Sign up and be the first to know

About Hugh Terry & The Digital Insurer

Hugh Terry & The Digital Insurer Video

Contact Us

1 Scotts Road
#24-10 Shaw Centre
Singapore 228208

Write an article

Get in touch with the editor Martin Kornacki

email your ideas at [email protected]

Pre Registration Popup

itcasia2020 Registration Popup

Share Popup

Prime Member: Find out more

Access a unique programme!
  • 56 pre recorded lesson of online content from industry experts over 7 courses
  • The best in digital insurance for practitioners and by practtioners
  • Online MCQ after each lesson
  • Join the discussion forum and make new friends
  • Certificate upon completion to show your expertise and comitment
  • 3 months to complete
  • Normal price US$1,400 Your Prime member price is US$999
  • Access to future versions included in your Prime membership!
Become a member

Prime Member: Contact Us

REach out to us. Please fill up the form below
  • Let us know how we can help. You can expect a response within 24 hours

Driving Increased Customer Value with Advanced Analytics – IBM

Article Synopsis :

Digitisation has given birth to hybrid customers and valuable data is being generated at each digital touch point. With the help of Predictive analytics tools this data can be intercepted and analysed for sustainable competitive advantage.Insurers can develop a comprehensive 360 degree profile of the customer and utilize analytics to gain deeper insight.

Integrating Multiple Sources of Data is a Prerequisite

As data is at the heart of predictive analytics it’s logical to identify the various data sources. On page 12 of his report “Predicting success: Driving Increased Customer Value with Advanced Analytics”, Colin Shearer from IBM outlines the data sources from various customer interactions. As per report the data sources which should act as the basis of analytics for 360 degree customer view are:

1. Interaction data – E-Mail / chat transcripts, Call Center notes, Web Click-streams, In person dialogues
2. Attitudinal data
Opinions, Preferences, Needs & Desires
3. Descriptive data
Attributes, Characteristics, Self-declared info, (Geo) demographics
4. Behavioural data
Orders, Transactions, Payment history, Usage history

On page 17, the author also details the important barriers to adoption of predictive analytics by organizations i.e.
1. Cost
2. Dependence on IT
3. Need for Analytical Expertise
4. Time to value

The report focuses on the power of analytics to attract and retain more of the right type of customers that will drive profits to the business

Link to Full Article:: click here

Digital Insurer's Comments

For an accurate 360-degree customer view, insurers must understand the fundamental role data plays and address the hurdles commonly encountered in the predictive analytics process. Important hurdles insurers will face are:

1. Collating customer data from various digital touch points into a single database
2. Filtering duplicate data
3. Carrying out the necessary analysis and building the appropriate model

Link to Source:: click here



Livefest 2019 Register Popup Event

Livefest 2019 Already Registered Popup Event

Livefest 2019 Join Live Logged-in Not Registered

Livefest 2019 Join Live Not Logged-in