New Using Analytics to Captive Performance - Hawaii Captive …hawaiicaptives.com/wp-content/uploads/2013/11/Using... · 2013. 11. 13. · Using Analytics to Enhance Captive Performance

Using Analytics to Enhance g yCaptive Performance

David BellExecutive Director, Corporate Risk Management, Kaiser Permanente

Richard FosterManaging Director, Guy Carpenter & Company, LLC

Ellen CharnleyManaging Director, Marsh Captive Solutions

The (potential) questions:

‘’For every complex question there is an answer that is clear simple and wrong!”that is clear, simple, and wrong!

‘’Y t ?”‘’You want answers?”....“I want the truth!”…. “You can't handle the truth!”

“Now that you know that the answer to the Ultimate question of Life, the Universe, and Everything is forty‐two (42), all you need to do now is find out what the Ultimate Question is ”now is find out what the Ultimate Question is.

The (potential) questions

• From whom?


– Owners, stakeholders, regulators, excess insurers, reinsurers, rating agencies….yourselves?

• Why use analytics / models?– Knowledge is power– Understand the limitations

The art and the science of risk management...Balancing

analytical models with intuition and judgment.

The (potential) questions• Are the original objectives still being met and/or still relevant?

• How are we identifying and quantifying our risk(s)?


How are we identifying and quantifying our risk(s)?– Prospective and retrospective (reserves)

• Are retained and ceded limits appropriate?– Should we retain more, or less, risk?

– Is the excess insurance / reinsurance efficient?

– Are we charging / being charged “the right” premium?

• Is their adequate capital to support the risk(s) retained?– What are the probabilities that our capital will prove insufficient (and by how much)?

Wh t i i k t l ?– What is our risk tolerance?

– What is the optimal level of capital held within the captive?

• Should we add some new exposures?– How will this effect our risk profile / appetite?

• Add / reduce volatility ‐ diversify or correlate

Using Analytics to Enhance Captive Performance

C t i d t


Create a process aimed at providing answersproviding answers

Create a process aimed at providing answersCreate a process aimed at providing answers

How much is at risk? What do we want to do

Identify Measure Analyze Manage Monitor

What risks exist? Do something about it Did the management How much is at risk? with the risk?What risks exist? Do something about it strategy work?

• Gather actual loss data• Gather anecdotal facts regarding risk exposureR t ti l l

• Prioritize against other risks

• Create strategies and recommendations for

• Identify known risk events

• Classify risk events• Document contributing

• Implement recommended actions

• Change policies and procedures

• Ensure actions took place• Compare current results with previous results

• Compare current results• Run potential loss models

• Perform scenario analysis

• Benchmark against industry data

recommendations for risk management actions (terminate, treat, tolerate, transfer)

• Get feedback and appropriate approvals f i k d

• Document contributing factors or drivers

• Are the risk core? Do we have a competitive advantage in assuming the risk?Wh t i t’

procedures• Improve internal controls

• Make investments• Sell assets• Acquire hedgesA i ( )i

• Compare current results with expected results

• Generate and distribute reports

from risk owners and oversight committees

• What is management’s and the Board’s tolerance?

• Consider possible impacts

• Acquire (re)insurance• Do nothing

Data Information Action


A l ti l d t d


Analytical products and modelsmodels

GC Analytics Capabilities

• Catastrophe Modelingk ’ f l h


– Property, Workers’ Compensation, Life, Health• Earthquake• Hurricane• Tornado / HailTornado / Hail• Terrorism• Pandemic• Flood• Wildfire• Wildfire• Ad‐hoc

• i‐aXsU d i j ti ith t t h d li il l ti– Used in conjunction with catastrophe modeling easily evaluating accumulation exposure and potential area of high concentration

– Also delivers catastrophe results at client’s fingertips– Risk Profiler – helps in pricing individual risks for catastrophe– Risk Profiler helps in pricing individual risks for catastrophe– Reveal – WC hazard analysis


• MetaRiskd d l b l f b


– Predictive Modeling by line of business– Ability to price excess and (re)insurance contracts– Analyze impact of reinsurance on a line of business or total company– Ability to look at company capital model

• MetaRisk Reserve– A licensable tool used to evaluate the volatility in reservesA licensable tool used to evaluate the volatility in reserves– Ability to analyze loss portfolio transfers and adverse development covers

