Claim process reengineering – what about the data?
There is no secret that legacy systems have resulted in business processes consisting of many manual tasks and fixes across the P&C industry. As processes are being reengineered, insurers should consider the flow and quality of the data in the process. How data is collected coupled with the system’s ability to manage the data will determine whether data can be extracted and leveraged for analysis and decision making.
Insufficient claim data continues to make it hard for carriers to enable data driven decisions across several departments spanning from claims to underwriting.
We think carriers should consider three key aspects from a data perspective before reengineering a process within claims:
#1: What data do you need from the process, now and in the future?
Before defining the claim process, or sub-process, consider if the data involved in the process is critical for decision making or whether the data can enable other process updates, now or in the future. As an example – by defining a claim process where you will not be able to easily extract and analyze the claimed objects, you might complicate your fraud efforts or product adjustments.
#2: Who needs the data?
Like above, when defining a claim process look beyond the claim department to understand what data they can leverage from the process. While the claim department might not see a need for a particular data – this data might be a game changer for other departments, such as actuaries, risk, and product.
#3: Can the technology provider in the process enable effective data output?
While spreadsheets or a legacy solution might solve the immediate problem in the process, they might not serve your data need. As an example – using a spreadsheet or legacy system to document structural damage or content loss might work to settle the claim today while most likely not enable effective and automated aggregation and analysis of the claim data.
It is time for carriers to stop guessing and start making data driven decisions based on accurate and accessible claim data.
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