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Connected Decisions: How a Holistic Approach to Decision Making Can Help Insurers Build a Profitable Book of Business An Insurance & Technology Editorial Webcast Sponsored by:

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A vendor presentation for software architecture and analytics for decision making in insurance industry in 2009.

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Page 1: Insurance Decision Making Architecture Slides 2009

Connected Decisions:How a Holistic Approach to Decision Making Can Help Insurers Build a Profitable Book of 

Business 

An Insurance & Technology Editorial Webcast Sponsored by: 

Page 2: Insurance Decision Making Architecture Slides 2009

Today’s Presenters

• Kathy Burger, Editorial Director, Insurance & Technology (moderator)

• Gail E. McGiffin, Global Lead, Underwriting, Accenture 

• Scott Horwitz, Senior Director, FICO 

• Lamont D. Boyd, CPCU, AIM, Insurance Market Director, Global Scoring Solutions, FICO 

Page 3: Insurance Decision Making Architecture Slides 2009

Agenda

• Assessing the challenges facing insurance IT organizations today ‐‐ and what this means in terms of capabilities for improving customer retention and driving growth.

• Competing as a price optimizing organization – what are the necessary tools, processes, structures?

• Better decision making on the front lines.

• Key differentiating technologies and strategies.

• Q&A and follow‐up.

Page 4: Insurance Decision Making Architecture Slides 2009

Insurance/FS at a Crossroads?

• Far‐reaching (and still unknown) impact of  financial/credit crisis, economic downturn, recession – cautionary for insurers (it’s not just about banking).

• FS industry is remade & realigned – erstwhile powers are weakened (or gone), new competitors emerge.

• Right now: It’s all about trust (or lack of it).

• Assumptions about risk, competition,                    growth under fire (or being reconsidered                         in emerging new regulatory environment.                    

• IT wasn’t part of the problem, but it will be part of the solution (be careful what you wish for). 

Page 5: Insurance Decision Making Architecture Slides 2009

Macro Impact on Insurance IT

• IT budgets under pressure – tight, but notbutchered. More doing more with less.Resource maximization more critical than ever.

• Increased (if possible) emphasis on removing  costs, inefficiencies from processes, improvingdeliverables (speed‐to‐market, compliance, retention, etc.), and refining  metrics (ROI, TCO).

• More need than ever for infrastructure & technologies that enable flexibility, interaction, measurement.

• Know your customers – insight that drives underwriting, sales, product development, service.

Page 6: Insurance Decision Making Architecture Slides 2009

Some Windows of Opportunities

• Speed to market, customer/employeeexperience – IT plays a critical role                             (new products, service, social media, STP, etc.). 

• Optimizing multi‐channel distribution – anticipating, supporting needs of distributors and customers.

• Web 2.0 for interaction and collaboration.• New/updated regulation will demand transparency and 

enhanced capabilities (analysis, reporting, documentation, etc.), which can be leveraged.

• Mastering the balancing act between risk management and growth.

Page 7: Insurance Decision Making Architecture Slides 2009

Shifting Investment Priorities?

• Analytics, models, rules – for customer, channel, competitive insights, plus enabling targeted pricing & profitable customer segmentation, product development.

• Better alignment, collaboration, information                   

sharing. Web 2.0 for business.

• Customer (policyholders & distributors)           

experience.

• Standards‐based architectures/infrastructures – to support growth, STP, integrated view, compliance, etc.

• BPM, governance – keys to compliance, maximizing resources, deliverables, transparency. No surprises.

Page 8: Insurance Decision Making Architecture Slides 2009

Unlocking the Value of

Enterprise Decision IntegrationGail Mc Giffin

Partner, Global Underwriting Solutions Lead

Page 9: Insurance Decision Making Architecture Slides 2009

© 2009 Accenture. All rights reserved. 9

Economic and competitive trends are reshaping the Insurance industryOver the past 5 – 10 years, both industry consolidation and a booming economy have redefined the insurance landscape, introducing complex challenges that require more sophisticated approaches to decision management.

