Discover the customer behind the data
In this day and age it is getting easier and less expensive to collect all kinds of data. But what matters is not how much data you can amass but what you do with this data. How can you use the data of past, present and future to gain insight and drive
In my first post I introduced the idea that most “big data” isn’t really big at all, and doesn’t conform to Gartner’s 3V’s. Instead, I've suggested that there’s benefit in focussing on “broad data”, or the use of many different sources of data to give us richer information. We put forward 4O’s of
Insurance companies are working to define solutions that support integration across a number of sources to provide a “360-degree view” of producers and policyholders. This single view brings together information about the policy, claims, billing, interaction, risk profiles, agent and agency
Insurers have relied on black box solutions for Telematics to date. This blog entry will examine the use of SmartPhones as an alternative to the black box and how it may benefit both the Insurer and the Consumer.
The cost of entry into the Telematics market for Insurers has been high to date,
Co-authored by Kim Minor, Worldwide Industry Marketing Manager for Insurance at IBM.
Claims fraud is an important topic, so we’ve written about it several times before. In this blog, I want to discuss how IBM big data capabilities can augment an existing fraud system at any insurer. By wrapping
Analytics solutions designed to handle the volume and variety of data available today also help insurance companies improve catastrophe risk modeling, through which companies determine the exposure of current policies and predict the probable maximum loss (PML) from a catastrophic event.
Motor insurance policies are traditionally priced on forecast risk - using rating factors such as number of miles you might drive, where you live, your age, the engine size and what you will use the car for - customers then pay a premium based on these values - however the introduction of
When was the last time that you looked at one thing? Just one thing, nothing else? We seldom look at just one thing, but rather look at ‘a thing’ in terms of its relationship with ourselves and with everything around us and it. Even in looking at a photograph, don’t we also think of the photograph
Solutions for analyzing big data can play a critical role in addressing the increasing prevalence of claims fraud. Traditionally, fraud is estimated to account for approximately 10 percent of insurance company losses, and that percentage is rising. Insurance companies need ways to quickly
Visitors to the London-based Chartered Institute of Insurance are able to visit the small museum, which includes policy documents and ‘contracts of insurance’ going back 300 hundred years,
These documents are, in numbers of years, as far away from Gutenberg’s printing press of 1439 as we are today
In my previous two blogs [here and here], I’ve talked about how cognitive computing and big data present the insurance industry with great opportunities and some challenges. To develop strategies that capitalize on the potential gold mine of information that big data represents, many carriers will
Almost my whole working life has been spent in the insurance industry, and in the early days, we thought we were being ‘cutting edge’ when using fax and telex. Now, after 30 years, the insurance sector is sitting in the centre of a new industrial revolution called ‘analytics’.
“Organizations around the world lose an estimated five percent of their annual revenues to fraud, according to a survey of Certified Fraud Examiners (CFEs) who investigated cases between January 2010 and December 2011. Applied to the estimated 2011 Gross World Product, this figure translates to a
This morning I read this post on Toolbox
Self-Service Business Intelligence is…
- A win-win for IT and business professionals
- A trend that could possibly threaten some IT professionals’ livelihoods
- A disaster waiting to happen…sounds like a reporting nightmare
What do you think and
What if insurance companies could simultaneously improve customer satisfaction, retain valuable policyholders and maximize cross- and up-sell opportunities?
To achieve these goals, insurers need ways to anticipate customer needs and determine the next best action for each individual customer.