. Miller has presented the Risk Classification Statement of Principles
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`(Ex. 2012) as if it were a binding verbatim requirement to be followed. That is
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`incorrect. The guidance provided by the Statement of Principles and its usage is
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`explained by Interpretative Opinion 4: Actuarial Principles and Practices (1982) of
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`the American Academy of Actuaries (AAA, the umbrella organization for all
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`actuaries), which would have been in effect through 1996. In fact, Interpretative
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`Opinion 4: Actuarial Principles and Practices (Ex. 1023)1 states in essence that the
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`1 Exhibit 1023 is a true and correct copy of “Interpretative Opinion 3: Professional
`Communications of Actuaries and Interpretive Opinion 4: Actuarial Principles and
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`3
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`Statement of Principles cited by Mr. Miller is only a guideline—one possible reference
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`out of a large body of material that form the bases of Generally Accepted Actuarial
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`Principles and Practices (which are a broad overview of how actuarial practice should
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`be done):
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`(a) Generally Accepted Actuarial Principles and Practices.
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`Guide 4(b) requires the actuary to “exercise due diligence to ensure . . .
`that the methods employed are consistent with the sound actuarial
`principles and practices established by precedents or common usage
`within the profession. . .” Such “sound actuarial principles and practices”
`constitute Generally Accepted Actuarial Principles and Practices.
`
`(b) Sources of Generally Accepted Actuarial Principles and Practices.
`
`Sources of Generally Accepted Actuarial Principles and Practices emerge
`from the utilization and adoption of concepts described in actuarial
`literature. Such literature includes, but is not limited to, the Actuarial standards
`and Actuarial Compliance Guidelines adopted by the Actuarial Standards Board,
`the Recommendations and Interpretations published under the auspices of the
`American Academy of Actuaries; the professional journals of recognized professional
`actuarial organizations (including the Statements of Principles promulgated by the
`Society of Actuaries and the Casualty Actuarial Society); recognized actuarial
`textbooks and study materials; and applicable provisions of law and regulations; and
`may include standard textbooks or other professional publications in related fields
`such as mathematics, statistics, accounting, economics and law.
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`Ex. 1023 at 6 (emphasis added, footnote omitted).
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`7. Mr. Miller further incorrectly argues that a POSITA would have strictly
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`adhered to the Statement of Principles in making “statistical considerations such as
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`Practices,” adopted 1970-1982 by the American Academy of Actuaries and
`republished in 1992 by the Actuarial Standards Board, which I obtained online at
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`4
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`the homogeneity, credibility, and predictive reliability of the claims data that will be
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`gathered for each actuarial class.” Ex. 2011 ¶ 34. Rather, Opinion 4 again rebuts this
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`assertion, stating ultimately in subsection (d) that “In all cases the professional
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`judgment of the actuary should prevail” and provides Standards of Practice and
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`Compliance Guidelines:
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`(c) Standards of Practice and Compliance Guidelines.
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`An actuary working in a specialized field should take into consideration any
`published Standard of Practice or Compliance Guideline of the Actuarial
`Standards Board. An actuary who uses principles or practices which
`differ materially from any published Standard of Practice or Compliance
`Guideline must be prepared to support the particular use of such
`principles or practices and should include in an actuarial communication
`appropriate and explicit information with respect to such principles and
`practices. . . . When dealing with a specific situation not covered by a published
`Standard of Practice or Compliance Guideline, the actuary should be aware of
`relevant precedent and generally available literature in deciding what constitutes
`Generally Accepted Actuarial Principles and Practices.
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`Ex. 1023 at 6-7 (emphasis added); cf. also Ex. 2012 at 12.2
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`8.
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`Indeed, one such Standard of Practice—No. 12, attached to Mr. Miller’s
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`supplemental declaration Ex. 2020—further belies Mr. Miller’s strict adherence to the
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`http://www.actuarialstandardsboard.org/pdf/superseded/intopinion.PDF.
`2 “These statistical considerations—homogeneity, credibility and predictive stability—
`are somewhat conflicting” and “there is no one statistically correct risk classification
`system. . . . The decision as to relative weights to be applied will, in turn, be influenced
`by the nature of the risks, the management philosophy of the organization assuming
`the risk and the judgment of the designer of the system.”