• Lack of Offering Differentiation– Undifferentiated products/services– Limited cross-selling– Large-grained industry and customer

segmentation

• Talent Erosion– Exodus of UW/Claims technical

experience – Reduced recruiting/training spend– Deficient sales skills at customer

interaction points

• Inconsistent, Manual Processes– Limited technology enablers– Lack of data and technology

integration

• Lack of Sophisticated, Granular Insight– Immature BI Capabilities– Limited Use of 3rd Party Data– Limited Use of Predictive Modeling

• Changing Agent/Broker Landscape– Return of Global Broker focus

on MM segment– Emergence of new National

Brokers from M&A– Disappearance of Local

Independent Agencies– Repositioning of Captive

channel

• Emerging Environmental Issues & Exposures– Expanding definition of terrorism– Virtual globalization of business

exposures– Climate change-related

catastrophes

• Increasing Market Pressures– Economic crisis– Increasing federal oversight– Cross-border M&A activity

Emerging Landscape

Historical Landscape

> Eco> Economic & Competitive Trenomic & Competitive Trends <nds <

Page 10: Insurance Decision Making Architecture Slides 2009

© 2009 Accenture. All rights reserved. 10

Insurers that maintain insight and business rules in functional silos experience sub-optimal decision making and therefore sub-optimal results.

Sales & Distribution

Underwriting & Pricing

Policy Administration ClaimsMarket Research &

Product Development

Target customer segment for new product = Boutique

StoresTarget profile = sales < $5m, suburban or rural territories, Tier I and II

agentsProducts = BOP, Auto, WC,

UmbrellaSpecial coverage forms,

proprietary rating, predictive pricing model

Sales force in certain territories discovers that retail store business is

controlled by specific Tier III agents writing with smaller, local insurers

Given new product launch in the market and

aggressive sales goals, local sales managers

decide to pursue these Tier III agents for the business.

New business application #1 --- urban jewelry store

submitted and quoted. Quote rejected as not

competitiveNew business application #2 – suburban pet store submitted and quoted

successfully (policy written) for Tier I agent.

UW rules dictate exclusion for animal mortality.

Thirty days after policy is issued, endorsement

request submitted to call center to add coverage for

animals.CSR processes

immediately based on tier of agent (Tier I) and target

nature of account.

Claim submitted for loss of animal inventory due to water contamination.

Adjuster pays claim and closes out file.

Claim department knows this type of claim is typical with pet stores rather than

mortality claims.

Boutique stores results are marginal due to lack of penetrationwith Tier I and II agent expectations and adverse selection in urban territories.

Performance Management

Page 11: Insurance Decision Making Architecture Slides 2009

© 2009 Accenture. All rights reserved. 11

This decision leakage can proliferate across the value chain thereby compounding the resulting impact.

Sales & Distribution

Underwriting & Pricing

Policy Administration ClaimsMarket Research &

Product Development

Target customer segment for new product = Boutique

StoresTarget profile = sales < $5m, suburban or rural territories, Tier I and II

agentsProducts = BOP, Auto, WC,

UmbrellaSpecial coverage forms,

proprietary rating, predictive pricing model

Sales force in certain territories discovers that retail store business is

controlled by specific Tier III agents writing with smaller, local insurers

Given new product launch in the market and

aggressive sales goals, local sales managers

decide to pursue these Tier III agents for the business.

New business application #1 --- urban jewelry store

submitted and quoted. Quote rejected as not

competitiveNew business application #2 – suburban pet store submitted and quoted

successfully (policy written) for Tier I agent.

UW rules dictate exclusion for animal mortality.

Thirty days after policy is issued, endorsement

request submitted to call center to add coverage for

animals.CSR processes

immediately based on tier of agent (Tier I) and target

nature of account.

Claim submitted for loss of animal inventory due to water contamination.

Adjuster pays claim and closes out file.

Claim department knows this type of claim is typical with pet stores rather than

mortality claims.

Lack of integrated decisions and insight results in unfavorable/unintended results

•Inadequate competitor &market analysis

•Gap in product vs. sellingrules

•Misalignment in salesexpectations and UW

appetite & pricing rules

•Service segmentationnot aligned with

risk segmentation•Lack of insight into UW

Intent/rules

•No insight into UW rules•No feedback loop

into PD/UW

•Lack of insight from priorclaims experience

•Lack of sales/agent insightIn market analysis

Page 12: Insurance Decision Making Architecture Slides 2009

© 2009 Accenture. All rights reserved. 12

Shared insight and integrated business rules enable more interconnected decisionsacross the enterprise.

