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201208 NAMIC Operations: Analytics: A Cross-Functional Solution to Information Overload
 

201208 NAMIC Operations: Analytics: A Cross-Functional Solution to Information Overload

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Predictive analytics and business intelligence tools and management practices are rapidly being adopted and evolved across the insurance industry. High-profile results are often touted within ...

Predictive analytics and business intelligence tools and management practices are rapidly being adopted and evolved across the insurance industry. High-profile results are often touted within specific functional areas. Yet there remains a broader ROI that can be achieved through integrated analytical modeling of information from finance, sales, marketing, pricing, underwriting, and claims. Rapid advances in analytics are enabling companies to translate their wealth of enterprise-wide information into cohesive, actionable strategies directly targeting profitable growth.

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    201208 NAMIC Operations: Analytics: A Cross-Functional Solution to Information Overload 201208 NAMIC Operations: Analytics: A Cross-Functional Solution to Information Overload Presentation Transcript

    • Analytics: A Cross-FunctionalSolution to Information Overload Presented to: 2012 NAMIC Operations Seminar Charleston, S.C. August 23, 2012 Presented by: Steve Callahan, CMC Practice Director Robert E. Nolan Company
    • Today’s Discussion  Why Analytics  Recent Survey Results  Case Studies  Final Thoughts  QuestionsAnalytics: A Cross-Functional Solution to Information Overload © Robert E. Nolan Company | Page 2
    • Analytics One of Top 5 Technology TopicsAnalytics: A Cross-Functional Solution to Information Overload © Robert E. Nolan Company | Page 3
    • How Do the Top 5 Compare TodayAnalytics: A Cross-Functional Solution to Information Overload © Robert E. Nolan Company | Page 4
    • Business Results Driven Priorities Admin / Legacy System Functional, Flexible, Supportable, Reliable Analytics / BI Optimal Information Driven Decisions Mobile Computing Service Delivered in Customer’s Hands Big Data Incorporate All Data into Decisions Cloud Computing Evaluate Universal Access / Variable CostMost Companies Have or Are Addressing Legacy Systems Next Step is Analyzing Discrete Data and Focusing Decisions Analytics: A Cross-Functional Solution to Information Overload © Robert E. Nolan Company | Page 5
    • 2011 Survey: Most Decisions Rely on Experience and “Gut” 82% 60% Robert E Nolan Company Executive Survey, 2011 6Robert E. Nolan Company © | Page 6 Analytics: A Cross-Functional Solution to Information OverloadJune 2012
    • Retrospective Based on Experience versus Predictive MY REAL-TIME ANALYSIS TELLS ME IT’S SMOOTH SAILING 7Robert E. Nolan Company © | Page 7June 2012
    • More Informed Decisions Improves ROI IDC Research Leveraging the Foundations of Wisdom: The Financial Impact of Business Analytics (© IDC) showed30% tremendous25% gains –20% 10 Years Ago15% (2002)10% Median ROI: 5% Predictive: 145% NonPredictive 89% 0% 1-50% 51-100% 101-500% 501-1000% >1,000%Analytics: A Cross-Functional Solution to Information Overload © Robert E. Nolan Company | Page 8
    • 2011 Survey: Leadership Decisions Moving To Data DrivenAnalytics: A Cross-Functional Solution to Information Overload © Robert E. Nolan Company | Page 9
    • 2011 Survey: Analytics Used Across Wider Variety of AreasAnalytics: A Cross-Functional Solution to Information Overload © Robert E. Nolan Company | Page 10
    • Analytics Capability Maturity Evolution 5 Tools and data rapidly evolving Most 4 Continuous improvement loop Companies Here 3 Direct Link to Decision Making Applied Across the Organization Advanced Analytics Tools 2 Integrated Data Limited Link to Decision Making 1 QA Standards Applied Basic Analytical Tools Limited Data Integration Basic Data Minimal QAAnalytics: A Cross-Functional Solution to Information Overload © Robert E. Nolan Company | Page 11
    • A Different View: From Reporting to Data InnovationAnalytics: A Cross-Functional Solution to Information Overload © Robert E. Nolan Company | Page 12
    • Relative Adoption by LOB 25.00% 20.00% 15.00% 10.00% Predictive 5.00% Retrospective 0.00%Analytics: A Cross-Functional Solution to Information Overload © Robert E. Nolan Company | Page 13