• Reinsurance Optimization– Algorithm to look at best mix of various treaty options for a company– Reinsurance Decision Tool

• Review key metrics to determine best reinsurance structure by Line of Business or in total

Analytical products and modelsAnalytical products and modelsCatastrophe Models

Correlated Loss

Distributions

60%

80%

100%

Dis

tribu

tio

LOB Loss Models

Probabilistic Cost/Benefit

R i

0%

20%

40%

0 50 100 150 200 250 300 350

Size of Loss

Cum

ulat

ive

D

Motor Engineering Fire

Economic Scenarios/Correlation

Reinsurance Economics

Impact on Financials,Operational,

C di A i k Rating

Economic Capital & Allocations

Credit, Asset risk

Company Financial Allocations

Info

MetaRisk – GC’s modeling platform

Getting to possible answers

Correlated Loss

Getting to possible answers• How are we identifying and quantifying our risk(s)?

Distributions

Probabilistic Cost/Benefit

– Prospective and retrospective (reserves)

• Are retained and ceded limits appropriate?– Should we retain more, or less, risk?Probabilistic Cost/Benefit

Reinsurance Economics

Should we retain more, or less, risk?

– Is the excess insurance / reinsurance efficient?

– Are we charging / being charged “the right” premium?

I th i d t it l t t th i k( ) t i d?

Impact on Financials,Rating

• Is their adequate capital to support the risk(s) retained?– What are the probabilities that our capital will prove insufficient

– What is our risk tolerance?

Economic Capital & Allocations

– What is the optimal level of capital held within the captive?

• Should we add some new exposures?– How will this effect our risk profile / appetite?– How will this effect our risk profile / appetite?

• Add / reduce volatility ‐ diversify or correlate

Getting to possible answersGetting to possible answersRisk tolerance / Capacity ‐ appetite

• Risk Capacity is determined by– Required Economic Capital relative to Available Capital– Ability to raise capital and/or use (re)insurance to utilize (re)insurer

capital– Earnings strength and stability

• Risk Appetite– Amount and type of risk that management and / or the Board are

willing to take given available risk capacity risk preferences and corewilling to take, given available risk capacity, risk preferences and core risk competencies

– Business strategy should be aligned with risk appetite


Managing Solvency Risk


g g yAligning Required Economic Capital with Actual Capital

• Maintain a balance between actual• Maintain a balance between actual capital held by the firm and required economic capital

• In reality firms hold some excess capital b i it labove economic capital– To provide for contingencies– Ensure continuation of existing dividend

policy– Is this appropriate for a captive?

• Therefore “required” economic capital is inclusive of the amount of capital needed to finance the risk on their books plus theto finance the risk on their books plus the buffer





• If required economic capital is more than actual capital– Reduce risk by hedging

• Reinsurance hedges underwriting risk• Derivatives can hedge asset risk• An ADC / LPT could hedge reserve• An ADC / LPT could hedge reserve risk

– Acquire additional capitalHedging





• If actual capital is more than required economic capital– Return capital to Parent / owners– Opportunity for increasing risk profile /

appetite of captive?

ReturnCapital

Using Analytics to Enhance Captive PerformanceUsing Analytics to Enhance Captive Performance

L k hi t dLokahi – a case study

Lokahi Assurance Ltd

Capital requirements and considerations


Capital requirements and considerations• Regulatory

– Minimum capital & surplus requirement

M i t i i & d i f t bli h t &• Maintaining & advancing reasons for establishment & existence

• Supporting risk assumed– Past, current and future liabilities

• Volatility management

• Efficiency of capital source to support risk (tolerance) position• Self‐sustaining

– Minimize need for additional capital from parent

• Conservative claim reserving underwriting & investmentConservative claim reserving, underwriting & investment strategies


Identifying potential risks to capital


Identifying potential risks to capital• Uncertainty / volatility

– Estimation of reserve adequacy and future losses (premium charge) based hi t i l l d ton historical loss data

• Significant deviation from “expected” may occur if future not reflective of the past