Sales & Distribution

Underwriting & Pricing

Policy Administration ClaimsMarket Research &

Product Development

Refined product targets for urban vs. suburban/rural

territories

Optimized pricing models by type of store by territory

Focused sales aligned to UW appetite, product rules and competitive pricing by customer type by territory

High hit ratios for submitted new business

Pricing/coverage can be elasticized for best risks

Policy servicing rules are synchronized with sales

and UW strategies

Tighter linkage between UW rules and

form/issuance rules

Predictability in loss types based on product/customer

profiles

Loss coding better aligned to UW/policy coding

Target mix achieved for desirable SICs, territories, agents and size.Compelling new product offering penetrates market with higher growth rate.

Performance Management

Page 13: Insurance Decision Making Architecture Slides 2009

© 2009 Accenture. All rights reserved. 13

High Performance Decisioning Benefits

Better synchronization of rules and analytics • Product eligibility/targeting• UW appetite/pricing• Workflow, work assignment• Sales approach• Policy forms, billing options by product/agent• Claim processing

• Improved loss ratio• Focused and targeted growth (better hit

and retention ratios)• More optimized book mix• Easier to do business with• Better customer experience• Fewer errors, less rework• More granular insights to refine products,

services and processing as a competitive edge

•More integrated insights• Claims experience Product development• Sales/marketing PD/UW• PD/UW Policy processing

Integrated decisioning can dramatically reduce decision leakage and provide a competitive advantage in the marketplace

Page 14: Insurance Decision Making Architecture Slides 2009

© 2009 Accenture. All rights reserved. 14

Accenture’s Integrated Decision Solution for Product Management

Product Configuration/Testing/DeploymentAnalytics

Testing Interfaces

ImpactAnalysis

Production(Transaction

Systems)

Data Services

Policy

Claims

DW

3rd Party

Product Definition

Rates

UW Rules(incl Predictive

Models)

Form Rules

RatingEngine

Rules Engine

Forms Engine

Production Rates

Production Rules

ProductionForms

PremiumDisplacement

Rules/PricingImpact

FormImpact

ETLCleansingMatchingProfilingQualityIntegrationAugmentation

Development Applications

Forms Application

Rules Application

Rating Application

Performance Data

Sample Data Sets

FormsSelected

Mods / Factors

Rules Fired

Customers

Agencies

Geographies

Competitors

An enterprise rules and analytics platform is required to support integrated decision solutions.

Page 15: Insurance Decision Making Architecture Slides 2009

© 2009 Accenture. All rights reserved. 15

A Rule Taxonomy helps to govern and direct decision behavior across the enterprise

Product Configuration

Product DefinitionData Validation

Display Formatting

Data Derivation

External InformationOrdering

Information NeedsIdentification

Data Reconciliation

EligibilityAcceptance

Referrals

Pricing Price Level Selection

Premium CalculationRate Order

Rate Step

WorkflowProcess Management

Task Management

Form Definition

- Sample Rule Category to Sub-Category Mapping –

Illustrative

Page 16: Insurance Decision Making Architecture Slides 2009

© 2009 Accenture. All rights reserved. 16

1-2 Months 4-8 Months 4-6 Months 1-2 Months•Determine scope of extraction/ management effort – e.g. 1 state, 1 line of business, type of rules

•Secure resources

•Conduct initial interview of functional SMEs to compile list of rule sources (e.g. rate plans, guidelines, individuals etc)

• Conduct initial interview of technical resources to identify existing rule locations in legacy environment

• Confirm location of Central Rule Repository (database) and determine if build activities are necessary

• Catalog Rules – establish rule types/categories via functional walk-thrus of each transaction type and technical discussions

•Document existing rule framework by mapping rule types/categories to legacy environment

•Perform manual review of documentation (e.g., manuals)

•Interview functional resources to understand variations from documented rules (e.g., actuaries and field operations personnel)

•Interview systems resources to make code dive decisions

•Perform automated and manual review (“code dive”) of rules within systems

•Create rule decision trees

•Build Roadmap to prioritize when certain rule types/categories should be targeted for extraction activities

