SettlementAnalytics is a firm that uses quantitative economic models and game theory to provide litigation analytics and software to corporations involved in high-value legal disputes. Their models aim to address limitations of conventional decision theory approaches, which focus too heavily on trial outcomes and ignore the bilateral complexity of legal disputes. Game theory is better suited as it considers settlement bargaining as a two-person game. SettlementAnalytics has developed fully specified game theoretic models and automated software to extract more insight from litigation analysis while leveraging existing expert systems, with the goal of helping litigants make better settlement and risk assessment decisions.

1. T H E S C I E N C E O F L I T I G A T I O N
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2. Litigation and Settlement Analytics
A Game Theoretic Perspective

3. “To study the strategy of
conflict is to take the view that most
conflict situations are essentially
bargaining situations.”
– Thomas C. Schelling

4. SettlementAnalytics
• SettlementAnalytics™ is a quantitative economic
research firm – focused on litigation & settlement.
• The firm’s economic advisory and software services
draw on proprietary quantitative models of litigation.
• Our models and approach incorporate ideas from
game theory, information economics, financial
analysis and Monte Carlo simulation.
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5. What We Do
• SettlementAnalytics provides legal-economic and
quantitative settlement bargaining analytics to
corporate and institutional litigants involved in high-
value legal disputes.
• The firm also develops proprietary quantitative
litigation and settlement analytics software
applications.
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6. Questions Answered
• SettlementAnalytics uses advanced methods to
obtain quantitative insights into several key
questions relating to legal claim valuation,
settlement optimization and litigation risk.
• Our work addresses three key questions, which can
be described as follows:
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7. Questions Answered
1. The Surplus Division Problem:
 How should the cost savings from settlement
(the “cost surplus”) be optimally distributed
between the disputants?
 What settlement policy, offer or demand results
in an optimization for the plaintiff or defendant?
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8. Questions Answered
2. The Dispute Pricing Problem:
 How should legal claims be valued for the
purpose of management / financial accounting?
 How do legal claims contribute to business
valuations?
 How should disputed insurance claims be
valued?
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9. Questions Answered
3. The Risk Measurement Problem:
 How can lawsuit and insurance claim risk be
quantified and described?
 How can the risk of settlement decisions be
quantified and visualised?
 How to distinguish between trial and claim risk?
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10. The Problem with Convention
• These questions highlight a number of key
problems with conventional methods of analysis of
legal claim valuation and settlement pricing.
• We will briefly review these in turn.
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11. The Problem with Convention
1. Limitations of Decision Theory:
 Conventional analysis leans heavily on “decision
theory” – this is the theory of one-person games
 Decision theory emphasizes a unilateral
perspective of the problem.
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12. The Problem with Convention
1. Limitations of Decision Theory:
 Decision theory – by definition – ignores the
bilateral complexity of legal disputes.
 Using decision theory, litigants and counsel are
forced to focus on trial value instead of the more
important claim value.
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13. The Problem with Convention
2. Qualitative Processes:
 After focusing on the trial outcome, litigants are
then limited to the use of qualitative processes,
heuristics and bargaining intuition to translate
trial expectations into a settlement bargaining
policy.
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14. The Problem with Convention
3. Uncertainty Averaging:
 Traditional approaches to claim valuation and
settlement tend to average over uncertainty.
 This ignores the rational discounting effect of
uncertainty on claim value and settlement
pricing.
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15. The Problem with Convention
4. Failure to Optimize:
 Traditional decision theory methods make no
explicit attempt to solve the settlement
bargaining problem – i.e., to find a rational
optimum settlement decision.
 Decision theory can only frame the solution to
the settlement problem.
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16. The Problem with Convention
5. Oversimplifies the Concept of Trial Value:
 Decision theory pretends that litigants are
exposed to the full weight of trial expectations.
 In reality, litigants do not face trial expectations
generically, but only after a specific settlement
offer has been rejected. They are exposed to
that portion of trial risk that is not “filtered out” by
the settlement bargaining process.
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17. The Problem with Convention
5. Oversimplifies the Concept of Trial Value:
 We introduce the term, “trial wealth residue” to
refer to that portion of the potential trial
outcomes that survive settlement bargaining.
 Only game theoretic models of litigation can
articulate this measure of trial value because it
turns on the bilateral nature of the dispute.
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18. The Problem with Convention
6. “In-Decision” Trees:
 Decision trees are sometimes used in litigation
analysis.
