Employing Data Analytics to Create a Customer-Centricity for Insurers

Transcription

1 Employing Data Analytics to Create a Customer-Centricity for Insurers Dr. Toa Charm Founder & Chairperson, BI and Big Data SIG Vice President (Professional Development) Hong Kong Computer Society DBA, MBA, B.Sc., CBIP (TDWI), Big Data Cert. (MIT) Jun 11, 2014 Hong Kong [email protected]

2 Dr. Toa Charm 湛家揚博士 Founder & Chairperson, BI and Big Data SIG Hong Kong Computer Society DBA, MBA, B.Sc., CBIP (TDWI), Big Data Certification (MIT) Industry Experience in Business Intelligence and Big Data Associate Partner, Business Analytics, Greater China, IBM GBS Regional Head of BI Competency Centre (BICC), Asia Pacific, HSBC General Manager, Business Intelligence, Greater China, Oracle Managing Director, Greater China, Hyperion General Manager, Asia Pacific, Kingdee International Group Accomplishment in Business Intelligence and Big Data Established 1st Business Intelligence Competency Centre (BICC) in HSBC Asia Pacific Founder and Chairperson, BI Special Interest Group, Hong Kong Computer Society Won Hong Kong Computerworld Best BI Award, Hyperion s Asia/Pacific Best Partnership Award, Hyperion s Best Marketing & Best Consulting Award Forum Chairs/Moderators: Big Data Business Forum (US), Hong Kong BI and Analytics Forum ( ), Retail Analytics Forum, Cloud Asia, Insurance Analytics, Finance Innovation, BankTech Forum, etc. Qualification and Publications Doctor of Business Administration, MBA, B.Sc. Doctoral Thesis: Impact of Organizational Capabilities on Business Intelligence Maturity and Customer Relationship Management Performance Author of two books to be published in 2014 Strategic Success of BI and Big Data Journey in Greater China and Strategy - Make or Break Our Company and Career Lives. Adjunct Professorship: University of Hong Kong, Fudan University (Shanghai), University of Macau Completed senior executive programs from Harvard, UC-Berkeley, MIT, CEIBS

3 Today s Agenda Big Data Collaborations in Hong Kong A Sense of Urgency for Insurers Innovative Use of Big Data in Financial Services Watch out the Double-Edged Sword

4 Hong Kong Computer Society Special Interest Groups (SIG) BISIG Business Intelligence and Big Data SIG EASIG Enterprise Architecture SIG MoSIG Mobility SIG SMSIG Social Media SIG CCSIG Cloud Computing SIG ISSIG Information Security SIG QMSIG Quality Management SIG DESIG Digital Entertainment SIG SMGSIG Service Management SIG Industry Advisors Financial Services Logistics & Transport Retail & Hospitality Health Care

5 BISIG BI & Big Data Special Interest Group Site Visits (e.g. GP, TVB, HKAA, etc.) Big Data Competition for Students Big Data Mentorship to University Students Talks to Business, IT and Academia Big Data Workshops Advisors, Moderators,Speakers for Big Data Conferences Big Data Survey and Research Big Data Analysts Sharing (e.g. Gartner) Cross-Over Networking with IT & Business Associations

7 C2B > B2C Customer Experience Big Data Analytics is Not an Option

8 Digital Disruption to Traditional Leaders Big Data is the Key for their Successes

9 New Players Disrupt and Re-Set the Rules of Our Games 湛家扬博士 (Dr. Toa Charm)

10 Big Data Innovators and New Challengers Source: Forbes Retrieved from on Jan 18, 2014

11 FinTech s Innovations Disrupt Financial Services Industry WW New entrants are cherry-picking select customer segments and banks are taking notice: 28% of executives mentioned online and mobile players as potential threats wesabe Source: IBM Institute for Business Value analysis, Company web sites and Annual Reports