•Document extracted rules in centralized repository

•Design, configure, and build central rule repository (if required)

•Design and build business rules workbench (e.g. rules maintenance facility)

•Perform Detailed Rule Review with SMEs to ensure extraction accuracy

•Consolidate/rationalize inaccurate and duplicated rules

•Establish rule test environments infrastructure

•Develop and confirm testing process flow and signoff criteria

•Perform rule testing – unit, system, client acceptance

•Revise extracted rules to ensure match to target system

•Obtain sign-off on results of validation and operational rule testing activities

•Complete build-out of the business rules workbench

•Develop training to support use of the business rules workbench

•Develop and confirm rules maintenance processes

•Install analysis and feedback loop among rule maintenance, underwriting, product development and other involved capabilities

•Determine metrics that will be collected and develop capabilities to support that reporting

Prepare Extract Validate OperateExisting Rule Framework Analysis

New Rule Framework Creation

RuleExtraction

Validation and Translation

Operational Rule Testing

On-Going Maintenance

InitialPreparation

A Rules Extraction Process helps ensure both programmatic and human decision-making elements are codified.

Page 17: Insurance Decision Making Architecture Slides 2009

© 2009 Accenture. All rights reserved. 17

Rules Architect•Provides a program-wide view of rules activities and application architecture decisions•Oversees maintenance of the centralized rules repository•Creates and maintains a decision tree to facilitate consistent deployment decisions•Tracks extraction activity across the project to be sure that rules are made available to facilitate design activities• Provides point expertise for all related rules activities including identification, extraction, deployment and testing

Rules Analyst•Reviews the materials available to identify and extract the existing rules (through manuals, interviews, etc.)•Documents rule categorizations, inventories, and application mappings•Develops future business rule capability requirements•Documents the rules in the Rules Repository

Enterprise Product Rule Manager•Overall responsibility for maintaining enterprise business rules•Liaison to actuarial, underwriting, product, and systems organizations•Provides guidance and strategy to the stakeholders around rule definition•Supervises line of business rule librarians•Responsible for maintaining integrity of the rules process, identifying improvements where necessary

Rule Librarian Specialists for Each Product/Line/State• Overall responsibility for maintaining line of business and/or business unit (i.e. underwriting) specific business rules•Works with actuarial, underwriting, product and systems organizations to ensure rules are defined and implemented correctly •Has authority to make decisions about product rules and implementation within the new environment•Provides guidance to line of business/region on product strategy•Understands impact of rule changes on systems•Maintains and enters rules

Centralized Rules Repository/Business Rule Workbench Developer•Assists development of centralized repository/business rules workbench•Develops front and backend components related to rule management infrastructure

Technical SMEs for Each System•Understands the implementation of all products within a given system•Able to read the code and understand the system architecture

Functional SMEs for Each Product/Line/State•Understands how products/rules are implemented in current systems

Key Roles and Responsibilities should be established to support this higher level set of analytics and decision capabilities

Illustrative

Page 18: Insurance Decision Making Architecture Slides 2009

© 2009 Accenture. All rights reserved. 18

Implementation Approach

DecisioningTechnology

Management InformationRule

ResultsReporting

BusinessSimulation

Data WarehouseIntegration

Technical Architecture

Testing

Rule/Rate/ ProductManagement Tools

Rule Testing TrackSoftware Testing Track

Rule Unit Testing

Automated Regression TestingSystem Testing Best Practices

Ruleset Testing

Test Data ManagementRules System Test

VersioningApproach

RuleConstruct

Type

Meta-DataApproach

RuleFirings

Persistence

OrganizationApproach

Security

Performance

Rule ServicePartitioning

Rule RepositoryArchitecture

ReferenceData

Approach

Business Outcome Testing

Project ManagementObject Model

ChangeDependencies

Rule ManagementSoftware

Workstream

Rule ExecutionSoftware

Workstream

Rule DevelopmentWorkstream

Testing Facility

Migration Facility

Reporting Facility

RuleDeployment

QA Ruleset

Portal

Authoring FacilitiesVersioning

Applicability

Query

Ambiguity Checking

Copy and Paste

Organization

Rule ChangeImpact Analysis

ResearchRules

EnterpriseRepository

ReferenceData

Management

Harvesting

MethodologyProduct & ProcessSMEs

Librarian

Type-SpecificRepositories

An Enterprise Rules Architecture supports the lifecycle of analysis, rule configuration, rule testing, rule deployment and rule performance measurement to industrialize decision management solutions.