 They can be a useful device to describe various
trial outcomes.
 However …
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19. The Problem with Convention
6. “In-Decision” Trees:
 Decision trees can only probability-weight
discrete trial outcomes.
 They are useful for computing expected values.
 But they cannot model the contingency that is
fundamental to bilateral disputes.
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20. The Problem with Convention
6. “In-Decision” Trees:
 They draw no mathematical connection between
settlement policy and the probability of settlement
 They draw no connection between settlement
policy and its influence on claim value.
 They also oversimplify continuous distributions.
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21. The Problem with Convention
7. Data Mining:
 “Big Data” is increasingly being applied to
commercial problems such as litigation.
 Analysis of historical data can be a valuable
input to the decision-making process.
 However ...
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22. The Problem with Convention
7. Data Mining:
 Historical data must be used with caution.
 Sample biases in the data can cause distortion.
 Important questions must be asked about
statistical significance and confidence intervals.
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23. The Problem with Convention
7. Data Mining:
 Legal claims are often unique. The sample of
historical data that actually fits the present case
may be statistically insignificant. If Big Data
becomes Small Data then it becomes
indistinguishable from anecdote.
 Because settlements are usually private, data
mining is largely biased towards tried cases.
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24. The Problem with Convention
7. Data Mining:
 “The Problem of Induction”: mining historical
data also suffers from the problem of inductive
reasoning. Just because it was so, doesn’t
mean that it will be.
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25. The Problem with Convention
7. Data Mining:
 Finally, the historical record of tried cases will
almost certainly contain the results of some
irrational decisions, or errors. Care must be
taken not to “shadow trade” irrationality (see
below).
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26. The Problem with Convention
8. Complexity Collapse:
 Overall, conventional approaches tend to
“collapse” the real economic complexity
associated with contingent claims.
 In reality, legal claims are much more
mathematically complex. Ignoring this
complexity can be a source error.
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27. The Problem with Convention
9. Qualitative Trial-and-Error:
 After computing trial expected values, traditional
methods seek to optimise outcomes through a
“price discovery” process – one of trial-and-error
offer and counter-offer bargaining.
 This is to use a qualitative process to solve
what is a highly quantitative problem.
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28. The Problem with Convention
• IN SUM: It is ironic that traditional approaches to
the economic analysis of litigation and settlement
emphasize trial expectations when approximately
93% of all lawsuits are resolved before a court
adjudication on the merits.
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29. Litigation Errors
• These problems and the complexity associated with
legal claims can give rise to significant errors in
valuation and settlement decision-making.
• For example, empirical research points to a high
incidence of error in lawsuit settlement decisions.
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30. Litigation Errors
• Four different studies have indicated that among
lawsuits that fail to settle:
 Plaintiffs make errors in approximately 60% of
cases.
 Defendants make errors in approximately 25%
of cases.*
* Link to research references
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31. Litigation Errors
• Data mining these errors might not be conducive
to the optimization of claim value or settlement
decision-making.
• It is likely that these errors are not only confined
to failed settlement situations, but may occur in
all disputes.
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32. Litigation Errors
• Moreover, the same biases and distortions in
settlement bargaining may also be manifest in
other legal-economic aspects of case
management including …
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33. Litigation Errors
 Legal spend decisions
 Discovery decision making
 The economic merit of legal strategies
 Timing of settlement negotiations
 Claim valuation for accounting/M&A purposes
 The sequence of legal procedure
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34. Potential Sources of Errors
• There are five main potential sources of error:
 Bad heuristics
 Psychological biases
 Reputation building behavior
 Irrational attempts at “strategic bargaining”
 Computational complexity
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35. On the Causes of Error
• It is our view that these sources of error have two
main root causes:
 Bargaining and valuation heuristics are poorly
adapted to the economic analysis of complex
contingent claims such as lawsuits.
 Simple decision theory approaches to litigation
analysis are likely overwhelmed by the
mathematical complexity of the problem.
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36. On the Causes of Error
• As a result of these issues, the trial and error
bargaining approach to settlement optimization
can often result in exactly that …
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37. On the Causes of Error
• As a result of these issues, the trial and error
bargaining approach to settlement optimization
can often result in exactly that …
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a trial and an error

