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Session 26 PD, Getting Ready for ORSA

Moderator: Nancy E. Bennett, FSA, CERA, MAAA

Presenters:

Nancy E. Bennett, FSA, CERA, MAAA James Russell Collingwood, ASA, MAAA

Casey Edward Malone, FSA, CERA, MAAA

Copyright © 2014 by the American Academy of Actuaries. All Rights Reserved.

Getting Ready for ORSA Valuation Actuary Symposium Session 26PD

August 25, 2014

Nancy Bennett, MAAA, FSA, CERASenior Life Fellow

American Academy of Actuaries

Copyright © 2014 by the American Academy of Actuaries. All Rights Reserved. 2

Agenda

US Regulatory Developments

Overview of US ORSA Requirements (Own Risk Solvency Assessment)

NAIC Field Test Results

New Regulatory Focus: Stress Testing


US ORSA Regulatory Developments

ORSA is intended To foster an effective level of ERM at all insurers (the identification,

assessment, monitoring and reporting on its material and relevant risks, using techniques that are appropriate to the nature, scale and complexity of the insurer’s risks, in a manner that is adequate to support risk and capital decisions; and

To provide a group-level perspective on risk and capital, as a supplement to the existing legal entity view.

RMORSA Model Law (adopted by NAIC in September 2012; adopted in 18 states)

ORSA Guidance Manual (adopted by NAIC in March 2012; current revision - July 2014)

Financial Examiner’s Handbook – exposure closed July 14, 2014 Financial Analysis Handbook – exposure closed July 14, 2014 ORSA Pilot Project (2012, 2013, 2014)


NAIC working groups involved with implementing risk management regulations: ORSA Subgroups (“E” Committee and the Casualty Actuarial Subgroup) Stress Testing Subgroup of the Life Risk-Based Capital Working Group Corporate Governance Working Group Group Solvency Issues Working Group

Holding Company Act Group Supervision Supervisory Colleges for internationally active groups Group Reporting

Regulators outside of US are influencing US insurance regulatory structure more than ever Insurance regulators: IAIS, EIOPA Bank regulators: Federal Reserve, FSOC, Basel FSB (the Financial Stability Board)

US ORSA Regulatory Developments (cont.)


US ORSA Requirements: Scope An insurer and/or the insurance group of which the insurer

is a member will be required to complete an ORSA “at least annually to assess the adequacy of its risk management and current, and likely future, solvency position.”

The ORSA requirement will apply to any individual U.S. insurer that writes more than $500 million of annual direct written and assumed premium, and/or insurance groups that collectively write more than $1 billion of annual direct written and assumed premium

January 1, 2015 effective date Part of state accreditation standards


US ORSA requirements: Contents

Section 1: Description of the insurer's risk management framework Risk culture and governance Risk identification and prioritization Risk appetite, tolerances and limits Risk management and controls Risk reporting and communication

Section 2: Insurer's assessment of risk exposures Quantitative and/or qualitative assessments of risks in normal

and stressed environments (likely an important ORSA section!) Risk mitigation activities and plausible outcomes


US ORSA requirements: Contents

Section 3: Group risk capital and prospective solvency assessment Description of insurer’s risk and capital management processes to

help determine the financial resources over a business cycle (e.g., 1-3 years)

Description of methodologies, assumptions, and considerations used in quantifying available capital and risk capital dividend policy leverage, fungibility of capital contagion risk, concentration risk and complexity risk liquidity risk and calls on the insurer’s cash position

Capital forecast consistent with insurer’s planning time horizon and stated risk appetite

Discussion of prospective risks affecting the capital projections


NAIC ORSA Field Tests

Conducted in 2012, 2013 and 2014 2013 Results (22 companies) reflected regulators’

understanding of company ERM practices. Improvements suggested: Enhance readability of report (e.g., Exec Summary, Table of

Contents, multiple years of data, mapping of legal entity to business units, glossary)

Improve identification of risks (e.g., use heat maps, rankings, IT, intercompany dependencies)

Discuss prospective and emerging risks in addition to prospective capital

Discuss details of risk limits and risk mitigation practices Perform combined stress scenarios in addition to single stress

scenarios


NAIC ORSA Field Tests (cont.)