    • Top Line Revenue is Improved As WellCarriers effectively using predictive analytics achieved:•1% improvement in profit margin•6% improvement in year on year customer retentionCarriers not fully using predictive analytics:•Dropped 2% in profit margins•Decreased 1% in year on year customer retentionHigher on the Capability Maturity Curve = Better Results:•Top 20% : 27% Year on Year Growth in Revenue•Middle 50% : 12% Year on Year Growth in Revenue•Bottom 30% : 1% Year on Year Growth in RevenueAnalytics: A Cross-Functional Solution to Information Overload © Robert E. Nolan Company | Page 14
    • Summary Key Benefits of Analytics Gain deeper, more relevant business insights to inform decisions Bring predictive analysis and regression modeling to entire organization Use analytics to identify and determine options for industry challenges Effectively and proactively manage risks Strengthen data governance at each level of the organization Reduce costs through more accurate, data-driven decision-making Use analytic capabilities and outcomes for change management Create a culture that thrives on fact-based decisions versus “gut” Analytics: A Cross-Functional Solution to Information Overload © 15 Robert E. Nolan Company | Page 15
    • Yet Companies Struggle to ImplementMost frequent reasons companies struggle with analytic initiatives:•Too much management, not enough leadership•Limited support and buy-in at multiple levels within the organization•No guiding purpose or vision for people to rally around•Overemphasis on technology implementation/success criteria•Business benefits are too fuzzy to articulate and communicate clearly•No consistent communication or messaging to stakeholders•Poor identification of stakeholders and influencing factors•Compensation structures and incentives not aligned Robert E Nolan Company Executive Survey, 2011 © 16 Robert E. Nolan Company | Page 16Analytics: A Cross-Functional Solution to Information Overload June 2012
    • And the Barriers Are DiverseSurvey Comments on Barriers to Growth in Use of Analytics“Resistance comes from most experienced, those requiring 100% accuracy”“Access to critical data that is not captured in the system but is on paper”“Getting away from tribalism, managing by anecdote and subjective decisions”“Availability of resources and the money necessary to do it right”“Data is spread all over and difficult to integrate or consolidate”“Privacy will become a major issue as external data sources drive decisions” Robert E Nolan Company Executive Survey, 2011 © 17 Robert E. Nolan Company | Page 17Analytics: A Cross-Functional Solution to Information Overload June 2012
    • With Opinions Varying Greatly“The importance placed on analytics will grow, however there will bea disproportionate reliance placed on results, until managementlearns that garbage in/garbage out continues to cast its shadow.““It really doesn’t matter as most data currently produced comprises the basis for most uses necessary. Advanced techniques do not therefore produce ‘advanced’ data - the numbers are the numbers no matter how produced. Indeed, give me a room full of ladies in green eyeshades and Marchant calculators and maybe a punch card reader or two and I could be perfectly happy with managing the business, no matter how complex.““Those companies that do not embrace technology and analytics will be left behind in the dust of those companies that do. “Analytics: A Cross-Functional Solution to Information Overload © Robert E. Nolan Company | Page 18
    • Common Barriers to Using AnalyticsAnalytics: A Cross-Functional Solution to Information Overload © Robert E. Nolan Company | Page 19
    • Analytics is One Tool in the Retroactive Entire Product Life Cycle Production Research Operations Internal and Feedback External Data Predictive Acquisition and Analysis Cleansing A clear but specific Exception Conversion and Formatting vision enables a Handling and Workflow manageable project Rule and Rate Client and Account Centric structure with iterative Automation and Integration deliveries. Enforcement Population External Data Analysis and Acquisition Segmentation Product Development & Assembly Underwriting Rule and Rate Product / Forms Rule and Rate Pattern and Data Rate Design and Rules Design Model Prediction Creation Production Analysis Modeling and Modeling and Optimization and Assembly Roll Out Iterative ProcessAnalytics: A Cross-Functional Solution to Information Overload © Robert E. Nolan Company | Page 20