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`5
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`Statement of Principles and repeated insistence on the use of actual claims data to
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`generate actuarial classes (see Ex. 2011 ¶¶ 16-18, 34-35, 45):
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`“5.1 Methods to Demonstrate Cost Differences—A risk classification
`system is equitable if material differences in costs for risk characteristics
`are appropriately reflected in the rate. Classification subsidies result
`when the price paid by an individual or class of individuals fails to reflect
`differences in costs among the risk classes.
`
`A relationship between a risk characteristic and cost is demonstrated if it
`can be shown that experience is different when the characteristic is
`present. In demonstrating the relationship, the actuary can rely on actual or
`reasonably anticipated experience; the actuary is not constrained to using only the
`experience of the actuary’s client or company. Relevant information from any reliable
`source, including statistical or other mathematical analysis of available data, may be
`used. Information gained from clinical experience, or from expert
`opinion regarding the effects of change on future experience (e.g.,
`medical or engineering) may be used.
`
`In the absence of actual experience, an actuary may rely on clear actuarial evidence
`that differences in costs are related to a particular risk characteristic. In demonstrating
`this, the actuary may rely on clinical experience or expert opinion. For example, an
`environmental that which has been demonstrated by clinical experience
`to be related to additional deaths may be used until further actual
`experience becomes available.
`
`Sometimes it is appropriate for the actuary to make inferences without specific
`demonstration. For example, it would not be necessary to demonstrate that
`persons with seriously impaired, uncorrected vision would represent a
`high risk as operators of motor vehicles.”
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`Ex. 2020 at Attachment pp.3-4 (emphasis added).
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`9. Mr. Miller also opines that it is not required that actuarial classes are
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`used to meet the statutory standard of charging premiums that are “not unfairly
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`discriminatory.” Ex. 2011 ¶¶ 27-29. While it is true that the statute does not
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`prescribe the means by which the law must be complied with, the utilization of
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`actuarial classes is and has been the accepted means for such compliance. And,
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`notably, Mr. Miller gives no alternative examples (or any examples of an approved
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`policy that did not employ actuarial classes).
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`10. At paragraph 18, Mr. Miller states:
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`The future insurance loss (i.e., risk of loss) being estimated is the product
`of the probability of an occurrence of an insured claim times the likely
`cost of the claim. Because the probability of an insurance claim
`occurring is a different value than the probability of an auto accident
`occurring, auto insurance rates are typically calculated based on the
`likelihood of claim occurrence, not the likelihood of accident
`occurrence.
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`11. Mr. Miller’s opinion here is muddled. Accurately stated, estimated future
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`insurance loss costs are based on the expected pure premium, which is equal to the
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`product of the expected claim frequency and the expected claim severity. The further
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`opinion by Mr. Miller that an accident does not necessarily generate a one-to-one
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`relationship to claims is not relevant to the concept of expected loss costs or expected
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`pure premium as long as a consistent measure is utilized.
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`12.
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`For example, accident statistics, like any other risk characteristic that is
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`or can be used to create an actuarial class (such as age, mileage, sudden braking
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`events, or excessive speeding), does not necessarily have a one-to-one relationship to
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`claims. Yet accident statistics can indeed in themselves be the basis for an actuarial
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`class—see, e.g., ‘970 patent (Ex. 1001) at 1:28-43 (number of at-fault accidents)—just
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`as, for example, the ‘970 points out that “number of sudden braking situations” can
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`be an actuarial class at 4:30-45. It is the job of an actuary to determine how risk
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`characteristics, such as number of accidents or sudden braking events, correlate to
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`predicted future insurance losses so that an insurer can charge an individual the
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`proper premium. This can be done—as explained, for example, in Standard of
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`Practice No. 12—using “actual experience” (actual frequency and severity claims data)
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`or “any reliable source, including statistical or other mathematical analysis of available
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`data” (Ex. 2020 at Attachment pp.3-4 (emphasis added)).
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`13.
