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2010-Tokyo-EBIG-Schrager-Semagin

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2010-Tokyo-EBIG-Schrager-Semagin

  1. 1. Equity-Based Insurance Guarantees Conference May 31 – June 1, 2010 Tokyo, Japan Risk Managing Living Benefits Andy Rallis, David Schrager, Denys Semagin
  2. 2. 1 VA Risk Management David Schrager Denys Semagin Head of Financial Engineering Head of Quant Development ING Life Japan, Annuity Risk Management division June 1st 2010 (13.45 – 15.45 hours) www.ing.com Agenda David Schrager • ING Experience in Financial Crisis • Lapse modeling in reserving / pricing • Risk management • Different approaches • Suitability for financial management Denys Semagin • ING Insurance Library 2
  3. 3. 2 What Worked in the Crisis • Hedge program never stopped • Goal: Replicate Guarantee Value movements using financial derivatives to reduce P&L volatility Hedge programe Hedge target Risk factors Hedge instrument Hedge coverage Target hedge ratio EQ delta hedge First order delta claims TOPIXX, EUROS EQ index futures First order items 100% IR delta hedge First order delta claims JPY, EUR, USD IRS First and higherorder items 80-90% FX delta hedge g First order delta claims EUR/JPY, , USD/JPY FX forwards First order items 100% Rho hedge First order rho claims and premium JPY, EUR, USD IRS First and higherorder items 100% • Enough liquidity for all hedge instrument • FX forwards, EQ futures, IRS markets are very liquid • Infrastructure puts asset / liability risk management a ”risk platform”. • Address time zone differences • Providing liability model(s) to project the market risk (“Greeks”) using Monte Carlo Simulation • Computer system platform cooperating with other ING Insurance Entities DataMart Trading System DB ING Insurance Library ING F FO - Trading (EQ, FX,IRS) ING F BO - Recon ING Insurance -Monitoring / maintenance -reporting / setup Accounting system Broker BBG SPVA site Trading application server Problems Faced in the Crisis • Basis risk for Active fund • Non disclosed position: key rate duration (interest rate sensitivity) was not available for several bond fund (they do not provide) which were unhedged. From 2009, after negotiation for key rate duration, we reduce the unhedged exposure from 10% to 1%. • Active fund performed worse than the index during the crisis. • Delta hedging P&L results are driven by assumptions • P&L at issue is driven by pricing vs. reserving • P&L over time is driven by economic assumptions vs. realization • Hedge instruments mismatch • Mismatch of hedge instruments and assets. • More pronounced in crisis. • Interest rate spread on cash bonds compared to swaps reversed. • Accounting challenges • Often the liability is measured at historic or locked-in assumptions while derivatives used to hedge the liability are fair valued • Timing differences when different markets close • Lapse model (Customer behaviour) • Although lapse leads a lower account value, customers chose lapse due to the lack of money in the crisis. • The current lapse rate function is jumping around even under low volatility environment. • As a result, Greeks become more random than necessary, which worsens hedge performance.