12 Smart Traditional and Technology Companies Leverage on Big Data to Enter into Financial Services

13 Finance & Insurance has the highest value potential of using big data

14 Big Data Adoption in Asia Pacific - by industry Source: Economist Intelligence Unit 2013

16 BI is Necessary and Good But it is NOT Good Enough All levels are connected by goals, metrics, people & performance Executive A global vision Highlights, Trends, Metrics & Goals Manager & Analyst A consolidated vision Ad-hoc, impact & root cause analysis End User A detailed vision Graphical, user friendly

17 Today s Executive Dashboard shows lag indicators only 湛家扬博士 (Dr. Toa Charm)

18 Analytics formulate objectives and drive actions Business Objective Increase Profitable Revenue through Improved Insight Goals Acquire New Customers Enhance Customer Relationship Activities Develop competitive products and pricing Improve Market Segmentation and Identify customers that meet Company Profile Geographic Expansion / Market Research Leverage Existing Markets for other LoBs Diversify Across Industry Value Chain Contract Agents meeting Company Profile Improve Ease of Doing Business Provide Sales Training and Support Recruit Underwriters with strong industry relationships and/or knowledge Improved Customer Segmentation / Analytics Improved Customer Satisfaction Identify and Retain Customers meeting Company Profile Identify Cross Sell Opportunities Identify and Provide Value-Added Services / Products Improved Agent Segmentation / Analytics Improved Incentive & Goal Setting Identify and Provide Value-Added Services Provide Sales Training and Support Business Lever/Benefits Improve Rating Insight Flexible / Innovative Product Offerings Increase New Business Optimize Agent Production Identify Quality Leads / Referrals Increase Cross Sell and Account Rounding Increase Policy Retention Innovative Service Offerings Increase Profitable Agent Retention Increase # Profitable Agents Traditional BI monitors the results of the activities Metrics Benchmark Rating Loss Ratio Submissions/Quotes/Binders Premium Growth rate Hit Ratio Effective Rate Change* Customer Retention Ratio Customer Satisfaction Score* Agent Retention Ratio Agent Satisfaction Score* Agency Profitability Score* Agency Growth Rate Increase Share of Book Assist with Perpetuation Plans Increase Premium Per Agent % Cross Sell Develop Human Capital / BI Competency Combined Ratio Loss Ratio Trend CUSTOMER AGENTS Client Manage Cost Through Improved Insight Improved Business Management Reporting Optimize Cost to Serve Align Performance Management to Strategic Objectives Reduce Adverse Selection Improve Loss Prevention Performance Management LAE Ratio Expense Ratio Commissions Ratio Employee Turnover

19 Big Data brings us a new set of lead indicators to lead the direction of our business and resources allocation e.g. Customer Segmentation, CLTV, Customer Churn Prediction, Sentiment Analysis 湛家扬博士 (Dr. Toa Charm)

20 Big Data s Value Potential for Insurers

21 Big Data Business Model Maturation Index Measures the degree to which your organization has integrated big data and advanced analytics into your business model Business Metamorphosis Business Monitoring Business Insights Business Optimization Data Monetization Traditional BI Big Data

22 Business Optimization - Next Best Action (NBA) Source: IBM

23 Business Optimization - Next Best Action (NBA) Source: IBM

24 Business Optimization - NBA

25 Event Based Customer Management (EBCM) e.g. Real-time One-Time Insurance (OTI) Translating the Customer Focused Enterprise communication strategy into real actions by using lifecycle event analytics to drive event-based interactions Track communication and client responses to become more effective, iterative, shorter-cycles. Identifying the potential events that may drive a buying episode Understanding that clients are infrequently engaged in buying episodes. Engage the client in a two-way dialogue. Dialogue Tracking Identification Behavior Lifestage, product and behavioral changes can signify when the company could be of service to the client. Focus marketing efforts on those episodes to improve sales, effectiveness, and customer experience Accept that communicating less frequently could be more valuable. Prioritize messages, contacts and channels for optimal results Prioritization Interpretation Interpret these changes (events), their significance to each client, and the opportunity it may represent for the company. Event-based interactions are most effective when implemented as part of an overall client communications strategy that leverages mass (brand) communication and propensity (modeled) communication. 25