Page 19: Insurance Decision Making Architecture Slides 2009

© 2009 Accenture. All rights reserved. 19

This architecture should be supported by an enterprise AnalyticsFramework…

Insurance Value Chain Analytics Framework

Product Development

Marketing & Distribution

Pricing & Underwriting

Policy Processing Claims Performance

Management

Enhanced Enterprise and Core Capability Decision Making

• Gain insights for creating more tailored products

• Improve ability to deploy new products effectively (filing strategies, training, marketing)

• Enhance primary and secondary research focus

• Leverage product performance metrics to improve business rules and operational efficiency

• Identify potential sales more precisely by analyzing customer purchasing patterns

• Enhance agency recruiting capabilities

• Optimize distribution compensation models

• Improve prediction of product preferences and customer retention

• Speed risk selection and quoting with better alignment between risk quality and pricing (reduced leakage)

• Provide timely insight into price tiering models (eg., predictive models) to adjust models for more targeted marketing

• Identify non-core underwriting operational activities that are candidates for automation, elimination or delegation

• Improve utilization of underwriting services (premium audit, loss control)

• Provide more accurate, timely and detailed understanding of exposure accumulation

• Increase ability to enhance servicing for the most valuable customers and distributors

• Lower costs of processing with enhanced insight into performance of operational staffing models

• Gain insight into process bottlenecks and detailed transactions to identify improvements in policy automation

• Improve timeliness and accuracy of fraud detection

• Enhance resource allocation and prioritization with better insight and predictability into claim complexity and settlement potential

• Improve subrogation predictions

• Enhance reserving practices

• Gain operational insight to increase levels of automation for simpler claims

• Improve consistency in metric management for the organization

• Improve alignment between internal and external data quality and reporting standards

• Achieve greater granularity and timeliness in reporting for improved insight and regulatory compliance

• Increase user sophistication in performance analytics through improved data management and analytic technologies

Page 20: Insurance Decision Making Architecture Slides 2009

© 2009 Accenture. All rights reserved. 20

…including detailed KPIs for targeted areas of decision analysis.

Marketing

• Market Penetration Analysis

• Strategic Demographic Analysis

• Competitor Analysis

• Agency/ Distribution Analysis and Performance Measurement

• Campaign Effectiveness (Affinity, Advertising, Lead Dissemination, etc.)

• Account Rounding Analysis

• Customer Value Analysis

Sales

• Agent Performance/ Profitability Analysis

• NB & Quote Flow• Hit and Yield Analysis

• Cancellation Analysis

• Retention Analysis• in-Force Strategy • Agent/Distribution Performance Analysis

• Channel/Access Method Analysis

• Agency Management Analysis

• Sales Tool Efficiency• Acquisition Cost Analysis

• Compensation Analysis

• Relationship Referral Analysis

• New Business Sourcing Analysis

• Cross Sell / Up Sell Analysis

• Lead Management

Product

Product Research• Market Territory Analysis

• Market Segment Analysis

• Competitor Analysis• Distributor AnalysisProduct Design/ Performance

• Historical Product Analysis

• Rate Making Analysis

• Pricing Analysis • UW Rule Analysis• Loss Experience Analysis

• Contract/ Forms AnalysisProduct Launch

• ROI Analysis• Product Launch Analysis

• Impact/ Disruption Analysis

• What/If Analysis• Regulatory/ Trend Analysis

• DOI Relationship Analysis

• Pricing Performance including Tool Usage

• Predictive Model inputs/outputs/final

• Predictive Model deviations from Baseline

• Predictive Model and UW Rule Integrated Analysis

• Rate Adequacy Analysis

• Marketplace Analysis

• Profitability Analysis

• Loss Ratio Analysis• Loss Development and Trending

• Rate Development and Trending

• Residual Market Loads (WC)

