How to Use Data Analytics to Optimize the Claims Process
Data analytics holds the key to a more efficient insurance claims process. Discover how to harness the power of data to improve efficiency, accuracy, and customer service.
For any insurance company looking to streamline its claims management, the effective use of data analytics is key to dramatic improvements in efficiency, accuracy, and customer satisfaction. But using claims data to optimize the claims process requires sifting through data and figuring out which information to use and how (and when) to use it. Dealing with all of that data can be a challenging process.
Today, however, advanced data analytics tools can make a powerful difference in helping claims departments lead positive change resulting in a dramatic impact on their performance.
With that in mind, this post will explore both the potential that advanced data analytics offers claims departments and how to use innovative data-driven tools effectively.
Analyzing claims data
Every insurance claim that an adjuster handles contains data that can be useful to their business. Not only can this data help adjusters improve their job performance, but it can also help their colleagues in other departments, such as underwriting, actuary and sales.
By analyzing and using this data effectively, the adjusters can maximize the speed and accuracy with which they resolve claims. In effect, this use of data can enable even claims adjusters with little professional experience to perform like their expert colleagues. This way, entire insurance claims departments can use data to lower their loss adjustment expenses and help their companies improve profitability.
To make the most of this data, it’s important to keep in mind how broad it can be.
Examples of claims information
Even relatively non complex insurance claims include a rich variety of data that can be useful to adjusters, not only in resolving and investigating the claim at hand but also in improving the resolution of future claims.
The basic information that can typically be found in even the least complex claims includes:
- The claimant’s personal information (such as name, address, etc.)
- The date and time of the incident
- A description of the incident
- The location of the incident
- The amount of damages
- Policy information
- Third-party information (such as details about witnesses, medical providers, etc.)
Using data analytics to optimize the claims process
Data analytics can enable insurance professionals to identify both patterns and inefficiencies in their claims processes. They can then use their data-backed findings to optimize a variety of aspects of their claims processes– among them fraud detection, payment recovery (salvage and subrogation), payout optimization and settlement, litigation prevention, and product efficiency.
“Data analytics for fraud detection”
One of the most important ways in which data analytics can empower claims adjusters is by helping them to identify fraudulent or exaggerated insurance claims. Fraud is a serious concern for insurance companies and others, costing the U.S. an estimated $308.6 billion each year, according to the Coalition Against Insurance Fraud.
It’s not hard to see why preventing fraud can have a major impact on incurred losses. Meanwhile, the ability to streamline the process of identifying fraud can help insurance companies reduce their loss adjustment expenses. Using data analytics can help them achieve both of these goals, maximizing the efficiency of their fraud detection process while preventing them from paying out on fraudulent claims.
Data analytics for payment recovery and subrogation
In addition to helping insurance companies detect fraud reliably and efficiently, data analytics can help them to recover payments via salvage and subrogation whenever appropriate.
Obviously, effective payment recovery can help insurance companies to prevent their incurred losses from becoming needlessly inflated. And by using data to streamline this process and minimize the resources needed for salvage and subrogation, they can lower their loss adjustment expenses. As with data-driven fraud detection, this combination of efficiency and reliability can help insurance companies improve their overall profitability.
Data analytics for payout optimization and settlement
Insurance companies can also use data analytics to optimize the entire process of reaching decisions on payouts and settling claims. The analysis of data from previous insurance claims can help adjusters identify patterns that can then help them determine the optimal amount to pay out on a given claim. By increasing the accuracy and efficiency with which adjusters process claims, this use of data analytics can help insurance companies both in terms of their loss adjustment expenses and their incurred losses.
This is a perfect example of how using data from previous insurance claims can help adjusters to improve their processing of a present claim, enabling even inexperienced adjusters to perform like their more seasoned colleagues.
Data analytics for litigation prevention
By helping reach fair settlements and expedite claims processing, the effective use of data analytics can help insurance companies to ensure that they comply with legal requirements – empowering them to minimize the risk of costly lawsuits. Analyzing insurance claims data can also help adjusters to identify potential problem areas, so they can proactively take steps to prevent disputes that could possibly lead to lawsuits.
In addition to helping insurance companies avoid financial penalties, this use of data analytics can help them save on third-party expenses (such as attorneys’ fees) and minimize their loss adjustment expenses. Just as importantly, this way of utilizing data can help them prevent the reputational damage that well-publicized lawsuits can cause.
Data analytics for enhancing product efficiency
Finally, analyzing claims data can help insurance professionals optimize the efficiency of the policies they offer, the ways they promote these products, and the service they offer their customers. For underwriters, the data collected by claims adjusters can be a gold mine to help make sure policies’ prices are high enough to make them profitable but low enough that they will appeal to customers and prospective customers. For claims adjusters, the increased efficiency that can result from the use of data analytics can help improve customer satisfaction – both by enabling those adjusters to focus more on delivering a positive customer experience and by shortening claims cycle times.
At the same time, data analytics can also help other professionals from throughout insurance companies – as well as third-party vendors – to improve their product efficiency. Claims data can yield a wide variety of useful findings for insurance companies, which can help virtually every department to ensure that it is operating efficiently and contributing to overall profitability.
Using tools and solutions to compile and analyze insurance claims data
Given the scope of insurance claims data available to claims adjusters, one key to zeroing in on the right data and using it effectively is using advanced technology. Of course, how effectively you use that technology depends on how well the solutions you rely on are suited for your needs and objectives. Before purchasing a tool to help adjusters tap into the power of data analytics, it is helpful to have a sense of what the options are.
There is a whole range of data analytics solutions out there that can help claims adjusters optimize their job performance. While very basic data-focused solutions like spreadsheets can have some value, today’s more advanced and user-friendly solutions can do more to streamline data analysis and help adjusters (and their employers) reap the benefits of claims data.
Improving claims data analysis with Five Sigma
While many platforms can help insurance claims adjusters use data analytics, Five Sigma stands out for its ability to streamline the entire process of managing claims from start to finish. Its intuitive user interface is designed for the ease of use of real claims professionals dealing with real claims, and it uses data analytics to make claims management as efficient, simple, and reliable as possible. Meanwhile, its deep integrations and use of APIs offer unparalleled flexibility, helping claims adjusters to maximize their productivity without compromising on accuracy.
Much of the way Five Sigma’s claims management software uses claims data is geared toward claims adjusters – helping them stay organized, make well-informed decisions, and use their time efficiently. For example, it makes it easy for a given adjuster to see a detailed list of all of their claims on a single screen. Our platform can also automatically calculate the reserve for any claim, and it can use the data it collects to make smart recommendations such as which vendor to use for a specific claim.
At the same time, Five Sigma uses data analytics to help claims managers and executives optimize their teams’ claims processing. Based on the data at its disposal, our technology can automatically recommend an appropriate claims adjuster for a given claim, streamlining the process of assigning insurance claims to adjusters. Our claims management solution also uses claims data to automatically generate dashboards and reports offering a detailed look at a claims department’s efficiency and financial performance – providing insurance leaders with comprehensive information that until recently would have only been available from a dedicated data analyst.
How can you use data analytics to optimize the performance of even claims adjusters with little professional experience? For valuable insights and ideas you can use, click here to check out our guide, Transform Every Claims Adjuster into a Top Performer, Using Claims Data.