With the ongoing development of our EiB Insurance Analytics solution, which provides automated premiums and claims management information (MI) for MGAs, Insurers and Brokers, we have recognised a trend in the challenges faced across the sector with regards to the issue of data quality. With this in mind, a few months ago we commissioned a report exploring the impact of data quality in the insurance industry, the role of automation in addressing this issue, and the future
The last instalment in our EiB Insights series, explored how our EiB Insurance Analytics solution allows you to access your raw premiums and claims bordereau and automatically transform this into powerful MI, without the arduous task of manually handling your data. Our focus now turns to the pertinent topic of what happens when your raw data is in fact erroneous data. After all, if the base data is flawed, then regardless of
Bad data…I feel your pain. But there is light at the end of the seemingly dark tunnel… Having worked with countless insurance companies over the years, I am pleased to assuringly inform you that the future of MI is a lot less daunting and time consuming as you all may think! Here are a few insights which I have gained as to why I believe this to be… Full Automation Of MI Sounds obvious, but I what I have repeatedly witnessed in
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