The insurance industry has always been data-driven. To approve claims, policies, and determine premiums, insurers must analyze thousands of documents effectively and properly interpret the information to make it actionable.
Here is a particular example of how we used data analytics to enable an organisation that dealt predominately with healthcare insurance claims to leverage data to achieve their goals.
Minimise loss from claims. Their objectives were reduce number of claims per customer and adjust policy premiums where claim costs were high. In order to achieve this we worked with the Chief Data Officer and his team to define the KPI’s that would enable his team to evaluate the data and make informed decisions on behalf of the organisation that would align and help achieve their objectives.
Example Dashboard (sample data)
|Reduce the number of claims per customer||Total # Claims||[# of unique Claim_Key]|
|# of claims per client||[# of unique Claim_Key]/[# of unique ClientID]|
|Claims Year on Year (Number)||[# of unique Claim_Key] Comparison WeekID|
|Top 5 policy types of claims (# of claims)||[# of unique Claim_Key] Ranked|
|Claims by gender/Area||[# of unique Claim_Key]|
|Adjust policy premiums where claims costs are high||Cost||[Total Claim/Amount]|
|Avg per customer||[ClaimAmount]/[# Unique ClientID]|
|Top 5 policy type by cost of claims||[Total Claim/Amount] Ranked|
|Claim by gender||[Total Claim/Amount]|