6 Ways Big Data Analytics Change the Insurance Industry
6 Ways Big Data Analytics Change the Insurance Industry
Big data services help resolve data issues that insurers face on a daily basis. Big data analytics applications make this task feasible and reduce the rate of fraud.
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Technology has a big impact on the way the insurance sector does business. Although big data analytics as a service is still fairly new, insurers rely on it heavily. As companies increase the number of policyholders in their databases, the need for meaningful analysis becomes more crucial. Big data analytics applications make this task feasible.
Big data services help resolve data issues that insurers face on a daily basis. A big data analytics platform can be challenging for those still getting used to the technology. However, there are many advantages to coming to terms with what big data offerings can do for your business. Learn more about how the insurance industry benefits from data analytics from the time a customer signs an application through their first claim filing.
Here are six different ways big data analytics services can change your insurance business for the better:
1. Preventing Fraud
Sophisticated data analytics tools are already available in the insurance industry. Successful fraud detection skyrockets when using this technology. Fraudulent claims impact premium costs and waste resources meant for legitimate claimants. Whether handled in-house or through big data consulting firms, it’s important to identify and investigate these cases quickly. By studying past behaviors, data analytics consulting resources can identify if an applicant is predisposed to make false claims by studying past behavior. Big data service offerings can also determine if an applicant has past fraud convictions.
Social media analytics gauge whether a policyholder is likely to commit fraud. Using predictive modeling facilitates the ability of agents to determine whether to request more information to just deny the policy. Similarly, companies use big data analytics services to process claims prior to high payouts. The claim data can be checked for trends leading up to the claim. For instance, a claimant reports a stolen car after they left a window open. This claim could be flagged for investigation.
2. Potential Risk Assessment
Data analytics is perfect for detailed risk assessments. Big data analytics applications identify the risk each applicant represents before a policy is issued. Due to the capability of big data service offerings, the industry can upload police crime records as well as social media information. This amount of data storage was inconceivable before big data offerings.
Let’s look at an example. A person has no criminal record and wants an insurance policy for a new car. This case goes through risk assessment checks that include the make of the car, the customer’s age and existing records.
With big data analytics as a service, providers have more information available than ever. So, details like the area’s crime rate and the number of accidents their model of car experiences are taken into account. Before approving a policy, risks are assessed and the premium is priced accordingly.
3. Streamlining Internal Insurance Activities
An effective big data analytics platform can streamline the internal processes. This includes the following areas:
- Customer feedback assessment
- Checking how a policy is selling
- Assessing customer response to sale techniques
- Gauging the effectiveness of promotions
- Determining which policies have the highest number of claims
These are just some situations that improve with the capabilities of big data analytics.
Tons of data are processed in an instant and data analytics facilitates the ability of managers to examine areas of their business that are doing well and others that need to improve. This allows for more meaningful feedback to employees who sell products and also helps them adhere to the statistical requirements of the products.
4. Personalized Policy Offerings
Insurance industries are centered on the customer. That means that policies have to be personalized and tailored to each client’s preferences. Customers want their agents to be trusted consultants who help them get the best policy at the best deal. This is made possible by big data consulting firms or in-house resources who design algorithms for flexible customer experiences. Data analytic algorithms assist with customer retention and predict what plans would benefit which customers.
An intelligent big data analytics platform gives insurers to get a comprehensive view of each applicant. This is why agents can offer actionable insights based on the prospective client’s insurance history.
5. Simplifying Complex Cases
Some people set up anonymous quotes and get insurance just to file claims and get money from the insurance company. Some of these are easy to prove as frauds and big data analysis helps identify legitimate cases more quickly. On the other hand, some cases involve a lot of complexity. These cases require tons of fact-checking to ensure the evidence matches what the customer says in the claim. Big data analytics applications employ mining techniques to process these claims and identify risks. Data mining categorizes various claims and scores them based on relevance. Some of these tools can even determine the amount that the company is willing to settle the claim for.
6. Settlement Cases
Many customers complain that lawsuit settlements take a long time. This can delay the customer’s ability to get the care they need or recover from financial losses associated with an insured event.
Using big data services helps settle some claims nearly instantaneously. Insurance company resources can evaluate the claims history of each customer or all customers insured by the carrier. This saves labor costs and improves accuracy. Investigators don’t have to spend as much time finalizing each data point in a claim. Customers are happier too because, chances are, they get their claims checks faster.
Data analytics consulting helps reduce the rate of fraud and simplify complex cases. Streamline processes and customized policies also lead to greater customer satisfaction. By accessing and evaluating the risk of individual applicants, big data weeds out high-risk prospective clients and prevents them from increasing the risks, which can result in lower payments for legitimate policyholders. There are some risks and issues that need to be resolved but that doesn’t change the fact that big data analytics services have greatly improved the processing of applicants and facilitated the claims resolution process.
Data analytics is moving the insurance industry ahead at a time when it’s needed the most. Expect to see more changes making positive impacts in the industry. Is your organization as data-driven as it needs to be. Whether you own insurance firms or provide BPO services, data analytics greatly expands your likelihood of acquiring and retaining quality customers. When implemented properly, big data service offerings help the insurance industry retain clients and improve their service.
If you have been waiting for the evidence that big data analytics solutions is worth the effort and expense, you now have it.
Published at DZone with permission of Rahul Asthana . See the original article here.
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