Unleashing the Potential: Thinking Big About Big Data in Insurance

There is a revolution sweeping the insurance industry. A digital transformation of epoch-shattering proportion is rendering old techniques obsolete and redrawing the playing field. Today, big data is the name trending in the insurance industry. It offers valuable optics into all aspects of business operations–from underwriting practices to consumer behavior to the ROI of marketing campaigns.

Embracing the Power of Big Data in the Insurance Industry

In 2022, analytics in insurance will be more than just crunching numbers. Trends indicate that there will be new strategies for insurance big data analytics that will help insurers do even more with their information. This post will walk you through how to think big about big data in insurance.

But first, a brief overview of what big data is.

What Is Big Data?

Big data refers to the analysis and management of high volumes of data for use in recording, tracking, and predicting patterns and trends. Insurers are inundated with swaths of data every other day, both structured and unstructured. Normally, this data is distributed in independent silos without any homogeneity or connection between them. 

One of the main challenges insurers face is precisely collecting and sharing all the data at a corporate level, so it becomes part of a unified repository that serves as a starting point for further analysis. Through the use of big data, insurers can analyze trends and patterns so that they can make informed decisions pertaining to risk assessment, insurance policies, and fraud identification.

How Insurers Can Leverage Big Data

Big data offers a better understanding of what risks are involved in the insurance process. With this information, insurance companies can provide measures that minimize risk and enhance insurability. Here is an outline of some of the ways that insurers can use big data to improve their operations: 

1. Risk Assessment

The entire idea of the insurance business revolves around risk diversification. Insurers have always focused on verifying customers' information while assessing the risk factor. Customers are usually segmented into different categories based on their data.

Big data can enhance the efficiency of the whole process of risk assessment. Before making the final decision, an insurer can utilize big data and use predictive analytics to count on possible issues based on a customer's data and put them into a suitable risk class.

2. Fraud Detection and Prevention 

According to the Coalition Against Insurance Fraud, insurers lose more than $80 billion every year because of insurance fraud. Such fraudulent acts result in increased premiums. Insurers can reduce the number of fraud cases through predictive analytics and data analysis. They can match the variables in every claim against the ones in fraud claims to determine if there is a need for further investigation. These variables could range from the person making a claim, the network of people associated with it, and the agencies involved in the claim.

3. Consumer Acquisition 

Every business needs to acquire customers to thrive. In these times when there is increased use of the internet, everyone generates large volumes of data via emails, social media networks, and feedback.

The data collected from customers' online behavior is categorized as unstructured data and is part of big data. By analyzing such data, insurance companies can create targeted marketing campaigns that will enable them to acquire new customers.

Gaining an in-depth understanding of consumers' habits and behaviors is a strategic move that can help insurers determine future behavior. The information gained from customer emails, data centers, social media, and other forums can help insurers make a unique profile for each customer.

These insights not only provide information regarding customer behavior, but also help forge a trusted relationship with the customers. Because of this, insurers achieve positive outcomes like solving consumer problems in real-time.

4. Cost Reductions

One of the main benefits that businesses, including those in the insurance industry, accrue from technology is cutting costs. The increased usage of machines in the insurance industry enhances efficiency, which ultimately leads to cost reduction. 

According to a report titled "Big Data Use Cases," companies that leverage big data enjoy a 47% cost reduction. You can use big data technology to automate manual processes, making them more efficient and reducing the cost spent on administration and claims handling. This will enable insurers to offer lower premiums to their customers and hence gain a competitive edge in the cutthroat insurance industry. 

5. Automation of the Insurance Process

Insurers usually undertake tasks such as data entry and compliance tasks. With the rise of big data, many new possibilities have opened up. Now, loan reconciliation, underwriting, claims verification, property assessment, among other tasks, can be done faster and more efficiently.

As the insurance industry moves more towards automation, insurers can save a lot of time and resources with the help of machine learning.

6. Personalized Service and Pricing

Today, customers strive for a personalized experience. The analysis of unstructured data can help insurers provide services that suit and meet their customers' needs. For instance, life insurance based on big data can be personalized by taking into account the medical history of a customer along with the behaviors perceived by the insured. The data can also be used to decide a pricing model that's ideal for the client and makes a profit for the insurance company at the same time. 

7. Customer Retention

No business wishes to lose its customer base. A business is considered successful if it has a high customer retention rate. The insurance industry is no exception. As such, it uses big data to retain its customers.

Based on customers' activities, predictive analytics can help insurers pinpoint early signs of customer dissatisfaction. By working on the insights gained through big data, insurers can quickly react to optimize their services and also find a solution to the grievances of a particular customer. Insurers can offer discounts or even change the pricing model for their customers.

Wrapping Up

Big data is one of the best ways insurers can make profitable moves. Even so, processing large volumes of complex data requires robust technology. When you look at the prevailing big data trends, you will realize most insurers are modernizing their legacy system to allow for better integration.

If your business is considering delving into the world of big data, Pilotbird can help. Try a free demo of Pilotbird's predictive analytics solutions.

REFERENCES

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Watts, M. (2020, June 10). What is big data in insurance? https://artificial.io/company/blog/what-is-big-data-in-insurance

Pathak, R. (2021, May 25). 7 uses of big data in the insurance industry. https://www.analyticssteps.com/blogs/7-uses-big-data-insurance-industry

Wargin, J. (n.d). Insurance big data analytics trends in 2022: how to leverage your data. https://www.duckcreek.com/blog/insurance-big-data-analytics-trends/

Springboard India. (2019, December 8). How data can help reduce business expenses. https://medium.com/@springboard_ind/how-data-can-help-reduce-business-expenses-194dfa42ba0a