• Involuntary Book Analysis

• Off-Balance Analysis

• Reserve Analysis• Expense Analysis

Underwriting

• UW Productivity• UW Expense Analysis

• SLA Mgmt• Appetite Analysis• Segmentation Analysis

• Book Mix Analysis• Hit and Yield Analysis

• Referral Rates• Authority Analysis• Rule Analysis• Price/Credit Analysis• Agent Performance by Account/Book

• UW Service Utilization

• Market Comparison Analysis

• Competitor Analysis• Quality/Audit Analysis

• Exposure Management

• CAT Management• Loss Experience Analysis

• Reinsurance Analysis (Treaty, Fac)

Servicing

• Service Channel Analysis & Optimization

• Service Channel Segmentation

• Knowledge Management

• Content Management

• Workflow Analysis• SLA Mgmt• Contact Mgmt • Turnaround Times• Cycle Times• Straight-through processing volume

• Escalation Analysis• Reassignment Analysis

• Customer Complaint Analysis

• Policy Error Analysis

• Span of Control Analysis

• Self-service Inquiry Analysis

Corporate Performance

• Planning/ Budgeting

• Growth Analysis• Book Mix and Portfolio Analysis

• Profitability Analysis

• Marketplace Analysis

• Competitor Analysis

• M&A Analysis • Performance Management

• Resource Attrition• Investment Analysis

• Expense Analysis • ISO and Bureau Reporting

• DOI/Statutory Reporting

• Taxes, Boards & Bureaus Analysis

• Voluntary /Involuntary Market Analysis

Pricing/ Actuarial

Claims

• Claims Assignment and Routing

• Fraud Detection• Formula Based Reserving

• Reserve Analysis• Claims Handling Effectiveness

• Claims Processing Efficiency

• Subrogation Analysis

Page 21: Insurance Decision Making Architecture Slides 2009

© 2009 Accenture. All rights reserved. 21© 2009 Accenture. All rights reserved. 21© 2009 Accenture. All rights reserved. 21

The interconnected decision processes must be supported by a set of enterprise rules services and analytics components that integrate these decisions efficiently and effectively across an account, and provide real-time insights into decision outcomes on the book of business.Enterprise Solution Architecture

Data Access Services

Business Process andWork Management

Distribution and Access Methods

Role Based UI

Orchestration and User Tasks

Enterprise Data Sources

AMS Upload

Back Office

Downstream and Reporting

Com

mo n

Arc h

itect

ure

Tool

san

dSe

rvic

e s

Third Party Data SourcesProduct /

Policy / UW Data Sources

Sales and Marketing

Data Sources

Billing Business Intelligence Claims

Email Fax BranchOffice

ProcessOfficeAgent Office

Decision Management

Decision Analytics and Rules Management

Claim Segmentation

Rules

Rule Performance

Analysis

User Experience

Rules

Info Ordering

Rules

Workflow Rules

Billing & Cancellation

Rules

Business Services and Tools

Product Configuration / Identification

Policy Transaction Processing

Underwriting Tools and Services

Sales and Marketing Tools and Services

Product Rules

Rating & Issuance

Rules

UW & Pricing Rules

Sales Rules

Page 22: Insurance Decision Making Architecture Slides 2009

Confidential. This presentation is provided for the recipient only and cannot be reproduced or shared without Fair Isaac Corporation's express consent.© 2009 Fair Isaac Corporation.

Connected DecisionsEnhanced Profitability & Sustainable Competitive Advantage

Scott HorwitzSenior Director, InsuranceFICO

Lamont BoydDirector, Global Scoring SolutionsFICO

July 9, 2009

Page 23: Insurance Decision Making Architecture Slides 2009

© 2009 Fair Isaac Corporation. Confidential.© 2009 Fair Isaac Corporation. Confidential.

FICO is the leader in Decision Management —transforming business by making every decision count

Automatecomplex decisionsin real time

» Increase consistency

» Reduce manual reviews

Improvedecision qualitywith analytics

» Reduce fraud and claims losses

» Optimize underwriting and reserving

Connectdecisions across theenterprise

» Manage across product lines and business silos

» Execute coordinated customer-level strategies

Over 400 insurers have used FICO solutions to create competitive advantage

Page 24: Insurance Decision Making Architecture Slides 2009

© 2009 Fair Isaac Corporation. Confidential.

