Data Analytics in the insurance sector is creating a massive shift by defying traditional ways of working to unlock new business growth opportunities. Insurance companies, by nature of their business, gather humungous amount of data on a regular basis. Today, insurance companies across the globe are adopting newer and smarter ways to analyze this data to accelerate business outcomes. The need for faster data-driven decision making, has led insurers to rely on data transformation services to handle critical data and analytic needs.
Insurance Data Analytics for a Proactive Business
Even before the on-going global pandemic, digital disruptions were affecting insurers. Thanks to digital innovations powered by Big Data, Predictive Analytics, Cognitive Computing, insurers are moving towards a more proactive model. This has resulted in accurate risk assessment and greater real-time business insights that help in preventing losses in the very first instance, rather than compensating for them later. Data Analytic technologies have gained tremendous momentum within the insurance industry as it helps in adopting a proactive business model, wherein critical business processes like data entry, insurance claim processing, personalization and fraud detection can be significantly improved in terms of speed, accuracy and relevance. This shift towards building a proactive business model driven by advanced analytics also means that insurance companies will be dealing with ever-growing banks of data. Hence, it has become a business imperative for insurance companies to quickly get into the data analytics bandwagon for tapping new opportunities – more safely, securely, sustainably and profitably while improving customer experience.
Research reports suggest that,” The insurance data analytics market is expected to grow with a 12.6% CAGR between 2020 and 2025.”
Top Data Analytics Insurance Use Cases
Undoubtedly, data has become the center of focus for the insurance industry that has tremendous power when unleashed rightly. Let’s look at some of the top uses cases and benefits, the insurance industry can reap from Data Analytics.
· Claims Processing: Faster claims settlement is one of the critical factors that determine the overall efficiency of an insurance business. Claims processing includes multiple time-consuming steps and while performing these steps, numerous issues like – manual or inconsistent processing, varying data formats and changing regulations may crop up. The need for automated data processing and faster transmission has led insurance companies to implement data processing services which help process all important documents into digital formats. The strong capabilities of Big Data Analytics in processing and analyzing huge datasets can make various aspects of a claim processing faster, simplifying the overall process of claim settlements. Also, with predictive analytics, insurers can now analyze historical data to determine events, which could affect the outcome of claims. This can streamline the entire claims process and help mitigate risks.
· Fraud Detection: According to studies, 1 in every 10 insurance claims turns out to be a fraudulent one. It is important that these fraudulent cases be detected, as these incur huge costs to insurance companies. Big Data analytics can be the best weapon against these fraudulent claims, as it can help to study past behavior, frequency of claims, credit score etc. and help the insurance agents to determine whether they should seek additional information about the applicant or to deny issuing a policy completely.
· Underwriting Automation: Data and advanced analytics can help insurers save a lot of time and resources involved in underwriting and automating the process. From data gathering to data validation to real-time recommendations, the “virtual underwriters” driven by Data Analytics, are faster and more accurate. With Data Analytics, insurers can overcome some of the common challenges like manual data gathering from different type of application formats and channels, pre-scoring applicant, avoiding missing information etc. Trained underwriters supported by smart and automated data analysis and decision-making systems will be able to provide higher values to their customers and improve cross-selling.
· Risk Assessment: Performing thorough risk assessments is one of the major use cases of data analytics in the Insurance sector. It helps to identify how much of a risk each applicant is representing before issuing them a policy. Thanks to the data analytic tools, the insurance industry holds various data sources and before issuing a policy, rigorous risk assessment is undertaken, and the policy is priced in accordance with this assessment.
· Customized Policy Offerings: The insurance sector is becoming more and more customer-centric and providing personalized policy offerings. Data analytic algorithms are helping insurers to retain customers, by predicting customized plans suited for each individual customer. Platforms built on data analytics are enabling insurers to get a 360-degree overview of their customers and provide actionable insights based on previous insured customer data. These insights will later be used to develop and improve product and policy design, enhance customer profiling and targeting, deliver valuable and relevant product recommendations for each customer segment.
Everything said, we are sure that Data Analytics is taking the entire insurance sector forward, and we will continue to witness a positive change in the future to come. As per McKinsey, data analytics-driven insurance firms are 23 times more likely to acquire customers, six times as likely to retain customers, and 19 times as likely to be profitable as a result. Data analytics will surely make the insurance sector reach new heights.
Aspire Systems with its strong Insurance domain experience and Data Analytics expertise can help insurers across the globe make the most out of their data and transform their business. Aspire Systems, in collaboration with Guidewire, provides AI-driven application management services that can help enterprises save more than 40% of the total costs with respect to implementation of Guidewire solutions.
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