Need more discussion of company’s capital requirements, including calculation basis, model validation and group capital considerations (US and international)

Provide more stress testing of liquidity (not just capital) Describe risk governance in more detail (e.g., risk owners,

risk oversight, impact on compensation) NAIC Report on the Pilot Studies:

http://naic.org/documents/committees_e_orsa_wg_related_docs_pilot_feedback.pdf


ORSA Section 2 requests stress testing information Stress testing is intuitive and resonates with non-technical

audiences. Illustrates those risks of concern to a particular institution or

indicative of a macro trend to regulators (e.g., emerging or systemic risk)

Bank and insurance regulators (US and international) have added stress testing to better regulate the financial sector: Federal Reserve: CCAR (Comprehensive Capital Analysis & Review) Dodd-Frank Act: mid-cycle stress testing (“DFAST”) EIOPA Stress Tests Solvency II (Pillar II)

The NAIC is considering more stress testing, in addition to ORSA: LRBC stress testing of the total asset requirement (TAR) PBR for fixed annuities (VM-22)

New Regulatory Focus: Stress Testing


Types of Stress Testing

Terminology confusion: stress vs. scenario testing Macro stresses/scenarios – affect all companies

Historical scenario (e.g., Japanese interest rates, 1918 influenza) Future scenario (e.g., 30% drop in equity markets)

Micro stresses/scenarios – specific to one company’s risk profile Specific stress (e.g., tax ruling, lawsuit) Normal variability of claims, lapses, expenses, etc. Worst case variability (e.g., 3+ standard deviations, 1 in 200

event)

Reverse stress testing (i.e., how far to breach risk appetite?)


Evaluating Stress Tests

What metric? Earnings, capital, liquidity, other? Forward looking, part of risk appetite statement Forward looking, consistent with business planning cycle and

corporate objectives

Uses of stress tests Determine a number (e.g., economic capital) Illustrate impact of extreme events Illustrate impact of risk mitigation


Evaluating Stress Tests (cont.)

Challenges How many stress tests to run? Single risk or multi risks? Single period or multi period? Historical or future looking? Risk correlation? Modeling issues – run time, assumptions, validation of model Over-reliance on models; disbelief in models Focus: solving the past crisis vs. mitigating a future crisis

A major area of actuarial research in coming years


ORSA: a company’s OWN assessment of its risks and risk management practices

Regulators’ expectations for report contents will likely increase over time Current US regulatory posture is non-prescriptive, principle-based How regulators will use its ORSA assessment in regulating

insurers is unclear Whether or not regulators have sufficient resources to evaluate

ORSAs is unclear

An insurer’s expectation for ORSA should be established by company management An opportunity for insurers and ERM practitioners Should be more than a regulatory exercise Can be leveraged to move ERM forward

Understand those risks posing greatest threat to firm’s vision Help firm navigate risks to achieve its vision


For More Information

Nancy Bennett, Senior Life Fellow

American Academy of Actuaries

1850 M Street, NW Suite 300

Washington, DC 20036

202-223-8196

[email protected]

Getting (Your Models) Ready for ORSA

Casey E. Malone FSA, MAAA, CERA

SOA Valuation Actuary SymposiumAugust 25, 2014

17

Modeling Needs for Quantitative ERM

Solvency cannot be assessed without advanced modeling techniques. The ORSA manual suggests stress testing and stochastic

analyses.– The manual defines stress testing as, “A type of scenario analysis in

which the change in parameters is considered significantly adverse or even extreme.”

– And stochastic analysis as, “a methodology designed to attribute a probability distribution to a range of possible outcomes.

In most cases, both stress testing and stochastic analysis will be necessary.

18

What is Solvency?

The ORSA guidance manual defines solvency as, “for a given accounting basis, the state where, and extent to which, assets exceed liabilities.” Most companies have at least some stochastic liability

calculations for both Stat and GAAP/IFRS Thus, solvency can not be assessed without stochastic analysis. Models must be able to project future stochastic balances, so

they must become more sophisticated and computationally demanding.

19

Stress Testing with Stochastic Liabilities

The stress testing of stochastic liabilities can alternatively be described as a stochastic on deterministic projection. The modeling is highly dependent on the time horizon. From the guidance manual:

– “Solvency assessment should demonstrate [that a company] has the financial resources necessary to execute its multi-year business plan in accordance with its stated risk appetite.”

A short time horizon does not fit the life insurance industry.

20

Modeling Approach to Stress Testing

Models must have some sort of mechanism to launch stochastic scenarios starting from future points in time. Two main approaches:

– Nest the calculation in a separate loop inside the model.• More efficient, fewer steps, less room for human error• Nested calculations can be a black box.

– Age the inforce file to future points in time, reset the model parameters to the future states and run the model.• More auditable and transparent• Less efficient with more room for human error

In either case, validation is very important.