    • Transforming Product Development Improved use of analytics can be organized so that the key plan areas can be developed along three parallel tracks. Data Production Product Processing Evaluation Development Integration and Analysis  Current Data  Modeling and  Rates and Rules Evaluation Analytic Tools Integration  Data Cleansing and  Rules Engines  Predictive Analysis Alignment  Rating Engines Models  Market Segmentation  Product  Workflow and Assembly Analysis Exception Process  Process  External Data  Legacy Integration Integration and Aggregation Management  “Dashboard”  Trend Analysis Tools  Performance Development and and Modeling ScalabilityAnalytics: A Cross-Functional Solution to Information Overload © Robert E. Nolan Company | Page 21
    • Case Study A: Prospect Scoring Scoring of prospects based on conversion and Psycho- value, marketing strategy developed to match graphic Data Potential Value Text High value, High value, High value, Low Medium High Data conversion, conversion, conversion, 2nd Priority Top Priority Top priority Predictive Potential Good value, Good value, Good value,Web Analysis Future Low Medium HighLog conversion, conversion, conversion, and Value of Low Priority 2nd Priority Top PriorityData Modeling Customer Low value, Low value, Low value, Low Medium High Survey conversion, conversion, conversion, Data Low Priority Low Priority 2nd Priority Purchased Low Medium High Data Propensity to ConvertAnalytics: A Cross-Functional Solution to Information Overload © Robert E. Nolan Company | Page 22
    • Case Study B: Agency Management60% of customers would switch carriers if so advised by their agent.(Source: JD Power & Associates)33%+ of agents are likely to change insurance carriers.(Source: National Underwriter and Deloitte)Insurers better manage their agents achieve competitive advantage.New customers have high acquisition costs, retaining one more profitable.New agents have high acquisition expenses and pose a greater risk ofinferior retention rates, resulting in lower profits.Monitoring effectiveness of agents provide early warning that an agent maybe about to leave, triggering action and market differentiation.Predictive scorecards tie traditional features like traffic lights andspeedometers to powerful analytics.  Dashboard visuals provided at-a-glance access to the current status of new KPIs, with automatic alerts for underperforming objectives and strategies.Implemented an agency dashboard based on new KPI’s that weremodeled with a predictive analytics tool.Analytics: A Cross-Functional Solution to Information Overload 23 © Robert E. Nolan Company | Page 23 June 2012
    • Case Study B: Agency Management © 24 Robert E. Nolan Company | Page 24Analytics: A Cross-Functional Solution to Information Overload
    • Case Study C: Loss based Pricing Territory average loss ratios generate prices that are too high for some and too low for others. $812.50 Detailed risk $438.00 analytics generate more accurate loss cost estimates by $1187.00 discrete segments of business. Result: More equitable and competitive risk adjusted pricing. ISO Price Analyzer Tool used for graphics © 25 Robert E. Nolan Company | Page 25Analytics: A Cross-Functional Solution to Information Overload
    • Case Study D: Retention Strategies Step 1: Determine Life time Value Post Purchase Activity – Increases in Future predictive value Value over time as behavioral patterns develop Predictive Analysis Customer behavior shifts focus from Time of current to future Purchase value Demographics Current -Loses predictive Value value over time as relevance is superseded by inforce behaviors 26 Robert E. Nolan Company | Page 26 ©Analytics: A Cross-Functional Solution to Information Overload
    • Case Study D: Retention Strategies Step 2: Predict Potential LapseSource of Businessinfluences lapse tendenciesbased on channel behaviors Predictive Analysis – Model ChannelTransaction behavior andinfluences lapse tendenciesper consumer behaviors Consumer Behaviors © 27 Robert E. Nolan Company | Page 27Analytics: A Cross-Functional Solution to Information Overload
