Of all the processes inherent to insurance, it could be argued that none are more important than the claims process. I was reminded of this by two recent conversations I had with customers and colleagues.
The claims process is typically time-consuming and labor-intensive, involving multiple systems, outdated technology and distributed operational units. The resulting inconsistent processes and inefficient data management sap resources and slow turnaround times, which leads to poor customer service. This feeling was echoed by a conversation with my colleague’s regarding his insurance claims experience. His son was involved in a car accident that resulting in his vehicle being written off. In the days and weeks after the accident he would complain (mostly to me) and get more frustrated with the carrier as he dealt with different departments (adjuster, total loss group, subrogation division) and what he felt like were out-dated processes. In the end the carrier and my colleague came to a fair settlement, but not after he felt like he had jumped through multiple hoops and probably resulting in a negative customer experience.
The general consensus is that claims typically account for up to 80% of an insurance company’s costs. When it is stated like that, 80% does seem like an exceptionally large number. But when you start to translate that percentage to premium revenue you realize that the claims operations in most insurance companies are huge. Which brings me to my second conversations, this time with a customer, who indicated that their claims department represented $19bn and employed 11,000 people. I was like WOW, that is bigger that probably 99.9% of all companies. Of course this customer was a global multi-line carrier, but even for a mono-line insurance company the claims process can represents hundreds of millions of dollars.
Now this is not news to most insurers and over the past few years many have made a lot of enhancements in claims processes but there is still room for improvement and one answer is analytics.
Predictive insurance claims processing, or claims analytics, is the process to analyze the structured and unstructured data at all stages in the claims cycle to make the right decision, at the right time, for the right party. Claims analytics can enhance the bottom line by:
- Reducing settlement lags and claims payout.
- Automatically assigning adjusters according to priority and skill set.
- Analyzing claim data to help with subrogation.
- Reviewing claims for litigation propensity
- Fighting increasingly sophisticated fraud.
Adding analytics to the claims life cycle can deliver a measurable ROI with cost savings and increased profits; just a 1 percent improvement in the claims ratio for a $1 billion insurer is worth more than $7 million on the bottom line.
For more information about how analytics can help with optimizing claims read this white paper.