Big Data & Analytics - What is it and How does it matter to Insurance?
This document discusses how big data analytics can help build strategic intelligence in the insurance industry. It provides an overview of big data characteristics, the rise of devices connected to the internet of things, and how ingestible sensors can collect health data from individuals. The document then discusses how insurance companies can collect large amounts of customer, driver, and home usage data from these sources. It introduces concepts of data science, the data value chain, and different types of data analytics including descriptive, diagnostic, predictive, and prescriptive analytics. Examples are given of how predictive policing and claim fraud analysis use big data. The document advocates that insurers apply analytics across various functions and adopt a digital, data-driven organizational model with computer science programs focused
Big Data & Analytics - What is it and How does it matter to Insurance?
- 1. BUILDING STRATEGIC INTELLIGENCE IN INSURANCE BIZ THROUGH BIG DATA ANALYTICS BIG DATA & ANALYTICS: WHAT IS IT AND HOW DOES IT MATTER? Head of Department Dept. of Computer Engineering Faculty of Engineering Chulalongkorn University natawut.n@chula.ac.th @natawutn http://natawutn.wordpress.com http://www.slideshare.net/natawutnupairoj Asst. Prof. Natawut Nupairoj, Ph.D.
- 3. Something that cannot be processed within reasonable time using 2-3 servers
- 9. IOT: THE RISE OF DEVICES Wearable devices’ shipment will be doubled in 4 years 20% will be healthcare related devices
- 10. IOS HEALTH
- 12. INTRODUCING FDA-APPROVED INGESTIBLE SENSORS IN PILLS http://www.forbes.com/sites/singularity/2012/08/09/no-more-skipping-your-medicine-fda-approves-first-digital-pill/
- 16. WHAT CAN WE COLLECT FROM THESE SENSORS? Customers’ Information • Preferences, Activities & Habits, Hobbies, Important Events, Health, Friends Drivers’ Information • Driving Behaviors, Time on the Road, Frequent Visiting Places, Car Information Homes’ Information • Usages Information, Security Status, Owners’ Behaviors But, we are talking about MASSIVE AMOUNT OF DATA
- 17. Data Science (Data Analytics) Data Engineering (Big Data)
- 18. DATA VALUE CHAIN Source: http://steinvox.com/blog/big-data-and-analytics-the-analytics-value-chain/
- 19. DATA ANALYTICS SIMPLIFIED Descriptive • “A.Natawut drinks about 1 cup of coffee a day” Diagnostic • “Number of cups that A.Natawut drinks depend on number of meetings he has each day” Predictive • “Tomorrow, A.Natawut has 2 meetings, it is very likely that A.Natawut will drink 2 cups tomorrow” Prescriptive • “Inform secretary to prepare 1 cup in the morning and one in the afternoon for A.Natawut”
- 20. TYPES OF DATA ANALYTICS
- 22. CASE STUDY: PREDICTIVE POLICING Being used by 60 cities in the US e.g. Atlanta, LA, etc. Source: http://www.forbes.com/sites/ellenhuet/2015/02/11/predpol-predictive-policing
- 25. Source: Capgemini, “The Disruptive Impact of Big Data and Analytics in Insurance”, June 2015 BIG DATA ANALYTICS AND CLAIM FRAUD ANALYSIS
- 26. SURVEY: FUNCTIONS IN WHICH INSURERS APPLY DATA ANALYTICS?
- 27. Digital Data Driven Organization
- 28. CS PROGRAM Architecture Track • Map/Reduced • In-Memory Processing • Cloud Computing • Mobile and Networks Analytics Track • Machine Learning • Data Mining • Big Data Analytics • Social Network Analysis