    • Case Study D: Retention Strategies Step 3: Develop Strategy Matrix Match effort to risk and value – •High value low risk gets medium effort, save money on retaining low risk customers •Low value customers get low cost efforts across the board •Targeted high efforts on high value / high risk © 28 Robert E. Nolan Company | Page 28Analytics: A Cross-Functional Solution to Information Overload
    • Case Study E: Claims Fraud • About 10% of all insurance claims are fraudulent. • Annual fraud losses for P&C industry total $30B in US alone. • Need to detect unknown patterns of financial fraud. • Keep track of new fraud schemes. • Unsure exactly what to look for. • Rules: Captures fraud on known patterns previously used Ex: Two claims in different time zones within short window • Anomaly Detection: Detect unknown patterns (ind & aggr) Ex: Statistics (mean, std dev, uni/multivariates, regression) • Advanced Analytics: Detect complex patterns Ex: Knowledge discovery, data mining, predictive assessment • Social Network Analytics: Determine associative links Ex: Knowledge discovery via associative link analysis (entity map)Analytics: A Cross-Functional Solution to Information Overload © Robert E. Nolan Company | Page 29
    • Automated Fraud Detection Points Re-estimate durationPrioritized investigation SIU Reassess loss reservingFocus on organized Prioritize resourcesfraud Fraudulent rescoringMinimize claim padding Review litigationReduce false positives propensity Fraud Referrals Fraud Referrals FNOL Assign Evaluate Update Close Claim Claim Claim Claim Fast TrackPredict duration Claim Cross-sell options forForecast loss reserves Negotiate / satisfied customer Customer retentionOptimize fast track InitiateclaimsPrioritize resources Services Identify salvage andFraudulent scoring subrogation opportunities Initiate Indicate deviationsLitigation propensity Reports on overrides Settleme © 30 Robert E. Nolan Company | Page 30 Analytics: A Cross-Functional Solution to Information Overload nt
    • Claims Analytics: Fraud Red Flag DashboardAnalytics: A Cross-Functional Solution to Information OverloadCourtesy of Attensity © 31 Robert E. Nolan Company | Page 31 June 2012
    • Other Brief Claims ExamplesOptimized Claims Adjudication process.Using data mining to cluster and group claims by loss characteristics(such as loss type, location and time of loss, etc.).Claims scored, prioritized and assigned by experience and loss type.Higher quality, more consistent, and faster claims handling.Adjuster Effectiveness Measurement.Adjusters typically evaluated based on an open/closed claims ratio.Analytics create key performance indicator (KPI) reports based oncustomer satisfaction, overridden settlements and other metrics.Claims using attorneys often 2X settlement and expenses.Analytics help determine which claims are likely to result in litigation.Assign to senior adjusters to settle sooner and for lower amounts.Analytics: A Cross-Functional Solution to Information Overload 32 © Robert E. Nolan Company | Page 32
    • Case Study G: Life Underwriting via App + Social Data Second child born last year Actively High investment risk tolerance pursue for Lived in home 2 years issuance of a Owns home preferred Commuting distance 1 mile policy without Reads Design and Travel Magazines requiring Urban single cluster fluids or Premium bank card medical Good financial indicators records. Active lifestyle: Run, Bike, Tennis, Use strong Aerobics Health food choices retention Little to no television consumption tactics.Life UW using a GLM predictive model to assess risk:Use info on app plus social data, No fluids or filesIntegrate 3rd party publicly available information. © 33 Robert E. Nolan Company | Page 33Analytics: A Cross-Functional Solution to Information Overload
    • Case Study: Life Underwriting via App + Social Data Current residence four years Do not send Lived in same hometown 15 years offers. Do not Currently renting pursue Commuting distance 45 miles Works as administrative assistant aggressive Divorced with no children retention Foreclosure/bankruptcy indicators strategies. If Avid book reader applies, Fast food purchaser pursue Purchases diet, weight loss equipment additional Walks for health medical High television consumption records and Low regional economic growth tests. Light wine drinkerIn a test over 30,000 applicants, behavioral and lifestylefactors provided 37% of the risk assessment influence andperformed as well as additional, more intrusive medicaltests and fluids.Analytics: A Cross-Functional Solution to Information Overload © Robert E. Nolan Company | Page 34
