How Predictive Modelling Maximizes Group and Voluntary Benefits Business Value

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Predictive modelling is not a secret in 2024. Giant organizations such as Uber use predictive models to determine demand patterns for rides in different locations, helping them optimize driver allocation and pricing strategies. Even most professional sports organizations use predictive models to forecast declines or rises in player performance.?

Employee Benefits insurers can gain a similar advantage using predictive modelling in underwriting, enabling increased profitability, more accurate rates, better closing ratios and more streamlined processes.?

Pricing & Rating?

Predictive modelling combines an insurer's historical data with machine learning to create predictions about future events and behaviors.?

A key benefit is more accurate pricing of insurance products. From adjusting factors on rates to entire rate recalculations, predictive models can optimize group pricing. In fact, 83% of insurance executives believe predictive models are very critical for underwriting’s future.?

Insurers can use machine learning to analyze rates based on data from won and lost quotes along with demographic and behavioral variables of groups to recommend pricing improvements. But, what about external data? Often carriers choose to incorporate internal product experience data into their models because external sources are costly and time-consuming.?

A sound predictive model can assess multiple data points simultaneously, spotting important trends and correlations. Additionally, predictive models give actuarial and pricing teams tools to identify trends and key factors in both won and lost cases to improve closing ratios.??

Majesco's robust Modelling component allows carriers to experiment more effectively, and plays a prominent role in renewal underwriting by allowing insurers to make and suggest adjustments to retain profitable customers.?

Benchmarking: Leveraging Market Trends?

Predictive modeling can help insurers reveal behavior patterns and common demographics that expose opportunities for increased market penetration.??

With this data, carriers can launch more targeted marketing initiatives and increase their probability of closing new business. Then, insurers may develop market penetration strategies that target underserved groups with tailored plan designs and pricing to make them profitable.?

For example, you might find that businesses in the finance industry are seeking health insurance with flexible options due to their young workforce and relatively low health risks. In this scenario, you can stimulate urgency and make a data-backed case for selling flexible health insurance coverage to prospects in the finance industry.?

Additionally, as voluntary benefits become an increasingly important piece of group benefits strategy, insurers will rely on predictive models to determine which products to up-sell to plan members in response to market trends. Are new popular voluntary benefits like pet insurance here to stay? Predictive models will provide insights.?

Similarly, predictive models can help producers benchmark and optimize coverage levels instead of suggesting more benefits to the plan.?

For example, suppose you discover that providing 100% coverage is a standard expectation for basic healthcare products in the manufacturing industry, but your client's plan only covers 80% of healthcare costs. In that case, producers can suggest reallocating funds to offer higher levels of coverage, especially if that's what's considered the most competitive component in the comparison group.?

The Future Belongs to Those Who Can Predict It?

The incorporation of AI and predictive modelling in group insurance is now a stark differentiator for carriers in a crowded market. According to McKinsey & Company, the usage of artificial intelligence and machine learning in data analytics is valued at over €1.2 trillion in value globally, with all the top players in the EMEA region viewing the uptake of predictive analytics as one of the top ten C-level priorities.?

By reducing quote turnaround times and providing tailored coverage options, these tools enhance customer experiences while driving revenue growth.?

The Majesco Intelligent Sales & Underwriting Workbench offers a suite of AI-powered tools for employee benefits carriers. These include AI-assisted census file scrubbing, a predictive analytics and modelling recommendation engine to help unlock optimal plan designs, AI-driven quote assignments, and more.??

Majesco is also actively integrating Generative AI (GenAI) into its insurance solutions. Majesco Copilot will provide insurers with a competitive edge by enhancing operational efficiency, productivity, user experiences, and delivering cost-effective solutions. This is happening across the Majesco ecosystem to streamline insurance processes such as policy, billing, claims, underwriting, distribution management, digital portals, and loss control. This integration brings advanced analytics to the core of operations, driving optimization and unlocking powerful insights.??

The future of insurance underwriting is set to be transformed by AI, empowering those who can leverage predictive modeling to enhance profitability, accuracy, efficiency, and decision-making processes.