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P 01 ins_analytics_ai_in_life_case_studies_2017_10_16_v12

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AI in Life Insurance Case Studies

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P 01 ins_analytics_ai_in_life_case_studies_2017_10_16_v12

  1. 1. 1 AI IN LIFE INSURANCE CASE STUDIES Vishwa Kolla Head, Advanced Analytics John Hancock Insurance
  2. 2. 2 TOPICS Background Landscape Case Studies
  3. 3. 3 BIG DATA or ANALYTICS or DATA SCIENCE or AI or AA – WHAT IS IT? CAMPAIGN NUDGE OPS - INTEG APPS APPLICATIONS BI STRATEGY INSIGHTS RECOMMEND Data Math Code AA = COMBINE DATA AND MATH USING CODE TO DRIVE BUSINESS VALUE
  4. 4. 4 2001 – 2013 CAGR Revenue (Firm | Industry) Source: 2001 – 2013 Revenue figures from Capital IQ 3% 3% 3% 1% 5% 7% 7% 8% 10% 12% INTEGRATING AI EFFECTIVELY UNLOCKS VALUE
  5. 5. 5 AI IS VERY OLD Source: https://blogs.nvidia.com/blog/2016/07/29/whats-difference-artificial-intelligence-machine-learning-deep-learning-ai/ Most Operate here
  6. 6. 6 DATA IS UBIQUTOUS
  7. 7. 7 COMPUTATIONAL POWER IS INCREASING EXPONENTIALLY Number of Calculations Per Second Per $1000 Source: The zettabyte era: Trends and analysis, Cisco, updated June 7, 2017’ United Nations; MMC Ventures; Nvidia; McKinsey Global Institute analysis
  8. 8. 8 ALGORITHMS ARE GETTING BETTER Source: The zettabyte era: Trends and analysis, Cisco, updated June 7, 2017’ United Nations; MMC Ventures; Nvidia; McKinsey Global Institute analysis
  9. 9. 9 AI ELEMENTS AI ELEMENTS MACHINE AND DEEP LEARNING IOT, RPA, AUTONOMOUS VECHILES CHAT BOTS COMPUTER VISIONNATURAL LANGUAGE
  10. 10. 10 MACHINE LEARNING IS WHERE IT ALL STARTS Machine Learning Supervised Learning Classification SVM Discriminant Analysis Naïve Bayes Nearest Neighbor Regression Linear, GLM Trees (RF, GBM) Ensemble Neural Networks Un- supervised Learning Clustering K-Means / K-Medioids Hierarchical Neural Networks Machine Learning (ML) gives computers (machine) ability to learn (learning) without being explicitly programmed (learning) Arthur Samuel, 1959
  11. 11. 11 DEEP LEARNING IS THE NEXT FRONTIER © Andrew Ng When you hear the term deep learning, just think of a large deep neural net. Deep refers to the number of layers typically and so this kind of the popular term that’s been adopted in the press. I think of them as deep neural networks generally. - Jeff Dean Source: https://www.youtube.com/watch?v=QSaZGT4-6EY MULTI-LAYER PERCEPTRONS CONVOLUTIONAL NEURAL NETWORKS RECURRENT NEURAL NETWORKS
  12. 12. 12 AI SYSTEMS MAKE IT REAL IOT, RPA, AUTONOMOUSML, DL VISION & LANGUAGE CHAT BOTS TARGETING UNDERWRITING CLAIM HANDLING CYBER SECURITYFRAUD CALL CENTER APP FORM EDA / LOOKUPS CLAIMS ADJUDICATION APS MEETINGS CONNECTED HOME CONNECTED HEALTH OCR CONNECTED CARS MORTALITY RISK MORBIDITY RISK ANNOTATION PAY AS YOU GO NOT EXHAUSTIVE
  13. 13. 13 TOPICS Background Landscape Case Studies
  14. 14. Source: Suncorp Group, The Changing Face of the Insurance Customer, 2013 Can I try before I buy? What are my friends doing? I want a seamless experience across devices I want options How does this help me? I want to be valued I prefer Value to Brand I want to buy in 2 days SATISFY THE SEGMENT OF 1
  15. 15. 15 USE CASES IN LIFE INSURANCE PROSPECTING NURTUREACQUISITION MARKET SEGMENTS CUSTOMER SEGMENTS LIKELY TO [*] MEDIA MIX CHANNEL SURVEY ANALYTICS CROSS / UP- SELL OCR MISREP LIKELIHOOD MORTALITY APS SUMMARY FLUIDLESS SMOKER LIKELIHOOD MORBIDITY CHURN NEXT BEST OFFER CLAIM LIKELI- HOOD JOURNEY CLAIM SEVERITY NEXT BEST ACTION FRAUD >> TEXT ANALYTICS OPTIMIZE NEXT LIKELY ACTION WELLNESS IOT ANALYTICS NPS ANOMALY >>
  16. 16. 16 TOPICS Background Landscape Case Studies
  17. 17. TODAY’S PERCEPTIONS ABOUT LIFE INSURANCE
  18. 18. 18 “Life insurance ranks at the top of the list of things consumers know they probably should buy, but get no personal enjoyment from whatsoever. There's just no happy way to look at life insurance. In the best-case scenario, life insurance is just another bill to pay. And in the worst case, your family collects the benefits, but unfortunately you're dead.” Source: USA Today, Knowing when you need life insurance, September 19, 2013
  19. 19. 19 ACQUISITION ON DIGITAL CHANNEL IS CRITICAL
  20. 20. 20 LOOK ALIKE MODELS SEEMED LIKE A GOOD START > Source: Krux.com
  21. 21. 21 THEY WERE NOT ENOUGH
  22. 22. 22 Capitalism is under siege. Diminished trust in business is causing political leaders to set policies that sap economic growth … Business is caught in a vicious circle … The purpose of the corporation must be redefined around … CREATING SHARED VALUE Michael E. Porter and Mark Kramer, Jan-Feb 2011
  23. 23. 23 Link
  24. 24. 24 AI HELPS MAKE UW PROCESS MORE EFFICIENT Decision Acquired Scheduled UnderwriterApplicant Part I Typically 3-6 weeks Process Bottle neck Traditional Process End to End Turn Around Time = Hours to 3 - 6 weeks Consent Proxy for Cholesterol, Glucose, Nicotine Likely to misrepresent Adjustment for Height and Weight Other issues found after roll out Encourages healthy people to apply
  25. 25. 25 MAN – MACHINE COMBO SPEEDS UP SUSPICIOUS PATTERN DETECTION not pay NOT PAYING not payable NOT PAYING not payble NOT PAYING not paycheck NOT PAYING not payment NOT PAYING not payout NOT PAYING not payroll NOT PAYING payment not NOT PAYING absence pay NOT PAYING absent pay NOT PAYING withhold payment NOT PAYING pay unpaid NOT PAYING unpaid pay NOT PAYING Check for keyword ‘Not Paying’ Use deep learning to find exact words / patterns Identify useful patterns Identify claims associated with the identified patterns Business checks flagged cases Reports cases to BUIBusiness uses expert knowledge to provide directional guidance Machine only Man + Machine Use deep learning to find similar words/patterns Reports cases To BUI Use all unstructured text as input to DL Select A few datasets
  26. 26. 26 ROBUST DATA ECOSYSTEMS ARE A FORTUTIOUS OUTCOME
  27. 27. 27 D E V E L O P AI-enhanced roadmap C O L L A B O R A T E to create shared value S H A P E your value delivery SUMMARY

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