  4. 4. 3 Risk Management at ING Summary: 1. Product design • Transfer or limit risk according to sensible risk appetite 2. Product Pricing • What products? What markets? What price and when? Then the rest follows… 3. Risk measurement • Need to set limits and ensure limit monitoring in place 4. Risk mitigation • Cannot prevent failure with good risk management after pricing stage, that’s where all the damage is done 5 Agenda David Schrager • ING experience in financial crisis • Lapse modeling in reserving / pricing • Risk management • Different approaches • Suitability for financial management Denys Semagin • ING Insurance Library 6
  5. 5. 4 Modern Economic Valuation Principles • Valuation of the embedded options in VA contracts requires understanding of: • Option theory: risk neutral valuation principles • Policy holder behavior: clients right to lapse • Different policy holder behavior modeling approaches can be used: • Traditional actuarial • Econometric • Early exercise behavior • Rational exercise of the right to lapse • Eventually valuation and hence reserving principles should be judged by ensuing effects on key financials and financial health of a company 7 Traditional Actuarial Approach The following principles are at work • Best estimate client behavior • “Expert” opinion • No / minimal interaction with underlying economics of the contract: • SV / SP or SV / K This has the following effects on the key financials of the company • P&L necessary different from zero, both positive or negative because experience will deviate from assumptions • Capital is required for this risk •• There’s no built in mechanism that guarantees beforehand whether the product will be profitable Conclusion • Approach is limited and unsuitable for financial management in modern financial industry, it’s great if you want to “support the business” 8
  6. 6. 5 Econometric Approach The following principles are at work • Client behavior is function of explanatory variables • Empirical data based • Interaction with underlying economics by using variables related to that like: • Moneyness / Forward moneyness (i.e. IR and M&E + AMF corrected) Time to maturity • Age / Gender Fund volatility • Tax laws Distributor This has the following effects on the key financials of the company • P&L necessary different from zero (likely less than with pure deterministic approach), both positive or negative because experience will deviate from assumptions • Capital is required for this risk • There’s no built in mechanism that guarantees beforehand whether the product will be profitable Conclusion • Approach is justifiable but unsuitable for financial management in modern financial industry where capital is expensive and investors/governments demand solid returns and capital positions 9 Early Exercise Approach The following principles are at work • Client behavior is worst case from financial economic perspective of company • Rational behavior based • Interaction with underlying economics by using variables related to that like: • Moneyness / Forward moneyness (i.e. IR and M&E + AMF corrected) Time to maturity • Age / Gender Fund volatility • Tax laws This has the following effects on the key financials of the company • P&L from this source is necessarily positive because experience will deviate from assumptions • No capital is required for this risk • There’s built in mechanism that guarantees beforehand that the product will be profitable Conclusion • Approach is only possible one in modern financial industry where capital is expensive and investors/governments demand solid returns and capital positions 10
  7. 7. 6 Reserve and Hedge impact (1) • Calculate reserve / hedging for different approaches • Example of impact method on delta and replicating strategy and replicated payoff… PV difference at issue Actuarial 6,973 Econometric 6,301 -672 Rational 5,620 -682 -1,354 Scenario Step dAV AV 0 0.00% 100,000 1 1 1.00% 00% 101 101,000 000 2 -3.00% 97,970 3 -1.00% 96,990 4 0.50% 97,475 5 -0.50% 96,988 11 Reserve and Hedge impact (2) Actuarial Step Delta Hedge P&L Cumulative P&L 0 -21,231 1 -17,632 -212 -212 2 -28,132 529 317 33 -3311,226699 228811 559988 4 -29,732 -156 442 5 149 590 Econometric Step Delta Hedge P&L Cumulative P&L 0 -24,460 1 -20,489 -245 -245 2 -32,062 615 370 3 -35,510 321 691 4 -33,821 -178 513 5 169 682 12 Rational Step Delta Hedge P&L Cumulative P&L 0 -28,019 1 -23,871 -280 -280 2 -35,883 716 436 3 -39,411 359 795 4 -37,687 -197 598 5 188 786
  8. 8. 7 Example of Bad Product Design • Consider standard MGDB+MGSB w/o ratchet or clicks • Strike = SP • AV(0) = SP • No surrender charge • M&E fee is fixed 13 Risk Management by Product Design Alternatively policyholder behavior risk can be mitigated by product design • More sophisticated surrender charge mechanism • Time to maturity • Moneyness • VIX level • … • Adjustable M&E fee • Up-front fee payment 14
