How Data Analytics is Transforming the Insurance Industry
- 16 May, 2023
- Posted By:Diana Krall
According to the Market Research Report published by Fortune Business Insights in April 2023 for the base year 2022, “The global big data analytics market size was valued at $271.83 billion in 2022”. Of this, the Banking and Financial Services and Insurance (BFSI) industry holds 23%, one of the biggest chunk. The report further adds, “…and is projected to grow from $307.52 billion in 2023 to $745.15 billion by 2030.”
The insurance industry has not been new to using data analytics for its decision making and for competitive advantage. Actuarial science, the science of risk assessment and probability, has long been the industry’s cornerstone. This got a boost with advancements in computing and data storage capabilities in the 1990s and early 2000s. Insurers started leveraging more sophisticated actuarial models to analyze vast amounts of data.
Big data analytics gained momentum from the early 2010s. Over the last decade, remarkable technological strides in computing power, storage capabilities, data collation and processing expertise accelerated its adoption by paving the way for handling and analyzing massive amounts of data efficiently. It also opened hitherto unavailable channels to gain more comprehensive understanding of risk and customer behavior. Nothing could be more pathbreaking than this then for the insurance industry.
Big data analytics opened the floodgates for insurance organizations to analyze more accurately and more efficiently broader set of data variables, detect patterns, and identify correlations that traditional actuarial models had so far failed to capture. With insurance companies facing growing complexities and uncertainties due to changing market dynamics, geopolitical shifts, emerging risks, and evolving customer needs, big data came in to be a saviour.
Let us evaluate the changes it is bringing in:
· It analyses large volumes of historical data and integrates external data sources to help insurers identify patterns and anomalies that further enables to pre-empt frauds
· It helps in the identification of risk patterns, trends, and correlations enabling product teams to design more responsive underwriting and pricing strategies
· It deploys predictive modelling to improve an insurer’s claims function, drives faster processing which in turn builds customer satisfaction
· It enables insurers in the effective segmentation of their customer base, accurately analyze customer behavior and preferences, thereby providing deep insights for customized offerings
· It builds customer stickiness and loyalty on the back of tailored policy recommendations, customized pricing, and proactive risk management solutions
· It provides real-time insights from market dynamics allowing the management to make fast and accurate data-driven decisions
· It identifies operational inefficiencies and helps build improved and cost-rationalized processes
Barring large multinationals, it is but natural for insurance companies to not possess high-end data analytics capabilities in house. Neither does it make business sense for most organizations since the budgetary outlay is massive. Not only will an organization have to invest heavily on technology, but will also have to spend large sums of money at periodic intervals to upgrade existing systems and upskill resources in order to keep pace with the rapidly changing technology landscape.
Outsourcing, in such cases, is often a judicious decision. It helps build expertise within no time, keeps costs in check, brings in scalability and flexibility without burning the pockets. A good insurance BPO service provider can also take the client to greater strengths and capabilities through their deep understanding of the insurance industry, its regulatory landscape, best practises, and with their deep analytical and industry-specific expertise.
Insurance Support World (ISW) has been a leading provider of insurance support and back-office services to insurance companies across every segment for the last 15 years. We had started off with the tradition insurance BPO offerings, but through the years, have graduated to high-end processes including data analytics across a wide range of insurance functions.
At ISW, we leverage a wide range of tools including data mining, data visualization, predictive modelling, machine learning to derive insights, to make predictions, and to support decision-making by the top management.
Our insurance data analytics team experts possess a combination of skills in data science, insurance domain knowledge, and analytical techniques. This has helped us offer specialized services to our clients to improve their risk assessment, underwriting and pricing strategies, augment their fraud detection, and personalize customer experiences. In addition, we have been instrumental in helping our clients’ leadership teams make data-driven decisions to drive business growth and profitability.
Choose from our offerings across Data Modelling, Pricing Support, Business Intelligence, Visualisation, Catastrophe Modelling, Insight Generation, Sales and Distribution. We provide end-to-end insurance back-office services that will help you strengthen your core functions and will enable you to take advantage of market opportunities.
Get in touch with us for a personalized walkthrough of our data analytics insurance BPO solutions irrespective of the region you operate in.
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ISW brings over 15+ years of industry experience and a team of 500+ professionals serving a wide range of clients worldwide, leveraging our insurance niche skills, expertise, and experience for higher operational productivity and process optimization.