Big Data is making the news in all sorts of ways. It is being used by actuaries and underwriters to fine-tune selection and become more precise in pricing. It allows claims examiners to detect fraud patterns and lower costs. Marketers can predict patterns of consumer behaviour from Big Data to tailor campaigns to increase sales.
Does this mean Big Data projects should take prominence over other initiatives? Experts are suggesting that resolving how Big Data works with existing or planned operational systems is critical to achieving real, sustainable benefits. We’d like your thoughts on this.
Reminder: Modern Core Systems Are Necessary…
A large proportion of the P&C insurance community has undertaken core systems replacement for very good reasons: We cannot expect our customers to remain loyal without modern administration systems that allow proper levels of service. As we noted in this space earlier this year, modernization is a big, important, and continuing journey.
Bottom line: modern core systems are table stakes.
… But Not sufficient
Marcus Ryu, CEO Guidewire, said it best in his interview with Insurance & Technology last fall: In a world of vastly increasing amounts of data, “core system are not enough”. Adding that the world has changed and customers are now asking “how can this operational environment be much more aware and integrated with all these proliferating phenomena outside.”
So How Do Priorities Get Made?
Not even the largest organization has unlimited resources. So how do priorities get made? If there is a choice between Core Systems Replacement and Big Data Analytics, there may be a more fundamental decision to be made: Does the organization have the proper architecture to move forward?
With a comprehensive MDM process, integrating the operational data with Big Data and the required analytic capabilities becomes more straight forward. (Note we didn’t say easy.)
In the case of Guidewire, after it discovered that its investment in developing core systems was not meeting the needs, it undertook to build additional capabilities to extend its data models which ultimately became Guidewire Live.
The alternative to this is to continue to develop silos of applications. The difference this time is that the silos are not defined by lines-of-business, but by functional capabilities.
What Do You Think?
If you are implementing Big Data Analytics how are these relating to exiting or planned Core Systems replacement projects? Do you have tips that have helped you?