Big Data in Insurance: Everything You Need to Know

BigDataScalability.com – Big data may sound like a buzzword. In reality, it is an invaluable tool that any business in any industry can benefit from. This, of course, includes businesses in the insurance industry. Insurance companies have been dealing with data from the beginning. Big data in insurance takes it to another level.

Leveraging big data, insurers can operate more effectively and efficiently and provide their customers with better products and services. Not to mention the cost saving and fraud detection benefits.

Thus, it is necessary to understand the role big data play in the insurance industry. In this post, we tell you everything you need to know about big data in insurance.

What Is Big Data?

The term “big data” refers to the management and analysis of high volumes of data for use in tracking, recording, as well as predicting patterns and trends.

Nearly every business in all sectors is inundated with a vast amount of data, both structured and unstructured. And this happens on daily basis.

Is the vast amount of data all there is to big data? Not exactly. What really matters is how businesses apply and turn the vast amount of data into something usable.

Data is not something new for businesses. They have been dealing with data from the beginning, after all. So, what makes big data special?

Big data is a relatively recent development. What makes big data special is the size of the data sets. Due to its huge volume, traditional methods cannot be used to store or analyze it.

With the advancements in technology, particularly machine learning and artificial intelligence (AI), businesses, including insurance companies, are now able to not just store and analyze, but also leverage big data. Hence, the recent development.

Big Data in Insurance Industry

By now, nearly all insurance companies realize the importance of big data in insurance. If anything, big data should be at the center of much of their work. That said, only a few companies truly understand how to process big data and put it to good use.

Almost all aspects of the insurance process can benefit from big data. From managing claims to customer service and underwriting.

According to the European Insurance and Occupational Pensions Authority, the most important role of big data in insurance is in pricing and underwriting.

An excellent example of big data’s role in the industry is in motor insurance. Leveraging big data, brokers can gain insights into individual driving behavior. Using the insights, they can predict risk as well as tailor policies to each motorist accurately.

Another example is in claims management. Using big data, insurers can effectively assess damage or loss to segment claims. In some cases, even automates claims.

There is also fraud detection. Big data in insurance can help detect fraud. Companies can use big data to model fraud risk, scour data for anomalies, as well as analyze social network information, among others.

The 6 V’s of Big Data in Insurance

Big data, and the insights it provides, is one of the most valuable assets an insurance company can have. Not all data is equal, of course. Some have high quality, some have low quality.

The question is, how does a company determine the quality of big data in insurance? By using a six-factor system known as the 6 V’s of big data.

The 6 V’s are volume, velocity, variety, value, validity, and veracity. Using these V’s, it will be easier for an insurer to transform raw data into actionable insights.

1. Volume

Volume is the base of big data. It is what the “big” in big data refers to. Volume is the amount of data that a company has and continues to collect. Currently, big data is measured in petabytes (1 petabyte = 1,024 terabytes) or exabyte (1 exabyte = 1,024 petabytes).

While big data is a relative term, if the size of the data sets is large enough for a company, it can be considered big data. This is because the data storage and analytics capabilities of insurance companies vary.

2. Velocity

Volume is not the end-all-be-all of big data. There is also velocity. Velocity refers to the speed at which data is generated and moves. Needless to say, insurance companies need velocity.

The faster the data flows, the more it is available at the right times. When data is available at the right times, companies can make the best decisions possible.

3. Variety

Variety in big data refers to the diversity of data types. Structured data (information such as name, address, car model, dates, claim history, etc.) is easier to understand than unstructured data. Nevertheless, unstructured data is also important and impactful.

When it comes to variety, the main challenge is to standardize and distribute the collected data accordingly.

4. Value

Value refers to the value that the collected data can provide. Is the collected data good data? Or is it bad data? Keep in mind big data is generated in such a vast amount. Not surprisingly, the quality of the data, and thus the value, may get watered down.

The more valuable the data, the better, more actionable insights a company can gain. A company must be able to not only distinguish good and bad data but also know what to do with it. Only then the company can leverage big data.

5. Validity

There are various methods of data creation and data collection. Each one comes with their benefits and limitations. What’s more important is the validity of the data. In other words, how well does the data relate to the questions and outcomes that the company is looking for?

