The Rise Of Top Two Data Challenges In Insurance Industry With Future Solutions
AI & MI Data Analytics

The Rise Of Top Two Data Challenges In Insurance Industry With Future Solutions

By Dipak Singh August 12, 2021 - 2,550 views

Every day, more than 2.5 quintillion bytes of data are generated that are mostly unstructured and “some 40% to 50% of analysts spend their time wrangling the data, rather than finding meaningful insights”. But, these data need to be analysed and tracked to assess risk and inform fraud by the insurance industries. Moreover, Big data is not anymore a buzzword rather, it has become imperative for the insurance industry. 

With market dynamics evolving at a tremendous pace, insurance industries are expected to stay aligned with the data-rich world. But, Quantiphi report suggests that “80 per cent of data received by underwriters is unstructured”. Mostly these are in the form of forms, email, pdf and images. Therefore extracting meaningful data from it leads to a huge processing time which lowers the efficiency of the underwriting team.

Thus with opportunities arises challenges! As big data is transforming the core concepts of the insurance sector simultaneously, it is also facing challenges that prevent experiencing the full potential of the data insights. Here are most faced top two challenges and their imperative solutions to deal with them:

Challenge 1: Confluence of unstructured data and legacy system prevents from making actionable insights

In a traditional insurance system, there is a barrier to seamless integration among different data depositories. It is often noted that each business has its own way of capturing data which they fail to communicate or share with other business units. Therefore, preventing insurance companies from realising the full potential of data. 

Solution: Build an integrated single platform that integrates new and existing data sources and makes data actionable by leveraging advanced analytical tools

Challenge 2: Deployed actionable data insights only for the product level and not at a customer level

Often customer insights are lost in silos more because they are scattered across the functional lines of the process. Also, there is a lack of predefined terms on customer insights; thus, insurance companies fail to recognise customers at different stages of the policy life cycle. Also, other business units fail to convey the insight for a particular customer to the other business unit, which further leads to an increase in expenses. 

Solution: Build customer-centric analytics solution for precise marketing, customer retention and increasing profit. This will make each business unit enhance the customer value across the policy lifecycle. 

Data itself has no value. To become information it needs to be processed and analysed thoroughly. With data generation increasing at an alarming rate, it becomes important to deploy new strategies and tools to make data work through actions. Learn how INT., with its proposition, is aiding and reshaping the underwriting landscape with an intense focus on customer experience.

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