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`Importantly, I further note that Mr. Miller’s entire discussion of the
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`necessity of collecting and applying actual claims data (see Ex. 2011 ¶¶ 16-18, 34-35,
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`45) is wholly lacking from the ‘970 patent. Nowhere does the ‘970 patent explain how
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`or where to obtain claims data, much less how to use such data to calculate overall
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`claims losses, pure premiums, expected loss costs, etc. Rather, those techniques are
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`left up to the knowledge of a POSITA, such as myself. While Mr. Miller repeatedly
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`states that the prior art references involved are lacking such discussions, so is the ‘970
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`patent, but nevertheless, it does not mean that a POSITA would simply not possess
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`such knowledge.3
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`3 Although I have not addressed certain of Mr. Miller’s arguments in his declaration
`here, that does not mean I agree with them. Rather, I understand some of Mr.
`Miller’s assertions about, for example, certain terminology (e.g., “risk factor” or “rate
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`8
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`14. Mr. Miller states that the unit of exposure for automobile insurance is
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`the insured vehicle and further states that “[p]remiums for auto insurance are typically
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`not calculated or quoted on a per person or per driver basis.” Ex. 2011 ¶ 21. Mr.
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`Miller’s statement is again muddled and incomplete. Premiums are generally quoted
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`on a policy basis. It is generally the risk characteristics of the insured driver that are
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`applied (using actuarial classes) to the base premiums by coverage or car to determine
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`the premium.4 For liability coverages, the specific car driven is not part of the rating
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`process because the premium is determined using actuarial classes based on only the
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`driver’s risk characteristics and the base premium for the selected coverage. See Ex. ‘970
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`Patent at 1:28-2:12. For physical damage coverages, the premium is determined using
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`actuarial classes based on the driver’s risk characteristics and the base premium by
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`coverage for the specific insured vehicle. See id.
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`15. Again, I also note that Mr. Miller’s opinions about any alleged issues
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`arising regarding the “per driver” versus “per vehicle” distinction are completely
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`lacking from the ‘970 patent. Thus, even if Mr. Miller’s opinions were accurate, he
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`factor”) do not appear pertinent in this proceeding involving the ‘970 patent.
`4 Even Mr. Miller appears to contradict himself on this argument when defining “pure
`premium”: “The numerical value is a ratio of the expected loss of one actuarial class
`to another. The expected loss for an insured is sometimes called the ‘pure premium.’”
`Ex. 2010 ¶ 19. Here he has defined it in terms of the insured (driver) rather than the
`vehicle. Progressive also misstates my views on the definition of “pure premium”:
`“Ms. O’Neil referred to ‘pure premium,’ which has the same meaning as expected
`losses.” Opp. at 11 n.2. Rather, “pure premium” is the loss dollars per unit of
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`relies exclusively on the knowledge of a POSITA—the same knowledge that the
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`POSITA would have when reading any of the prior art references Mr. Miller criticizes.
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`16. Mr. Miller also attempts to utilize the muddled distinction he has created
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`between drivers and vehicles to conclude that insureds are not “assigned” to actuarial
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`classes, stating as follows:
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`In the case of auto insurance, it is not an insured person that is being
`“assigned” to an actuarial class of similar risks. It is the premium
`charged, and any future claim losses, associated with the insured car that
`are coded to an actuarial class for each of the risk characteristics used in
`determining the premium for the insured car.
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`Ex. 2011 ¶ 30.
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`17. This is incorrect and cannot be concluded from his former muddled
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`point about driver versus vehicle. In fact, insurance policies typically identify the
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`assigned classification of the driver for rating purposes. Similarly, distinct aspects of the
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`vehicle’s classification are identified. The final premium is determined by a rating
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`algorithm combining the driver, vehicle, and selected coverages. The resulting insurer
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`premium and claim experience for a particular classification consists of the premium
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`and claim amounts for all drivers combined who have been assigned to that
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`classification.
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`exposure.
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`18.
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`In an attempt to further his argument about driver versus vehicle, Mr.