– Medical professional & managed care liability is inherently volatileMedical professional & managed care liability is inherently volatile– High per occurrence claim policy limit ($20 million)– Unlimited (no aggregate) per occurrence policy limit– Changes to the tort environmentChanges to the tort environment– Medical and general inflation– New theories of liability / exposure– Uncertainty surrounding PPACAy g– “Parameter risk(s)”


Managing Volatility ‐ “Evolution”


Managing Volatility Evolution• Created to underwrite all KP regions “excess PPL”• Retroactively assumed all PPL outstanding claim liabilityRetroactively assumed all PPL outstanding claim liability

from 1985 through 2002 ($300+million)– Protected via an Adverse Development Cover

- Subsequently commuted

• Regulatory approval received to allow assumption of PPL exposure from KFHP regions from “first dollar”exposure from KFHP regions from first dollar

• $500 million loss portfolio transfer from regional balance‐sheets to Lokahi


Managing Volatility ‐ Expanded role and risk position


Managing Volatility Expanded role and risk position• Lokahi assumed all PPL exposure previously retained by KFHP

regional health plans for occurrences from 1/1/2003 and forwardL k hi i iti $500 000 t tt h t f• Lokahi previous position excess $500,000 up to attachment of commercial PPL program ($15M ‐ $20M, currently)

• Each KPHP region previously required to maintain balance sheet f li biliti t $500 000reserve for liabilities up to $500,000 per occurrence

• Transaction “mirrored” assumption of regional liabilities prior to 2003

/ / /• Effective 1/1/2011 Lokahi to issue annual indemnification / insurance policies to regions

• Indemnifying regions for fixed actuarially determined premium• Policy coverage form to be consistent with historical PPL form• Coverage now “first dollar” as opposed to Excess $500,000


Managing Volatility


Managing Volatility• Further reduces regional & overall result volatility• Provides “dampening” effect to reserve volatility• Increase administrative efficiencies • Facilitates increased budgetary certainty and planning advantages• Reducing significant reserve swings at regional levelg g g g• Facilitates increase focus on underlying cost / loss drivers• Re‐focus on critical risk management initiatives• Structured so as not remove “ownership” of claims frequency &• Structured so as not remove ownership of claims frequency &

severity• Allows exploration of further volatility management (reinsurance)

R t ti (Ad D l t C )– Retrospective (Adverse Development Cover)– Prospective Excess of Loss Reinsurance, within $20M retained layer


Managing Volatility


Managing Volatility• Positions taken within Parent’s commercial insurance program• Facilitation of Terrorism coverage (TRIA)g ( )• Facilitation of integrated Terrorism and Pandemic

(reinsurance) placement– Physical property & medical / hospital expense

• Exploration of retaining additional corporate risk(s)W k ’ C ti– Workers’ Compensation

Using Analytics to Enhance Captive PerformanceUsing Analytics to Enhance Captive Performance

C id tiConsiderations

ConsiderationsConsiderations

• No model is “100% right”“For every complex question there is an answer that is clear, simple and wrong”simple, and wrong

• Using analytics / models to make decisions requires:‘’You want answers?”.... “I want the truth!”….“You can't handle the truth!”– Management buy‐in as to modeling approach– Judgment and experience to temper technical results– Understanding of sensitivities to assumptions and data limits– A reasonable level of understanding of the modeling– Technical leaders on significant model components– Collaborative thinking when building the model

ConsiderationsConsiderations• Data quality is vital… “Garbage in, garbage out”

“Now that you know that the answer to the Ultimate questionNow that you know that the answer to the Ultimate question of Life, the Universe, and Everything is forty‐two (42), all you need to do now is find out what the Ultimate Question is.”

The Ultimate Question, of course, is…… “What do you get if you multiply six by nine”*

*Six times nine is actually fifty four The program on the "Earth computer" should have run correctly but the unexpected arrival of*Six times nine is actually fifty‐four. The program on the Earth computer should have run correctly, but the unexpected arrival of the Golgafrinchans on prehistoric Earth caused input into the system—computing (because of the garbage in, garbage out rule) the wrong question—the question in Arthur's subconscious being invalid all along.


Q ti ?


Questions?.......and (possibly) Answers…and (possibly) Answers

Documents

New Using Analytics to Captive Performance - Hawaii Captive …hawaiicaptives.com/wp-content/uploads/2013/11/Using... · 2013. 11. 13. · Using Analytics to Enhance Captive Performance