The Concept of Connected Decisions

Connected Decisions is all about taking a wide-angle view of the business, to see problems and opportunities early enough to takedecisive action to improve results

Connected Decision Principles Operational Benefits Delivered» Taking a policyholder lifecycle view

rather than a functional view

» Recognizing historical information, previous actions, and current policies at one lifecycle decision can influence decisions at another point

» Unlocking efficiency gains and competitive advantage that lie between decisions

» Vision: Improved business visibility & reporting across the policyholder lifecycle

» Segmentation: Finer categorization of policyholders resulting in better matches between actions, needs and outcomes

» Lifecycle Coordination: Individual and incremental value-add through connections that span different decisions

» Policy & Compliance Management:Consistent management of policies at all levels: account, customer, product, channel

» Time to Market: Shared components across functions allow quicker spin up of new products

Page 25: Insurance Decision Making Architecture Slides 2009

© 2009 Fair Isaac Corporation. Confidential.

Product Management Underwriting Policy

AdministrationClaims /

Reserving Fraud

Core Insurance OperationsMarketing

Age

nt P

orta

l

AgentCustomer

Disconnected Decision - Example

Marketing offer for Kevin Smith directing him to visit his agent to get a free rider on homeowner policy

Kevin Smith visits his agent to get the offer

The Independent Agent is not aware of the promotion and applies for the coverage for Kevin

Disconnected Decision:Kevin is denied the offer as information regarding Kevin’s pre-qualification was not fully integrated into underwriting system

» The customer experience with marketing was very good at first, but the disconnect between marketing and underwriting scars his overall experience with the carrier.

» The independent agent is not only uninformed of promotions, but the bad experience his customer had with his carrier makes him less loyal to the carrier’s products in the future

Potential Cost of Disconnected Decision

Connecting decisions across the customer lifecycle unlocks the efficiency gains and competitive advantage that lies between decisions

Connecting decisions across the customer lifecycle unlocks the efficiency gains and competitive advantage that lies between decisions

Page 26: Insurance Decision Making Architecture Slides 2009

© 2009 Fair Isaac Corporation. Confidential.

Product Management

Underwriting Claims / Reserving

Fraud

Core Insurance Operations

Marketing

AgentCustomer

Connected “New Business” Decision

Agent or Applicant Requests New Policy

Application Data Validation

1

Credit Based Insurance Scoring

Analytics 2

Marketing Offer

Analytics

3

Claims History4

Fraud Assessment

Analytics

5

Composite Risk Assessment

Analytics6

Offer Configuration

8Underwriting

Approval7DECISION SERVICES

AnalyticServices

RulesServices

DataServices

Policy Administration

Page 27: Insurance Decision Making Architecture Slides 2009

© 2009 Fair Isaac Corporation. Confidential.

Connected “New Business” Decision Decision Services Unlock the Value

Decision Services Descriptions* Value PropositionValidates the accuracy and completeness of application data using business rules, internal and external data and provides a successful validation or failure with reason codes. Validated applications are passed to the next step in the new business process, while failures result in a request for missing or corrected data.

-Reduces errors in application

-Reduces time spent on acquisition

Pulls a FICO CBIS score from applicable bureau to perform early segmentation of applicant’s risk. If CBIS Score falls within acceptable risk levels, business rules determine additional data requirements and application continues through the new business workflow. Unacceptable risk scores follow a different path, based on state regulatory requirements.

- Better risk segmentation

- Expense reduction in determining additional data requirements for underwriting decision

Obtains data regarding any current offers the applicant has received or is qualified for and augments new business workflow with appropriate information.

- Improved customer service

- Relevant offers presented to prospects

Pulls any available internal claim/loss history or any required external claim history data as required based on data available from previous steps. Allows for internal historical data to be utilized during the process.

-Efficient use of internal/external information to enhance the risk profile

Utilizes possible prior internal claim history and application information to determine if the applicant has any positive identification of recent proven of suspected fraud. If applicant has past suspected fraud, application is routed by business rules to special resources to determine appropriate action.

-Early identification of suspicious risks prior to claim submissions

Based on CBIS score, application data and additional external data (e.g. MVR, CLUE, etc.) creates overall applicant risk score for underwriting decision and price tiering.