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`Miller provides an incorrect example to illustrate his contention that insured cars, not
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`drivers, are the basis for classification analysis:
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`For example, assume the premium for an insured car is determined
`based on only three risk characteristics: the rated-driver of the insured
`car is an adult driver, the coverage is subject to a $500 deductible, and
`the insured is eligible for a claims-free discount. The insurer’s
`policyholder records for this insured car will reflect a separate code for
`each of the three risk characteristics (i.e., adult driver, $500 deductible,
`and claims-free). When analyzing the difference in risk between adult
`drivers and youthful drivers, the premium and claims data of our
`hypothetical insured car will be included with the adult risk class. When
`analyzing the difference in risk between a $500 deductible and a $250
`deductible, the premium and claims data of our hypothetical insured car
`will be included with the $500 deductible risk class. When analyzing the
`difference in risk between insureds that are claims-free and those that are
`not, the premium and claims data of our hypothetical insured car will be
`included with the claims-free risk class.
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`Ex. 2011 ¶ 31.
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`19. Mr. Miller’s example is incomplete and incorrect. The driver in Mr.
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`Miller’s example would have been assigned a classification of adult driver. The base
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`rate for the physical damage coverage for the vehicle would be modified for a $500
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`deductible (if some other deductible amount was reflected in the base rate). The final
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`rate would be modified by a claims free discount. The comparison of premium and
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`claim experience of adult and youthful drivers would be a comparison of data for the
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`adult and youthful classifications based on their risk characteristics. For the deductible
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`option, the comparison of premium and claim data would be a comparison of the
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`data for the $500 and $250 classification options. Finally, the claim-free discount
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`would compare the premium and claim data for classifications with the discount and
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`without the discount. In each of these rate making analyses, the claim data would be
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`collected for each resulting exposure, or the pure premium. This analysis remains
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`consistent with the initial assignment of drivers to rating classifications in order to
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`determine the policy premium.
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`20. Mr. Miller argues that obtaining “household” data is necessary to rate an
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`insurance policy:
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`The “rated-driver” is the specific driver among multiple drivers in the
`household, whose risk characteristics impact on the premium calculation
`for a specific insured auto. . . . The premium is calculated to reflect the
`total insured risk associated with the ownership and operation of a
`vehicle that potentially has multiple operators. The insureds under a
`personal auto insurance policy are the named insured(s) listed on the
`policy’s declaration page, as well as all relatives resident in the household.
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`* * * *
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`[A] POSITA would have understood that to accurately determine an
`auto insurance premium, the risk characteristics of all drivers resident in
`the household are needed. These data are necessary so that the insurer
`can determine which of the operators in the household should be the
`“rated-driver” on each insured car in the household.
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`Ex. 2011 ¶¶ 22-24, 42.
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`21. Mr. Miller is incorrect. There is no requirement that household data be
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`collected because, for example, the insurer’s rating algorithm can be applied even if
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`only one driver participates in the monitoring. Also, an individual driver can get a
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`policy on a single car for himself only, so there is no requirement that an insurer get
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`information on multiple drivers or “household” data.
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`22. This household “requirement” argued by Mr. Miller is yet another point
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`that is not discussed in the ‘970 patent. So, again, even if Mr. Miller’s opinions were
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`correct, his exclusive reliance on the knowledge of a POSITA (rather than any ‘970
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`disclosures) is the same knowledge the POSITA would have in analyzing the prior art
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`references.
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`B. Mr. Miller’s Opinions and Progressive’s Assertions Regarding
`Herrod’s Actuarial Classes
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`23. Mr. Miller appears to make two arguments relating to Herrod: (1) his
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`assertion that the use of the Herrod monitored data is only for demonstrating driving
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`competence, rather than broader insurance purposes and (2) his assertion that the
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`Herrod disclosure cannot be used for actuarial classes. These two arguments are
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`intertwined. And Mr. Miller’s opinions regarding both are muddled, incomplete, and
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`incorrect.
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`1. Herrod’s Applicability to Insurance Purposes
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`24. Regarding point (1) about demonstrating driving competence, Mr. Miller
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`states:
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`“Herrod states that the data pertaining to each operator’s driving habits
`could be used by “safe drivers” to “demonstrate their competence to
`insurance companies.” . . . A POSITA would have been aware that in
`1996 insurance companies did not require drivers to demonstrate their
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`“driving competence” and, as such, a POSITA would likely not have
`considered Herrod to have any meaningful application or value to the
`field of determining insurance premiums. At most, a POSITA may have
`understood that the reference in Herrod to a “demonstration of
`competence” meant that the data could have been used by an insurer to
`determine a driver’s eligibility to be offered insurance coverage.
