Role of Business Analytics in Insurance Industry
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Business Analytics In Insurance Industry

29 Jul 2020

Insurance companies generate and hold a wealth of data. It comprises of consumer information, product details & pricing information, underwriting practices, and much more. Insurance data analytics helps leverage knowledge by converting it into actionable insights. Rishabh Software empowers insurance firms with efficient predictive analytics based models & data visualization tools that accelerate business outcomes to drive competitive advantage.

Data analysis is one of the historical pillars of the insurance sector. With statistical models used by actuaries in the past to predict property loss & damage to selling policies, the insurance industry indeed collects a large volume of data sets about the customers.  However, investment in data has gained strategic importance in recent times when insurers have sought to become more relevant for their customers.

To leverage advanced analytics and further integrate the outcomes with a business process must be an integral part of every insurer’s strategy today. And, while the digital opportunities are abundant, the focus should be on harnessing data analysis to cut down on claim handling time & costs and eliminate potential fraud.

Predictive analytics in insurance drives data-led decisions such as:

  • Potential fraud detection
  • Risk identification
  • Acceptance/Rejection of consumer claims
  • Product insights of performance & pricing
  • New industry trends

Rishabh Software helps insurers embrace new models of analytics & data science technologies with comprehensive actuarial services and advanced analytics coupled with machine learning tools that drive growth and innovation.

Insurance Data Analytics – Diving into the Essential Components of Our Capabilities

Actuarial Modeling

  • Automate the laborious process of file generation for end-to-end asset modeling as part of the centralized system
  • Use of in-built workflows or customize them as per the compliance (creation/approval process) need of business rules & service engagement
  • Calculate the accurate MCEV (Market Consistent Embedded Value) for the business unit and perform real-time analysis of sales & in-force management plans

Further, by leveraging the BI (Business Intelligence) and reporting capabilities of insurance analytics, we help create data-driven investment strategies, understand market scenarios, capital management tactics and more.

Actuarial Modeling in Insurance Analytics

Join The Insurance Industry Transformation

Our custom analytics solution help in streamlining risk assessment & claim management processes with real-time actionable insights.

Insurance Data Analytics Risk & Capital Management

Risk and Capital Management

We assist companies with insurance data analytics by addressing risk management components that cover balance sheet optimization, assessment & analysis, reporting and more.

Our capabilities allow:

  • Evaluation of new applicants based on the defined criteria and filter out unqualified leads automatically using the model-building feature
  • Get actionable insights based on historical data about customer behavior to identify and a crackdown on potential fraud scenarios
  • Detect the loss circumstances with the aggregation of damages due to inadequate claim settlement and fraud detection processes

Besides, one of our recently developed COVID-19 dashboard solution helps provide insights on pandemic hotspots to backtrack its effect on insurance claims, forecasts loss and increase in applications.

Transformation Tools

To help insurance companies move ahead with agility and unlock new opportunities, we can build and implement a variety of tools for process & communication improvement as part of insurance analytics focus.

It includes but not limited to

  • Underwriting dashboard – Helps conduct preliminary analysis with various risk parameters related to new customers/policies before taking further action on risk scoring & underwriter performance assessment
  • Communication tools – Enables social collaboration to dig deeper with faster data sharing to improve decision making
  • Trend predictor – Identify the target market by analyzing user behavior patterns, demographics and other characteristics on a real-time basis
Predictive Analytics Tools in Insurance

Reasons Why Predictive Analytics In Insurance Industry Could Become The New Norm

  1. Customer centricity
    Customers are always looking for a personalized experience, especially when interacting with insurance consultants. With analytics, you can capture digitally and derive actionable insights on user behavior, their buying behavior and lifestyle habits to serve the customers better.
  2. Identifying & preventing fraud
    According to a study, fraudulent claims cost P&C insurance firms a loss of $80 billion annually in the US alone. The predictive insurance modeling assesses consumers’ online behavior on social media and other channels that identify & prevent potential fraud at the earliest.
  3. Smooth claim assessment
    An insurance analytics system forecasts the needs of insurers regarding claims based on market trends and consumer behavior. It alleviates their concerns and improves the insurer-customer relationship.
  4. Self-servicing of insurance policies
    Artificial Intelligence (AI) in the Insurance enables insurance to provide smart assistance with recommendations to customers at the time of policy purchase or while amending an existing one.


Predictive analytics in the insurance sector is creating a monumental shift by defying old-school methods of working to unlock new growth opportunities.

Rishabh Software is a preferred partner for insurance companies to leverage this transformation by deriving value through analytics powered by AI & machine learning capabilities. We enable the organizations to drive improved service, higher customer satisfaction and faster processing time.

Drive Growth With Data Analytics

Rishabh Software enables the right decision making to drive insurance business forward with an integrated suite of risk, consumer, operations and capital management solutions.