  9. 9. 8 Agenda David Schrager • ING experience in financial crisis • Lapse modeling in reserving / pricing • Risk management • Different approaches • Suitability for financial management Denys Semagin • ING Insurance Library 15 ING Insurance Library: What is it? IIL is a powerful in-house software library that could be combined with any type of user interface and has unlimited potential to support valuation for any type of products in ING Group. • A calculation engine that provides risk and other metrics for ING insurance products • A software framework using re-usable code that will facilitate rapid delivery of new products and enhancements moving forward • A replacement for old liability models that are not flexibly callable, not easily extendable, and operationally insecure. • Passed major audits in Q2 2009 and in Q1 2010 • Includes database for secure and auditable storage of inputs and outputs • Other business units within ING Group consider IIL for risk management related tasks
  10. 10. 9 ING Insurance Library: Business Impact Summary • Basis Risk better addressed in IIL => reducing P&L volatility of Basis Risk by 20% • Intra-day hedging targeted through IIL => reducing P&L volatility • Hedging and control of P&L volatility are more fair and efficient with tunable risk factor modeling. • All currently hedged products (9) are in IIL (modeled and approximated) • Around 2 months for full development and testing cycle targeted for new VA products • Cooperation within ING group for hedging, stochastic models/calibration development ING Insurance Library: Business Alignment Financial: • Better attribution and control of P&L volatility • Improved risk management to protect solvency and ratings • Reduced hedging costs Operational: • Faster time to new products • Fewer operational errors Compliance: • Single repository of data for risk regulatory and reporting purposes • Tight controls on processes, separation of duties • Secure data storage
  11. 11. 10 ING Insurance Library: General Functional Diagram IIL Request Service AFRM DataMart Enterprise Data Inforce Market Fund Assumptions Product Assumptions Actuary Assumptions Mainframe FRM Server Server Server Server Server Server Server Server Server Server IIL Client Batch IRM ALM Server Server Server Server Server Server Server Server Server Server IIL Request Service Pluto IIL Service Data Sophis Hedging Model Market Trades Moses Reporting ING Insurance Library: General Architecture Overview ING insurance library framework Enterprise IT External systems Market Trades, IFRS, Special Reporting, Research and Development, Prototyping, Etc. Sophi s Excel Othe rs Message interface Message interface Message interface Library request message interface (xml) Enterprise Data Base: Market data In-force data Assumptions data Etc. Message interface MoSe s Message Transport Profitability Analysis Reporting Valuation Components IIL Data Base Data interface Sensitivity Analysis Queries
  12. 12. 11 ING Insurance Library: Facts Sheet Item Legacy Approach ING Insurance Library Product flow development 4 months (1 product) 6 weeks (2 products) Example of atomic module development Add multi-multi threshold lapse model 3 weeks (3 products) 1 week (all products) Daily hedge runtime 500,000 contracts 3h05’ 2h35’ (valuation + hedge sensitivities) Post processing 1h50’ 0h20’ Total ~5 hours ~3 hours Scalability and configuration Risk types supported 0 14 (EQ+IR+FX, configurable) Fund groups supported 8 (fixed) 46 (configurable) Add risk factor N/A No development required Add fund group Development required No development required Data output formats Fixed Configurable Load Balancing/Resources None/Fixed Configurable/Scalable ING Insurance Library: Architecture And Road Map Architecture type: Multi-tier client-server Component communication: • Messages: standardized XML • Message transport channel: message queue (activated on server side) Components: • Service clients application (manual control on user side or automated on server side) • Service application (calculation service, server side only) • Resource manager / load-balancing applications (server side only) • Configuration and logs: flat files (server side only) •• Databases and GUI: Oracle and web service (server side only)
  13. 13. 12 ING Insurance Library: Current System Architecture Client: Enterprise Data IIL DB Internet Queries Data Storage Scheduled Automated Client Web DB GUI Queries Queries Server Server-side applications: Resource manager / Load balancer / Logging Message Broker Request / Response Messages/Responses network / Server Farm intranet Restricted PRODUCTION Environment Client: IIL Run GUI ING Insurance Library: Remote Access to IIL/DB Operations Corporat e I t t Local Intranet Area Remote User Intranet Area Web DB Client URL Remote Desktop IIL Service / DB / Sophis Dedicated PC for remote access
