Presentation on the integration of predictive analytics in assumption setting (2014 SOA Annual Meeting, Orlando)

1. © 2014 Oliver Wyman
Guillaume Briere-Giroux, FSA, MAAA, CFA
Integrating Predictive Analytics in Assumption Setting Implementation and Integration in Financial Models
2014 SOA Annual Meeting & Exhibit
Orlando – October 27, 2014

2. © 2014 Oliver Wyman
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Agenda
I.How and where predictive analytics impact assumption setting?
II.Implications for assumption setting process
III.Challenges and solutions for financial modeling integration
IV.Key takeaways

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How predictive analytics impact assumption setting?
Business value
Data analytics literacy
Describe / monitor
Analyze / understand
Score / predict
Decide / optimize / manage
Descriptive analytics
(what happened and why?)
Predictive analytics
(what will happen?)
Prescriptive analytics
(what should we do?)
Scope of predictive modeling techniques
Enhanced
experience studies
Enhanced assumption setting
Enhanced model-based
decisions

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Where predictive analytics impact assumption setting? Use of predictive modeling is increasingly widespread for experience studies
Product
Surrenders / Lapses
Utilization / funding pattern
Mortality
Morbidity
VA Living Benefits
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FIA Living Benefits
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Fixed Annuities
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Universal Life
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Term
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Long Term Care
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We are also seeing greater use of predictive analytics in M&A
Source: Oliver Wyman research

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Implications for assumption setting process
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More attention is paid to more secondary internal variables
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Increased opportunities to test external variables
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Additional relationships to study and understand
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More comprehensive ”data-driven” discussions
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Better ability to put experience in context
In summary, using predictive analytics requires more resources dedicated to assumption setting but enables richer thinking around key assumptions

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Example: Integrated GLWB policyholder behavior cohorts
Cohort of GLWB
Observed behavior
“Efficient” users
•Utilize 100% of GLWB maximum income
•Strong utilization “feature skew”
•Low lapse rate
•More efficient dynamic lapses
“Partial” users
•Utilize less than 100% of GLWB maximum income
•Weaker utilization skew
•Higher lapse rate than efficient users
•Less efficient dynamic lapses
“Excess” users
•Utilize more than 100% of GLWB maximum income
•Very high lapse rates
•Least efficient dynamic lapses
“Waiting” users
•Have not yet utilized
•Low lapse rates
•Efficient dynamic lapses
•Waiting for rollup?
This creates four cohorts to model, i.e., a “policyholder behavior scenarios” dimension

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Computational implications for modeling Run time optimization becomes a three dimensional problem
Can specify accuracy functions to determine optimal accuracy for a given run time and generate an efficient frontier

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Other considerations for modeling How granular should the model become?
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Materiality and certainty of dynamic
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Materiality of business
3
Model purpose
4
Degree of buy in
5
Ability to implement and validate

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Model implementation approach There is a compromise between transparency, flexibility, controls and system performance
Desirable property
Parameterized formula
Factor tables
Transparency
Flexibility (model form)
Flexibility (adjustments)
Ease of control
Auditability
Computational performance
High
Low

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Best practices for model implementation
Area of focus
Considerations
Parallel testing
•New assumptions are more complex to code
•Do single cell-testing with replicator (e.g., Excel)
•Excel replicator can also be used for extreme value testing / sensitivity testing
Internal data
•Data definition between experience study and financial models must be consistent
External variables
•Modeler must understand the sensitivity of projected behavior to external variables (how reliable are my scenarios?)
Sensitivity testing
•Understand the potential impact from stress testing the assumption parameters
Documentation
•Documentation of rationale for key modeling decisions and any limitations or simplifications

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Key takeaways
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Think about the business and the environments
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Think about the models and their end goal
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Prioritize and make incremental improvements