21

Can Stress Testing be Sufficient?

Stress testing can have its advantages:– Easy to explain and understand– Less computationally demanding

But it has very significant weaknesses:– Stress scenarios only reflect (and reinforce) management’s current

views of risk.– Testing historical crises will not prepare you for tomorrow’s crisis.– All in all, stress testing can provide a bit of intuition, but it paints a

very incomplete picture.

22

Multi-Year Stochastic on Stochastic Analysis

Up to now, I have tried to make the points that:– A long time horizon is necessary– Stress testing alone is insufficient– Stochastic liability calculations are necessary for solvency

assessment.

Given that, the only method to robustly capture risk and analyze solvency is with multi-year, stochastic on stochastic analysis. The only problem…

23

It’s Computationally Impossible!

The scale of the computational shortfall is on the order of between 10,000:1 and 100,000:1. Computers and software cannot keep up. If we use Moore’s law (i.e. computing power doubles every 2

years), we’ll need to wait 30 years to make up for the shortfall. Luckily, we have options.

24

Proxy Modeling

The guidance manual definition of stochastic analysis goes on to say, “May use closed form solutions, or large numbers of scenarios in order to reflect the shape of the distribution.” Closed form solutions require trivial computing power to

calculate. However, unless we’re only selling plain vanilla derivatives,

where do we get closed form solutions? The answer comes from an idea called proxy modeling. A proxy

is a stand-in, and a proxy model is a stand-in for your model.

25

Proxy Modeling Methods

Replicating Portfolios – represent the liabilities as a portfolio of assets, which themselves have closed form solutions.– Very difficult to calibrate, obtaining poor fit– Impossible to model insurance or policyholder behavior risk ->

oversimplifies the liability

Curve fitting – generate a limited number of data points (similar to stress testing) and fit a curve to the result.– Impossible to generate a complete set of calibration scenarios– Poor fit in the blind spots between calibration points

Least Squares Monte Carlo (LSMC)– Method originally derived for pricing of American options– Leads to robust estimates of the stochastic measure in question

26

Least Squares Monte Carlo (LSMC) Theory

Nested Stochastic LSMC

Least Squares

Regression

27

Least Squares Monte Carlo (LSMC) Theory

Monte Carlo simulation to generate data to be fed in Least Squares regression. The number of data points for the regression equals the number

of outer loop scenarios The number of inner loop scenarios drives the quality of each

observation on its own. The desired result is Y = f(x1, x2, …, xn) where:

• Y = our target stochastic calculation (e.g. reserves, capital, hedging target)

• X = set of n risk drivers

28

Scenario Generation - Sobol Sequence

• The Sobol sequence effectively fills a hypercube allowing fast convergence to an analytical mean.

• Every point contributes valuable information in each dimension, meaning more risk drivers can be modeled with fewer scenarios.

29

Legendre Polynomials

Ordinary Polynomials Legendre Polynomials

30

Nested stochastic projection

Polynomials for future time points can be calibrated from a single set of time zero scenarios. – 10,000 outer loops, each with10 inner loops at time 0.– Becomes 100,000 outer loops, each with 1 inner loop at future time

points.

Real world is more difficult. – It requires using rebasing (e.g. scenario decomposition) to estimate

a scenarios characteristics, or separate scenario sets for future points in time.

Polynomials are functions of macro risk drivers and inforce characteristics at future points in time.

31

Validation and Implementation of Proxies

Validation is of paramount importance.– Plot function sensitivities to risk drivers to confirm that relationships

are intuitive and/or explainable.– Perform brute force validation under a limited number of

deterministic scenarios, i.e. use stress testing to validate the proxy modeling.

Implementation– Closed form solutions, even many term, high order polynomials are

easily handled by actuarial models with trivial runtime.– The formula is assessed when called in a model as a function of the

risk drivers at that point in time.

32

Conclusions

A quantitative framework for ORSA requires more sophisticated and computationally demanding modeling than companies are generally doing today. For most companies, multi-year nested stochastic on stochastic

calculations will be necessary. This is computationally impossible, so closed form proxy models

will be necessary. Advanced proxy modeling techniques such as LSMC will be able

to get companies on the right track to a robust and meaningful ORSA.

26 PD — Getting ready for ORSA2014 Valuation Actuary SymposiumJames Collingwood, ASA, MAAA

25 August 2014

Disclaimer

► This material has been prepared for general informational purposes only and is not intended to be relied upon as accounting, tax, or other professional advice. Please refer to your advisors for specific advice.

► The views expressed by the presenter are not necessarily those of Ernst & Young LLP.