To make the most of big data, a company must be capable of matching the right data sets with the appropriate tasks.

6. Veracity

The last V is veracity, which refers to the trustworthiness of and confidence in collected data. Insurance companies collect data from many sources. Not all data has the same level of veracity, of course. Some may come from disparate sources, while others may be untrustworthy by default.

Note that there is always a slight margin of error, especially when it comes to large data sets. To leverage big data, a company must be able to not just work through them but also make the most accurate decisions possible.

Big Data in Insurance Applications

Personalized Service and Pricing

Insurance companies use big data to collect information. For example, when a customer wants to buy car insurance, the insurer can leverage big data to calculate said customer’s past driving records and safety levels for driving in their vicinity.

Using the insights big data provide them with, the company can decide on the right premium and cover for the insurance buyers.

Everyone likes to be treated specially. Leveraging big data, insurers can treat each customer specially by providing them with personalized service and pricing.

Gaining Customer Insight

For insurance companies, making customers the center of their attention and improving customer experience is crucial. This is another area where big data in insurance can help.

Thanks to big data, insurers now can manage, store, and access information related to customers from multiple sources. With big data analytics, insurers are better equipped to improve customer experience.

Fraud Prevention and Detection

Insurance frauds are common. Insurers can use big data to minimize insurance fraud. Big data in insurance has been proven to be highly effective to prevent and detect fraud.

Using big data, insurers can keep track of claims made by a client. When the system detects a claim is being made by a client who has a history of false claims, it halts the claim processing automatically. Then, an investigation against the client initiates.

Risk Assessment

Insurance companies deal with risks every single day. Their main task is to assess and diversify risk, categorizing customers into different risk classes based on collected data. Big data helps to make the whole process more efficient.

Cost Reductions

Cost-cutting is among the many benefits that big data offers. As machines play more roles in the industry, efficiency increases. Eventually, this leads to cost reductions.

Insurers can leverage big data technology to automate manual tasks. This not only makes the process efficient but also reduces the costs spent on these tasks.

The Benefits of Big Data in Insurance

What about the benefits? Are there any benefits of big data in insurance? The answer is, of course, yes. In fact, big data benefits not just the insurers, but also the customers. Below are a few examples of big data in insurance benefits.

Cost Savings

Among the most significant benefits of big data in insurance is cost savings. Big data can do a lot of the work that employees have to spend many hours doing. This, in turn, can add up to cost savings for the company, which they can pass on to customers.

Faster Approvals

Among the benefits of big data in insurance is faster approvals. Big data helps insurance companies underwrite policies. This enables faster approvals and denials. For customers, this means their insurance policy may go into effect faster.

This results in a lot of good things. Most importantly, with faster approvals, customers will be able to protect their families financially sooner.

Not to mention there will be fewer records that need to be tracked down manually, fewer phone calls, and, in some cases, even fewer medical requirements to meet.

Incentivizes Positive Behavior

Insurance companies can leverage big data to incentivize positive behavior. For example, some companies may provide their customers with a pedometer to encourage them to be more active.

If customers are more active, exercise regularly, and track the steps they have taken in an app, insurance companies can offer lower prices and incentives.

Reduces Fraudulent Claims

Big data in insurance can also reduce fraudulent claims. Among the most important factors in securing life insurance policies are honesty and accuracy.

Insurance companies do everything they can to reduce spending on fraudulent claims. Gathering information as well as verifying data about applicants plays a vital role in that process.

Better Customer Service

When it comes to customer service in insurance, there is always room for improvement. Insurance companies can leverage big data to better their customer service. With the insights they gain from big data, insurers can provide their customers with more personalized service.

Using these insights, insurance agents are better equipped to help customers choose policies that really fit their needs and budgets.

Most insurance companies realize the importance of big data in the industry. However, not many truly understand how to leverage it and thus, derive optimum benefits from it.

Unlike some hot topics of today, big data is far from a passing trend. If anything, it will stay in the foreseeable future. The applications of big data in insurance will grow. And with that, more benefits for not just insurance companies but also customers.