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`Ex. 2011 ¶ 41.
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`25. While Mr. Miller attempts to unnecessarily narrow Herrod’s disclosures
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`based on the phrase “safe drivers would be able to demonstrate their competence to
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`insurance companies,” a POSITA would not have dismissed Herrod on that basis.5
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`The repeated reference in Herrod to use the system for insurance purposes already
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`indicates several things to the knowledgeable POSITA. Ex. 1007 at 1 (“This
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`[monitored driving data] information could be of use to vehicle owners and
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`insurers.”), 2 (“The database [containing the monitored driving data] might also be
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`used by . . . insurance companies, who wish to monitor the standard of driving of
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`certain vehicles.”). For instance, any means of determining expected loss costs would
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`be of interest to a POSITA. Herrod teaches monitoring and gathering acceleration
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`data and accident statistics to group drivers in “behavioural groups” reflecting
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`5 In fact, the ‘970 patent makes a virtually identical statement about using the alleged
`invention to prove driving competence: “[s]uch data measurement will allow the
`vehicle user to . . . operat[e] the vehicle in a manner which he/she will know will
`evidence superior safety of operation and a minimal risk… of an insurance claim.”
`EX1001 at 6:24-30. I also note that Mr. Miller’s comment about the lack of an
`affirmative requirement to “demonstrate competence” at the time (as interpreted by
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`different levels of accident risk. A POSITA would know that, in order to create such
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`behavioural groups relevant to insurance rating—which a POSITA would interpret as
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`actuarial classes—would involve analyzing the data collected in Herrod to determine
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`any associated expected loss costs with such data.
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`26. Mr. Miller also narrowly reads Herrod to suggest that the use of data to
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`display “driving competence” in Herrod is simply for “an insurer to determine a
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`driver’s eligibility to be offered insurance coverage”—i.e., underwriting. Ex. 2011
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`¶ 41. However, Mr. Miller’s reference to the use of the Herrod data for underwriting
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`is redundant of the individual drivers’ accident and violation history, which any
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`insurer would already collect and utilize for underwriting (although these data may
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`also be utilized as part of the overall underwriting profile).
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`27. A POSITA would further know how to calculate/estimate such
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`expected loss costs associated with the monitored data. For instance, as I explained
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`above, a POSITA would know that generating actuarial classes based on expected
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`future losses can be developed based on the actual historical claims data of the insured
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`vehicles or can be based on any other reliable data aside from the actual claims data.
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`See, e.g., Ex. 2020 at Attachment (Standard of Practice No. 12) pp.3-4. Actual claims
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`data need not be used, despite Mr. Miller’s arguments to the contrary. Id.6
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`Mr. Miller) does not mean an insurer would have rejected such information.
`6 Mr. Miller could not reasonably be suggesting that somehow the in-vehicle device
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`28.
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`First, in the absence of claims data, a POSITA would know that the
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`actuarial class could initially be established on a theoretical basis using estimated data.
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`In that case, actual claims data is not used, but an estimate of claims data might be
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`used instead. For example, when I did consulting for the New Jersey Market
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`Transition Facility (NJMTF) around 1994, I helped develop an actuarial class system
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`using driving record points on a driver’s license (i.e., for speeding, moving violations,
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`etc.) as the pertinent risk characteristic. Because this was a new risk characteristic, the
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`NJMTF had no actual loss experience data. Nevertheless, we performed actuarial
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`analyses on estimated data in order to determine the amount that the DMV (Division
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`of Motor Vehicles) surcharges should be based on driving record points.
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`29.
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`Second, even if actual claims data were to be used in Herrod’s system, a
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`POSITA would know that such data would be collected by the insurer—by any
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`conventional means—to implement the usage-based insurance system of Herrod.
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`Certainly the ‘970 patent does not disclose or suggest any novel method of collecting
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`actual claims data. A POSITA would already know how and where to collect such
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`data when reading Herrod, just as the applicants for the ‘970 patent assumed the
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`must be used to collect claims data or that there is some other novel way collecting
`actual claims data in the ‘970 patent. Indeed, the ‘970 patent itself does not even
`discuss how or where to collect claims data—likely because collecting claims data for
`insureds is standard practice for insurance companies.
