The insurance industry is a for-profit entity like any other sector. This is one industry where assessing risk factors of potential clients is absolutely essential. In this sense, insurance companies need to look at data sets much more differently than the retail or any other industry. Most auto, home, and health insurance companies these days have their own data mining tools for making the most of big data.
In this article, we shall be looking at 6 ways big data affects the insurance industry and what you can do about that.
How Big Data Affects the Insurance Industry
Telematics is a new trend and is helping insurance industries acquire valuable data in real time. In the health sector, companies can use IoT devices and wearables like Apple Watch or FitBit to monitor a client’s health and physical well-being. The data provides insights about the client’s likelihood of attracting cancer or other major illness.
This data benefits both the insurance company and client. The company can share the data with the client and require him/her to undergo a physical evaluation. This lowers the client’s risk of poor health through preventive measures. The insurance company saves tremendously on potential insurance payouts associated with expensive medical procedures.
Healthcare fraud costs insurance companies an annual $68 billion, according to a study by Blue Cross. Through big data, companies can use predictive modeling to identify the probability of a potential fake claim. This is done by matching the data of present claims with the claims of past claims that proved to be fraudulent.
Furthermore, with the advancement of the latest business intelligence tools, insurance companies can also examine unstructured data to look at client behavior. Data gleamed from social media may yield behavioral traits of individuals likely to make fraudulent claims.
Improve Customer Experience
Loyalty programs aren’t just limited to the retail industry. Insurance companies also provide discounts, such as accident forgiveness programs in the auto insurance sector. Another way to improve customer experience is through the use of free apps.
State Farm Insurance, for example, has their own app known as Driver Feedback. The app evaluates driver behavior and provides feedback on how to improve driving habits. This keeps collisions down especially among younger and more inexperienced drivers.
The health insurance sector is doing the same by handing out wearables with apps that monitor the clients’ heart rate, physical activity, etc. The app provides feedback to the client while relaying the data back to the company.
Insurance companies need to market their policies. Big data help companies devise the best campaign with targeted services. Business intelligence software can analyze visitor behavior on a website and provide offers if it detects the visitor is about to click out. BI software may determine, for instance, that visitors are likely to click out if they don’t click on a link in the navigation bar within 60 seconds of being on the homepage. The BI tool can respond at exactly the 60-second mark with a pop-up offering something like a free quote over the Web.
To bring potential customers further along the sales funnel process, those that click the popup can be offered an additional incentive if they sign up on the spot. This may be an offer like the first month’s premium free.
Most insurance companies have a fast-track process for instantly settling claims and payouts. While this saves time and resources, it may also be costly as the company may end up overpaying.
This typically occurs in the home insurance sector where mass payouts occur when natural disaster strikes. In this instance, the insurance provider may end up overpaying as they don’t have the resources to individually examine the damage of each property. However, with the ability of BI tools to analyze claims and claims history, the insurer can set a more accurate limit for payouts.
In the insurance industry, loss reserve refers to the estimated payout of a given claim or group of claims. The estimation is usually a ballpark figure since there are too many unknown variables early in the claims process.
Claims forecasting, though, has become more accurate and predictable in the past five years due to big data, which can determine a probable sum based on data collected from past similar claims. This gives insurers a more precise figure that they need on hand for meeting future claims.
Big data is gold in the insurance industry. Companies rely on the information for optimizing every area of the process, from handling claims to adjusting premiums. The end results are speedier and more accurate payouts, improved customer experience, and reduced overhead.
This is a guest post written by Lucy Boyle. She’s a Mother, a blogger and a freelance business consultant; currently a regular contributor to Allocable’s blog. Follow her on Twitter @BoyleLucy2.