Insurance companies offer insurance products that can generally be categorized into one of the following: home owner, personal auto, personal property, commercial auto, commercial property, commercial package, and general liability. However, as insurance companies began to ride the innovation wave a decade or two ago, they started to design products that fit across multiple categories. As an example, many carriers combined homeowner and auto coverage as one policy, rather than two. But beyond combining policies, insurers have also invested, and continue to invest, in new offerings that are reshaping the industry.
Once in a while, I come across an insurer with extremely ambitious plans in terms of the products they would like to offer. However when new products are not thoroughly vetted, these ambitious plans introduce unnecessary risk factors which can lead to financial consequences.
Let me illustrate an aggregation of my observations of new products using a fictitious insurer I’ll call Carrier A. Carrier A has slated several product launches during the next 5 years, including:
To successfully implement these new product lines, Carrier A needs more advanced technology than the legacy systems it is currently operating. To address this technology gap, Carrier A is modernizing their core systems. In addition, Carrier A has conducted some market research and they are quite optimistic about the opportunities that the updated modern platform will offer. They’re certain the new platform is going to help accelerate organic growth and provide returns to shareholders.
Let’s fast forward one year. Carrier A’s core system modernization project is well under way. However, the implementation has been fraught with every conceivable hiccup, including development issues, testing dilemmas, loss of data, production defects, bugs fixes and more. Due to poor planning, the introduction of new systems has destabilized existing processes and delayed the anticipated product line expansion. As a result, the new products cannot be delivered as promised. In addition, existing products are currently experiencing issues affecting the bottom line with incorrect bills sent to policyholders because a concrete data migration strategy was an after thought.
As we all know, there tends to be costs associated with launching anything new. Often times, it is the unknown or better yet, the “unplanned for” that results in delayed launches, budget increases and product feature scope creep. Carrier A unfortunately made an oversight that occurs more frequently than we would expect – not properly planning for how old systems will function and exist when new systems are implemented. As a result, the new platform and the existing systems did not integrate seamlessly. Of course, if this happened to one of your projects, rather than a fictitious carrier, the implications would be far more reaching – irate customers, disappointed shareholders, unmotivated employees, and the list goes on.
During core system migration projects, insurance carriers face many challenges, many of which are the result of poor data reconciliation between disparate systems. Policy, billing and claims must be in sync. Beyond that, your operational data warehouse, downstream applications and general ledger must also be in balance. Some of these may be mainframe systems while others are distributed systems or a combination of the two. Regardless of the type of system, it is crucial for an insurance carrier to incorporate an end-to-end enterprise data analysis platform that can reconcile data across any system, despite data type, to ensure a successful migration project. Such a platform can provide a dashboard that has all the important details specific to each system being monitored, a crucial aspect to any successful migration project. I would recommend that an insurer consider a solution whose dashboard capabilities are similar to a supermarket layout where you can easily navigate from section to section (system to system) depending on what is needed. For example, if a business user was interested in how many personal auto policies were terminated on a single day, it would be easy to analyze the data and find the results.
To conclude, in my years of implementing core system projects, I have found the following details are critical to successful projects:
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