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`POSITA would know when reading the ‘970 patent’s specification (which does not
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`describe how to do this).
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`2. Herrod’s Disclosure of Actuarial Classes
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`30. Regarding Mr. Miller’s assertion that a POSITA would not understand
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`Herrod to disclose actuarial classes, he states:
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`Neither this statement [about driver competence] nor any other part of
`Herrod’s disclosure would have suggested to a POSITA that the data
`generated by the monitoring device of this patent application had any
`relevance to, or application in, the creation of actuarial classes or the use
`in the determination of auto insurance premiums. A POSITA would
`have had little or no interest in Herrod, since it was directed principally
`to the electronic equipment.
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`Ex. 2011 ¶ 41.
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`31. These statements are not supported. Herrod clearly was not directed
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`principally to electronic equipment, but rather to the applications that may arise from
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`the use of that equipment. Indeed, as I mentioned above, Herrod explicitly and
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`repeatedly explains how his invention was pertinent for insurance purposes. Ex. 1007
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`at 1-2. Herrod mentions several suggested applications of the data derived from
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`monitoring, including direct driver feedback, measurement of accident risk, and driver
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`classification (into actuarial classes) based on monitored data. A POSITA would
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`recognize that the data collected using the Herrod device is used to define actuarial
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`classes (“behavioural groups”) based on measured accident risk arising from observed
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`driving acceleration patterns.
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`32.
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`In addition to the strict requirement Mr. Miller asserts regarding actual
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`“claims loss data” discussed above, he further points to additional requirements for
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`determining the policy premium based on actuarial classes which might be derived
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`from Herrod monitored data, which he argues are missing from Herrod.7 For
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`example, Mr. Miller adds a “household” data requirement, which he argues Herrod
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`does not disclose because the device records data for specific drivers:
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`However, a POSITA would have understood that to accurately
`determine an auto insurance premium, the risk characteristics of all
`drivers resident in the household are needed. These data are necessary so
`that the insurer can determine which of the operators in the household
`should be the “rated driver” on each insured car in the household.
`Herrod does not disclose that all of the drivers in the household would
`have cards, and there is no suggestion that they would.
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`Ex. 2011 ¶ 42.
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`33.
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`First, I already explained above the flaws in Mr. Miller’s assertion about
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`household data. See supra ¶¶ 20-22. Second, even to the extent these data were
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`required, Mr. Miller’s statement that all drivers in the household would not be
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`measured is contrary to Herrod’s disclosure. Mr. Miller is wrong in asserting that
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`“Herrod does not disclose that all of the drivers in the household would have cards.”
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`Instead, Herrod discusses providing a programmable monitoring card to “any driver”
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`of “any equipped vehicle”: “any driver with a suitable card or disk can be monitored
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`7 Conspicuously, not once does Mr. Miller cite the ‘970 specification or claims to
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`whilst driving any equipped vehicle.” Ex. 1007 at 2. Finally, as I also mentioned
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`above, nowhere does the ‘970 patent mention any requirement that “household” data
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`be collected before any insured can be assigned to an actuarial class.
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`34. Mr. Miller also adds a requirement relating to “homogeneity” to further
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`argue that actuarial classes are not disclosed in Herrod:
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`A POSITA would have understood that the “behavioral groups”
`disclosed in Herrod could not be actuarial classes. First, the Herrod
`behavioral groups data is incomplete and would fail the actuarial
`standard for homogeneity. Two persons using the Herrod device may
`have identical acceleration/retardation data, yet have significantly
`different insurance risk (e.g., one person driving in a congested urban
`area, another driving in a rural area). Because of this, a POSITA would
`understand that two drivers could be slotted in the same behavioral
`group by Herrod even though they would likely represent significantly
`different degrees of insurance risk (i.e., risk of loss). As such, the Herrod
`data would have been of no use to a POSITA in the establishment of
`new actuarial classes.
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`Ex. 2011 ¶ 43.
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`35. Mr. Miller’s discussion and example to suggest lack of homogeneity (due
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`to the lack of monitoring location data—i.e., urban versus rural) is misleading and
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`incomplete. The Herrod data provide certain data as mea