Agenda

► Guiding principles for ORSA readiness

► Assessing readiness for ORSA

► Addressing gaps in ORSA readiness

► Role of the actuary

► Value of an ERM assessment

Guiding principles for ORSA readiness

► Own Risk and Solvency Assessment (ORSA) should not be underestimated.

► Future requirements are likely to be more complex and robust.

► Enterprise risk management (ERM) assessments are a valuable first step to prepare for ORSA.

Assessing readiness for ORSAComparison points and key questions

► Comparison of the insurer’s ERM framework against:► US National Association of Insurance Commissioners (NAIC) ORSA requirements► Insurer’s desired ERM maturity► Other related requirements (International Association of Insurance Supervisors

(IAIS) Insurance Core Principles (ICP) 16, Federal Reserve standards, etc.) and industry best practices

► Key questions to consider include:► Does the insurer have a clear understanding of what it wants from an ERM

framework and ORSA?► Does the insurer understand the requirements as stated by the US NAIC ORSA

Guidance Manual?► Are documented risk appetite statements used to inform business decision making?► Is exposure for all types of risks measured in a consistent way?► Can the insurer project future risk capital requirements consistent with its strategic

planning horizon?► Is it possible to create a group-wide capital assessment with a consistent

measureable framework?

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Assessing readiness for ORSAORSA requirements map to an ERM framework

Risk identification • Covers all types of risks• Identifying emerging

risks

Risk assessment and measurement• Single version of truth• Reflects risks presented

Risk monitoring and management• “Industrialized”

production of risk analysis

Risk reporting and management information• Information to drive business decisions• Clear, concise and reflective of current status

Data, IT, infrastructure • Integration of risk and finance systems architecture• Data to be consistent, complete, accurate and auditable

Policies, standards, internal controls, people and culture • Clear ownership of tasks and activities • Consistent policies and standards• Robust internal controls

Overall governance arrangements

• Strategy and risk appetite• Oversight arrangements

Decision and planning support• Technical pricing and value contribution are core inputs to product design• Metrics to identify underperforming portfolios

US ORSA Report Section 1: Description of the Insurer’s Risk

Management Framework

US ORSA Report Section 2:

Insurer’s Assessment of Risk Exposures

US ORSA Report Section 3:

Group Risk Capital and Prospective

Solvency Assessment

Assessing readiness for ORSAApproaches to assessing readiness

► Insurers are assessing their readiness for ORSA in a number of ways, including:► Interviews with key ERM stakeholders across multiple functional

areas (e.g., ERM, Finance/Treasury, Actuarial, Operations, Internal Audit)

► Review of existing ERM framework documentation ► Development of an internal draft of the ORSA summary report

► Important considerations when performing an assessment include:► Use of internal vs. external resources to perform the assessment► Format, content and audience for the results of the assessment

Addressing gaps in ORSA readinessKey considerations

► Development of a consistent view across the organization around the level of ERM maturity desired

► Understanding of timelines► Short-term timeline to prepare for first ORSA summary report► Medium-term timeline to strengthen ERM framework

► Creation of a review process for the ORSA summary report► Identification of stakeholders (e.g., senior management, legal,

board of directors) that will need to review and approve the ORSA summary report

► Consideration of sequence of and timeline for review by each group

Addressing gaps in ORSA readinessDesigning a work plan

► Prioritizing improvement opportunities

► Sequencing improvement opportunities

► Defining key activities for each improvement opportunity

► Developing resourcing estimates

► Assigning roles/responsibilities

Role of the actuary

► Play an active role in the ERM assessment process, providing a clear view of the current state

► Develop work plans to address improvement opportunities related to the quantitative aspects of ERM and ORSA (e.g., stress and scenario-testing capabilities)

► Have a key role in risk quantification efforts for ERM/ORSA, including:► Coordination and performance of the risk exposure quantification

calculations (including the prospective solvency assessment)► Assessment of the suitability of the calculation models,

methodologies and assumptions

Value of an ERM assessment

► Provide a clear understanding of strengths and improvement opportunities for the insurer’s ERM framework

► Allow for the development of prioritized improvement plans

► Identify where improvement opportunities can add value:► Enhancements to the decision-making process► Increased collaboration and engagement of functional areas► Cost savings through increased efficiency (e.g., automation of

manual tasks, reduction in duplicative efforts)

Questions?

For more information

James CollingwoodEYOffice: +1 312 879 6306Mobile: +1 319 331 [email protected]

EY | Assurance | Tax | Transactions | Advisory

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