38. On the Causes of Error
• As a result of these issues, the trial and error
bargaining approach to settlement optimization
can often result in exactly that …
a trial and an error
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39. A Solution
• Game theoretic methods and other quantitative
approaches can act as a useful check against the
causes of legal-economic decision-making errors.
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40. A Solution
• SettlementAnalytics seeks to address the problems
associated with decision theory methods and
qualitative processes through the application of
proprietary mathematical models and litigation
analytics software applications.
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41. A Solution
• Our approach is distinguished from conventional
methods because it uses game theory in place of
decision theory.
• Game theory is the theoretical discipline of two or
more person games.
• Game theory is more naturally adapted to the
bilateral nature of legal disputes.
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42. Advantages of Game Theory
• There are several advantages to using our game
theoretic framework …
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43. Advantages of Game Theory
 Optimize over the dyad of trial and settlement
 Distinguish between trial value and claim value
 Correctly discount for uncertainty in expectations
 Provide a contingent expression of trial risk
 Better reflect the complexity of contingent claims
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44. In Short
• The real economics of litigation and settlement are
inordinately complex when fully considered.
• The decision theory / trial expectations framework is
incapable of factoring this complexity.
• Game theoretic methods are more appropriate to
the problem.
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45. But …
45

46. But …
Is Complicated
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47. It’s Complicated
• There are several obstacles to exploring the full
economic and mathematical complexity of legal
claims using game theory …
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48. It’s Complicated
• Game theoretic models are more complex than their
decision theory counterparts.
• Most game theoretic models of litigation have
remained strictly theoretical and are incompletely
specified for practical application.
• Game theoretic models involve several assumptions
in order to be theoretically valid.
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49. Curing Complexity
• Research and development at SettlementAnalytics
has for the first time made game theoretic models of
litigation and settlement both “production ready” and
easy to use.
• Over the past several years we have …
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50. Curing Complexity
• Developed fully-specified game theoretic models of
litigation to incorporate real-world complexity,
including:
 Costs of capital
 Term to trial
 Contingent fee structures
 Hybrid fee structures
 Cost indemnification
 Risk aversion
 Sunk cost considerations
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51. Curing Complexity
• Incorporated over 50 different economic dimensions
of litigation & settlement – allowing us to analytically
describe virtually any legal conflict.
• Fully automated the application of our models by
developing a proprietary software application
called “OptiSettle™”
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52. Curing Complexity
• Simplified the economic inputs so that informational
encoding of any legal dispute is very similar to a
client’s existing analytic process.
• And our models can be as equally applied to
disputed insurance claims as they can to legal
disputes.
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53. Leveraging Expert Systems
• The following needs to be emphasized:
 The processes, models and software developed
by SettlementAnalytics are designed to leverage
existing expert systems, not replace them.
 SettlementAnalytics does not provide legal or
financial advice.
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54. Leveraging Expert Systems
• In this way, our work serves to extract greater
analytic insight from existing corporate expert
systems.
• We do not replace lawyering, litigation analysis,
settlement bargaining or negotiation, but rather we
provide quantitative analytic support and software to
assist these functions.
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55. Economic DNA of Litigation
• Overall, our approach demonstrates that there is an
“economic DNA” to legal disputes that is only
revealed using game theoretic methods.
• This DNA is a function of uncertainty, the bilateral
character of dispute and the contingent nature of
legal claims.
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56. Economic DNA of Litigation
• These are the economic building blocks of legal
conflict.
• They are all formative to claim valuation, settlement
pricing and litigation risk – and yet they are all
largely ignored in the conventional trial
expectations / decision theoretic model of
litigation.
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57. Economic DNA of Litigation
• At SettlementAnalytics we help corporate and
institutional litigants better explore these
fundamental economic drivers of their legal claims
and legal claim portfolios.
• Our software includes powerful visualization tools
that vividly illustrate these issues.
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58. … so armed, we believe litigants
can make better litigation and
settlement decisions.
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59. For More Information
• To learn more about our analytic models, please
click here.
• To learn more about our analytic processes,
please click here.
• To learn more about OptiSettle™, please
click here.
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60. Contact Information
Info@SettlementAnalytics.com
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61. The Science of Litigation™
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62. Copyright 2014 SettlementAnalytics
T H E S C I E N C E O F L I T I G A T I O N
™