  14. 14. 13 ING Insurance Library DB Web GUI and data control Summary panel in DB Web GUI readable by human user • Each set of data tables will be grouped by a Run ID and referred as a component in a IIL request message • Data Settings • Data comparison • Data validation • Data approval • Audit trail of user and modified data • User rights • Grouping data for Runs • Running for a set of data grouped by Run ID ING Insurance Library: Process Flow Diagram Data up loader IIL Inforce M k t IIL Service Mainframe Enterprise Data Market data Assumptions IIL DB Assumptions GUI Load Balancing BBG ftp User Output PV/Greeks Automated Client Run Manager Automation Process (inforce, client-service, operator emails, etc)
  15. 15. 14 ING Insurance Library: Data Flow in Full Trading System Set-up Trading Enterprise Acc. Data Broker BBG system DB Data ING Insurance Library IIL DB User group B Trading system application server -Monitoring - Trading - Reconciliation - monitoring -maintenance (EQ, FX,IRS) -reporting -setup User Group A ING Insurance Library: Model Flow in IIL Run External processes and Memory Cache Model Calibration Fund Regression Result storage Inputs Risk Factor Projection Risk Factor Mapping to Funds SPVA Liability Projection Generation of Results IIL Process Engines and Object Cache
  16. 16. 15 ING Insurance Library DB Web GUI and XML request message - (illustration) Summary panel in DB Web GUI readable by human user • Each set of data tables will be grouped by a Run ID and referred as a component in a IIL request message IIL request message template: run specs readable by service • A IIL request message is a root component with optional sub-components • <Request> • <Component> • <Name>FRMProcessFlow</Name> • <Type>ProcessFlow</Type> • <Parameters></Parameters> • <Outputs></Outputs> • <Component><-- RF projections -- > • <Component><-- HW Model -- ></Component> • <Component><-- BS Model -- ></Component> • <Component><-- FX Model -- ></Component> • </Component> • <Component> <-- SPVA evaluation -- > • <Component><-- Lapse -- ></Component> • <Component><-- Mortality -- ></Component> • <Component><-- AV Model -- ></Component> • <Component><-- Click Model -- ></Component> • <Component><-- SP Model -- ></Component> • </Component> • </Component>< -- Data component -- ></Component> • </Component>< -- Etc… -- ></Component> • <Reply> • <Status></Status> • </Reply> • </Component> • </Request> ING Insurance Library: Functional Stratification of IIL Service Utilities Components Data Cache Set Up IIL Objects Set Up Process Flow Set Up Flow Engines Individual Models Message MESSAGE Evaluation Layer Internal Set Up Layer External Set Up Layer IIL SERVICE AREA TRANSPORT AREA
  17. 17. 16 ING Insurance Library: Stochastic Modeling Framework for VA Financial Market Model Actuarial Models Calibration based on Market Data Calibration based on risk and return assumptions Risk Neutral Simulation Real World Simulation Scenarios for risk factors Mapping of risk factors to investment funds Scenarios for investment f d Variable Annuity Liability Models Dynamic Policy holder behavior models Mortality models (static / trend / …) Surrender Charge model funds Time Steps Standard DB+SB / Click / Ratchet / Best-Of / IB / WB Risk Reporting PV DB+SB / PV Fee / Deltas / Gammas / Cross-Gammas / Rho / KRD ING Insurance Library: Flexibility of Evaluation Flow in IIL Service Run same evaluation flow with a different interest rate model, reporting t t i lb ifi th Results Calculation SPVA Evaluator Hull-White IR Model Results Calculation SPVA Evaluator BDT IR Model type, etc, simply by specifying the new models in the evaluation request. SPVA Evaluator Replace this component Zero Rate Curve Bootstrapping Swap Curve Libor Curve Foundation Layer Zero Rate Curve Bootstrapping Swap Curve Libor Curve Foundation Layer p p Zero Rate Curve Bootstrapping Swap Curve Libor Curve Foundation Layer
  18. 18. 17 ING Insurance Library: flexible model building blocks and flow invariance Lapse rate: Account Value model l = F(moneyness, lapse assumptions) Surrender Charge Assumprtions Strike model Moneyness Model Surrender Charge Payoff lapse_NSC SV (left): moneyness = AV_1 / Strike_1 Guarantee model SC SS (right): moneyness = Lapse Rate Model Lapse Assumptions AV_2 / Guarantee ING Insurance Library: Development Summary • Includes state of the art stochastic models • Database and load balancing are parts of IIL framework • Supports rapid development through code re-use • Software can be developed in and shared among different locations • Service can be deployed to other locations on Windows (or Linux) • Fully supports hedge program by providing ALL hedge sensitivities as well as Performance Attribution

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