    • Types of third party marketing data Deloitte Predictive Model for Life © 35 Robert E. Nolan Company | Page 35Analytics: A Cross-Functional Solution to Information Overload
    • Life Underwriting Savings: Using 3rd Party Data versus Medical Data Deloitte Predictive Model for Life © 36 Robert E. Nolan Company | Page 36Analytics: A Cross-Functional Solution to Information Overload
    • Workers Comp already has a track record of using Social Data © 37 Robert E. Nolan Company | Page 37Analytics: A Cross-Functional Solution to Information Overload
    • Social Analytics: Customer Engagement Dashboard Automatically monitor social conversations Filter out irrelevant posts Analyze posts to extract key insights Engage customers with proactive outreach Improve experience customers are having on the site Improve brand image and emphasize business legitimacy Analytics: A Cross-Functional Solution to Information Overload © 38 Robert E. Nolan Company | Page 38
    • Social Analytics: Conversation Sentiment Tracking Courtesy of AttensityAnalytics: A Cross-Functional Solution to Information Overload © 39 Robert E. Nolan Company | Page 39
    • Social Analytics: Website Sentiment by LOB Courtesy of AttensityAnalytics: A Cross-Functional Solution to Information Overload © 40 Robert E. Nolan Company | Page 40
    • Available Third Party Data is ExtensiveThird party marketing datasets are often used to develop the predictivemodels, they include over 3,000 fields of data, contain no PHI, are notsubject to FCRA requirements, and do not require signature authority.The match rate with insured’s is typically around 95% based only onname and address. Third party marketing data includes: Survey Data: •Self-reported informationRewards programs •Contains many lifestyle elementsMagazine subscriptions Basic demographicsEmail lists •Age, sex, number & ages of kids, maritalWebsites statusGrocery store cards •Occupation categories, education levelBook store cards Financial informationPublic records •Income level, net worth, savings, investments •Home value, mortgage value, credit card info Lifestyle data •Activity: running, golf, tennis, biking, hiking, etc. Robert E. Nolan Company | Page 41 © •Inactivity: TV, computers, video games,
    • Social Analytics: Overall Sentiment Ratings DashboardAnalytics: A Cross-Functional Solution to Information Overload © 42 Robert E. Nolan Company | Page 42
    • Social Analytics: Competitive Sentiment Dashboard Courtesy of Attensity © 43 Robert E. Nolan Company | Page 43Analytics: A Cross-Functional Solution to Information Overload June 2012
    • Closing Notes: Bloomberg Qualitative Research Findings Analytics rapidly advancing past “emerging stage” Organizations proceeding cautiously in adoption Business experience driving factor in decision making Analytics for big issues, focus on improving bottom line Key adoption challenges: – Data quality, acquisition, integration – Many carriers lack proper analytical talent – Culture critical – Executive sponsorship key – Start small, work bigAnalytics: A Cross-Functional Solution to Information Overload © Robert E. Nolan Company | Page 44
    • 3 Guidelines to Implementing Analytics1. Have executive sponsored roadmap clearly outlining:  What resources will be needed for how long,  Where and when predictive analytics will be used,  Which tools will be used, and  How will success be measured.1. Use data that is comprehensive, accurate, and current.  Not necessarily 100%, some have used only 70%.  Must be representative.§ Staff with talented and engaged people. 1. Completely understand business problem, proficient with analytics. 2. Every person does not have to meet both qualification. 3. A team can be used with some business and some analytics experts.Analytics: A Cross-Functional Solution to Information Overload 45 © Robert E. Nolan Company | Page 45June 2012
    • Questions? Thank You... Steve Callahan, CMC Practice Director steve_callahan@renolan.com www.linkedin.com/in/stevenmcallahan @stevenmcallahan (206) 619-7740Analytics: A Cross-Functional Solution to Information Overload © Robert E. Nolan Company | Page 46