- Increased pricing precision based on use of predictive models and connected internal/external data

Generates an underwriting decision and sets a price for coverage utilizing the composite risk score and business rules. The underwriting decision service can optimize pricing to suit strategic goals and constraints using optimization models as applicable.

-Provides the ability to set competitive and optimized prices for desired customer profiles

Utilizes marketing, CBIS, underwriting and claims analytics to determine any complimentary products or offerings that should be packaged with the requested coverage to cross-sell, up-sell or enhance conversion rate for high value customers.

-Increased revenue/profit potential through identification of additional opportunities

1

2

3

4

5

6

7

8

* Decision Service Descriptions correlate to numbered actions on previous slide

Page 28: Insurance Decision Making Architecture Slides 2009

© 2009 Fair Isaac Corporation. Confidential.

Pres

enta

tion

Tier

B

usin

ess

Serv

ices

Tie

r

Product Management Underwriting Policy

AdministrationClaims /

Reserving Fraud

Core Insurance Operations

Marketing

Call CenterAgent Portal

Agent Customer

Web Portal

Decision Management ArchitectureEnabling Common Components

Key Enabling Architectural Components

Data Access & Management

Rules Management

Analytics & Optimization

Model and Rules

RepositoryCase

Management Reporting

FICO’s leading Decision Management solutions enable carriers to develop more precise insights and implement optimized strategies that connect decisions and extract the value

that lies between lifecycle functions

Page 29: Insurance Decision Making Architecture Slides 2009

© 2009 Fair Isaac Corporation. Confidential.

FICO Technologies Help Insurers Achieve the Competitive Advantage of Connected Decisions

FICO Decision Management Solutions

Key Benefits to the New Business Process

FICO Blaze Advisor Business Rules

Management

»Automates the underwriting process by incorporating a carrier’s underwriting guidelines within the rules repository

» Improves the agility of new business and product development processes by giving business managers more control

»Allows for consistent decision making across the underwriting decision lifecycle

»Allows carrier’s to scale their business without the need to add additional underwriting staff

FICO Predictive Analytics

(Industry-Standard Scores and Custom models)

» Improves the precision of existing rating methodologies; assistsexisting underwriting systems to make more accurate decisions

» Improves a carrier’s ability to predict or anticipate a customer’s reaction to discrete offers

»Allows carriers to analyze customer acquisition and attrition patterns and make predictions based on those patterns to acquire and retain customers

FICO Decision Optimization

» Improves a carrier’s ability to develop business strategies based on an optimized view of business objectives and associated constraints

» In some cases allows carriers to incorporate strategies real-time

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© 2009 Fair Isaac Corporation. Confidential.© 2009 Fair Isaac Corporation. Confidential.

Value of Connected Decisions

“Sharing data, analytics and intelligence across the customer lifecycle produces better decisions, enhanced profitability and a sustainable competitive advantage for insurers.”

Marketing Policy Underwriting Loss Ratio Fraud Solution

Development

Profit per account through cross marketing and

selling

Straight-thru processing

Decrease in loss ratio

Decrease in fraud losses through

early identification

Decrease in systems

development time

30%30% 99%99% 50%50%

Sample Client Results within Insurance

8 %8 % 35%35%

Page 31: Insurance Decision Making Architecture Slides 2009

Confidential. This presentation is provided for the recipient only and cannot be reproduced or shared without Fair Isaac Corporation's express consent.© 2009 Fair Isaac Corporation.

THANK YOU

July 9, 2009

Scott [email protected]

Lamont [email protected]

Page 32: Insurance Decision Making Architecture Slides 2009

Q&Aplease submit your question now

• Kathy Burger, Editorial Director, Insurance & Technology (moderator)

• Gail E. McGiffin, Global Lead, Underwriting, Accenture 

• Scott Horwitz, Senior Director, FICO 

• Lamont D. Boyd, CPCU, AIM, Insurance Market Director, Global Scoring Solutions, FICO 

Page 33: Insurance Decision Making Architecture Slides 2009

Resources 

To View This or Other Events On‐Demand Please Visit:

http://www.insurancetech.com/webcasts/

For more information please visit:

www.fico.com

www.fico.com/insurance