Don’t get left behind: why insurance companies need to use big data

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Today, insurers have incredible amounts of data at their disposal. They also have access to powerful machine learning tools that can transform it into business intelligence better than any traditional analytics tool could.

The introduction of technology like the Internet of Things (IoT), Artificial Intelligence (AI), blockchain and machine learning has evolved and enriched the insurance landscape. Another factor helping the insurance industry thrive is big data–and its popularity is growing at a rapid rate.

Insurance has always thrived on data analysis to target its customers. It relies on statistics to segment customers’ personal information in order to help group people into different risk categories. This plays a massive role in preventing fraud losses and optimising expenses.

Big data in insurance

For insurance purposes, big data refers to unstructured or structured data being used to influence underwriting, forms, rating, pricing, marketing, and claims handling. By now, most insurance companies understand that big data should be at the crux of all they do. The European Insurance and Occupational Pensions Authority (EIOPA) found that the most significant role of big data in insurance today is in pricing and underwriting, where brokers can compare customer information with a big data set to accurately predict risk and tailor policies to each organisation. In claims management, insurers can use big data to assess loss or damage in order to segment, or even automate, claims. This makes it far simpler for insurers to make big decisions on claims.
Big data offers a great benefit to commercial insurance, helping to inform policy and optimise business practices at a high level, while improving value for business owners at the same time. Big data is particularly relevant in products offering public and employers’ liability cover as it can be used to assess risk against a wide variety of behaviours and precautions. For example, it can identify the most effective health and safety measures and provide an incentive to improve health and safety across the board.

The future of big data

Big data isn’t just a passing trend. As more and more Internet of Things devices come online and consumer behaviours change, the opportunities afforded by big data in insurance will grow, just as the capacity of the cloud to store such quantities of data will. The world generates 2.5 quintillion bytes of computer data per day and IDC forecasts report that the global datasphere is expected to reach 175 zettabytes by 2025.

With the global capacity to collect and store data growing and with the advancements in artificial intelligence and machine learning technology, insurers need to seriously evaluate their technology stacks to ensure they can remain competitive and respond to growing customer demand.

On-demand access to data that provides insight and context to business intelligence and information that is easy to interpret is what will propel businesses in a customer-first environment and empower analysts to quickly conceptualise data in data-intensive industries like insurance.

The shift toward digital has opened the door for new sources of information that can be used to understand customers’ complex behavioural patterns and, right now, getting the right data to the right people at the right time is the name of the game.

Looking forward, the ability to use big data to identify risk will be a key factor for competitiveness in the insurance industry. New technologies will allow the role of insurance to evolve from pure risk protection to risk prediction and, thus, better risk prevention.

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