26 Business Optimization - Customer Life Cycle

27 Business Optimization - Cross-Selling

28 Business Optimization - Insurance Renewals Two customers with house contents/buildings insurance, due for renewal in the near future Insurer uses predictive analytics to preemptively target customers unlikely to renew Actively manages finances and household affairs. Already shopping around. Retention Offers 1. Cost 44, prob 0.23 Early contact letter: benefits, options Call with favored customer incentive no claims protection, free for 1 year 2. Not applicable 3. Cost 52, prob Cost 67, prob 0.44 Likely to defect? Renewal imminent Current policy holders Retention risk No great awareness of insurance policy, likely to renew by default If female And age And claims > 0 And service_call > 1 And used amount (sentiment NEGATIVE) Then defection risk is HIGH Standard renewal letter: you need do nothing Executive reports on renewal rates and patterns

29 Segmentations Analysis Enabling Partners to Do More Business

30 Risk-Based Premium Pricing for Target Customers Simplistic Pricing Approach Sophisticated Pricing Approach Risk Risk Characteristics Limited data points Simplistic models Coarse grain pricing Product based Driven by collateral valuation Tens to hundreds of price points Example Mortgages Pricing segments Characteristics Many data points Complex models leveraging permutations of many data points Fine grain pricing based on interest rates, fee structures, reward programs, interest free days Micro Segment & Campaign based pricing Driven by ability to repay loan Potentially millions of price points Example Credit cards Pricing segments 30

31 Insurance Companies Use Big Data for Risk Assessment

32 Risk-Based Premium Pricing for Target Customers

33 Two Leading Big Data Fintech Companies ZestFinance and Kabbage

34 Zest Finance Douglas Merrill, CEO of ZestFinance Former Chief Information Officer of Google.

35 Zest Finance - Big Data Based Underwriting Model A new set of underwriting models that allow ZestFinance to extend credit to 25 percent more Americans and increase repayment from customers by 20 percent.

36 Kabbage Small Business Loan

37 Kabbage Partners

38 Behavioral-based Credit Scoring Entrepreneurial Finance Lab, for example, wants to solicit potential borrowers to take psychometric tests to help determine how truthful they are and prescreen their creditworthiness Lenddo analyzes social media data to help score the credit risk of middle class borrowers. RevolutionCredit's software is designed for partner creditors to invite borrowers to view courses at points of transaction, such as when a person takes out a credit card or wants to waive a fee for a one-time late payment. The hope of the young company is to show that a person who is willing to go through one more hurdle is a less risky borrower than his credit score implies.

39 Progressive Auto Insurance - Disruptive Premium Pricing Source:

40 RevolutionCredit Credit Traffic School

41 Centrifuge - Fraud Network Visualization

42 Financial Services Use Analytics to Detect Suspect Employee Behavior Compliance & Due Diligence Ten large U.S. and European banks are using natural language processing technology from Digital Reasoning one of Bank Technology News' 'Top Ten Tech Companies to Watch for 2012' to uncover such revealing documents before lawyers and examiners do.

43 Hearsay Social Social Compilance and Marketing for Financial Services

44 Social Media Online News Social Media Analytics Backend - Building the System Frontend - Discovery Alert Monitor Persistence Queries Analyzing Sentiment Discovery Analyzing Influencers List of Blogs/ Understand Boards Information Extraction Create Point of View Analyzing Taxonomies Analyzing Relationships Discovery Point of View Internal Customer Data News Feed / Wires Targeted Websites Create the Landscape Visual / Faceted Search URL s Discovery Topics

45 Social Media Analytics

46 Simple Free Banking (Freemium Platform Strategy)

48 Target s Pregnancy Predictive Model - Business vs Risk

49 Employing Data Analytics to Create a Customer-Centricity for Insurers Dr. Toa Charm Founder & Chairperson, BI and Big Data SIG Vice President (Professional Development) Hong Kong Computer Society DBA, MBA, B.Sc., CBIP (TDWI), Big Data Cert. (MIT) Jun 11, 2014 Hong Kong [email protected]