Data Analytics in Insurance Industry
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Data Analytics In Insurance Industry

13 Jul 2021

In the digital era, every sector needs to leverage the potential of untapped data. One such industry that holds a wealth of data is the insurance business. It comprises customer information, product details & pricing information, underwriting practices, and much more.

You would agree that the rising competition, stricter regulatory & privacy policies and ever-changing customer trends are driving insurers to digitize quickly. And organizations can stay competitive by not just focusing on effective data management but also converting it into useful insights for data-driven decisions.

Through this blog, we’ll talk about the power of Business Intelligence and how can it assist insurance companies with Big Data management & data visualization to refine their workflows, take smart decisions and deliver valuable customer experience. If you are looking to leverage the full potential of the said technologies, then this article is for you.

Did You Know?

Research suggests that more than 60% of insurance companies use data and predictive analytics to increase sales while reducing time to market.

Role of Analytics for the Insurance Sector

Data Analytics in the insurance sector is creating a massive shift by unlocking new business growth opportunities. The insurance companies, by nature of their business, gather a humungous amount of data. Most of the future-oriented organizations are adopting newer and smarter ways to analyze this data to accelerate business outcomes.

It has led insurers to rely upon big data transformation services to handle critical data and analytic needs. BI supports all aspects of insurance data visualization, right from profitability, operations, claims, marketing, and sales. A business intelligence platform is an important component of data transformation services that analyzes vast amounts of data and displays it appropriately.

Benefits of Insurance Data Analytics

For organizations managing high volumes of data, visual representation brings insights to life. It is a collation of information component across accident statistics, policyholder’s personal information, along with supporting third-party sources to prioritize different risk categories, prevent fraud losses, and optimize expense. This allows brokers and underwriters to make fast, informed decisions from their preferred location or device, speeding up decision-making overall.

Data visualization in conjunction with Big Data helps organizations to aid in making decision making across areas of their business such as:

  • Faster Claims analysis: Advanced analytics enables the logical connection between data and effective action. With the growing adoption of automation, changes in policies and increases in claim data, there is an enhanced need for advanced claim analytics.
  • Precise Risk Identification: Insurers conduct customers’ information verification while assessing the risks. With apt data management techniques one can create various risk classes and customers are segmented into different classes based on their profile. You can even upload social media information and criminal records if any. All this data can then be put on a solid data viz dashboard which can give you insights and clear identification of high, med and lower risk profiles.
  • Product Profitability Analysis: It helps investigate individual insurance products at a deeper level by analyzing the product performance and profit by distribution channel, geographic region, customer segment, and other factors. Within a BI system, it can check in real-time the product’s premium update, its lapsations, claims and other related details
  • Revenue comparison: Conversion ratios, expenses ratios, and retention ratios to conduct an in-depth analysis of a single product can be put on a dashboard to have thorough insight on performance. Staying abreast of these parameters help avoid underwriting overruns and remain profitable.
  • Enhanced Process Automation: Optimizing operational processes by automating data entry, compliance checks, repetitive tasks, and more. By leveraging technologies, such as RPA can automate & improve back-office processes and customer-facing services.
  • Effective Decision Making: Data visualization and decision-making tool can provide report insights to empower marketing by tracking sales & services, claims processing, underwriting, product development, and other aspects of an insurance business. There is an abundance of valuable information that insurance companies can glean by using different data visualization techniques.
  • Improved Customer Satisfaction: With analytics, you can capture prospective client’s feedback digitally, store it and derive actionable insights on their buying behavior and lifestyle habits. Utilizing the data, you can plan better to provide them a better experience. This is where data management & BI systems will help most.

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Top Use Cases of Data Analytics in Insurance

In the modern digital era, Big Data management is helping process vast amounts of information, increase workflow efficiency to ultimately reduce operational costs. With BI dashboarding and reporting software, users will quickly assemble interactive data visualizations for executive presentations. Business analytics in insurance help get insights about potential markets, competitors, customers, risks, regulations & plans for natural disasters.

Pricing and Service Optimization

  • The ability to examine risk and determine price policies becomes a central point of value creation for insurance companies. Big data analytics in insurance helps actuaries to build policies better suited to dynamic business needs, market conditions, risk concentrations and patterns.
  • By analyzing consumers’ behavior, lifestyles, pricing sensitivity, and buying preferences, you can optimize and showcase more appropriate insurance products.
  • Previously, it was difficult to customize policies at the individual level. However, insurance providers can now use pay-as-you-go and more dynamic pricing models based on clients’ behavioral signals, predicted risk factors, and shopping preferences.

Fraudulent Claims Detection

  • The fraud cases in claim processing are a major challenge in the Insurance sector. According to studies, 10% of all claims turn out to be fraudulent.
  • Improvements in technologies have made it possible to detect suspicious claims, fraudulent activities, and behavioral patterns by leveraging predictive analytics in insurance subjected to further investigation.
  • Whenever a claim made by a user with a history of false claims is detected, the fraud prevention system halts the claim process and suggests case investigation. Predictive modeling techniques are applied to analyze patterns in fraud and the screening of false claims.

Future-Proof Your Insurance Business

Insurance business means huge amount of data and huge opportunities. While the digital opportunities are abundant, the focus should be on harnessing the big data to cut down on claim handling time & costs and eliminate potential fraud.

Using Big Data analytics in combination with data visualization, the organizations can now offer personalized policies, with a risk assessment to prevent fraudulent activities and increase the efficiency of internal processes.

Rishabh Software empowers insurance firms with custom data management & data visualization solutions that boosts business outcomes to drive competitive advantage. By leveraging the BI reporting capabilities, we help create data-driven investment strategies, understand market scenarios, capital management tactics and more.

Wish To Leverage Data Insights Better?

Our team of specialists can help you manage, develop and assess insights tailored to your insurance business needs