Bottom Line: How Insurance Policy Admin Systems Can Boost Revenue

Introduction

Policy administration systems (PAS) within the insurance sector are generally associated with efficiently managing and processing insurance policies. They’re rarely top of mind when it comes to revenue generation, but that is rapidly changing through AI and Machine Learning (ML). Both technologies can significantly transform insurance PAS systems by harnessing their data records to generate specific data-driven insights, subsequently fueling new business opportunities.

The AI/ML Revenue Revolution

Leveraging big data for automation, underwriting, and risk assessment is nothing new, but imagine how AI and predictive analytics can help with personalization and recommendation in a way that distribution channels will be automatically fed with insights that optimize their performance and generate more premiums.

AI and ML provide systems with the ability to learn and improve as they digest data and receive feedback that creates a learning loop. Relying on PAS data means you can ultimately understand customer behavior and motivation and predict their actions at any point in time, providing them with the right insurance product throughout their sales journey.

In addition, there are indirect ways in which AI predictive analytics can reduce costs and streamline automation. With fraud detection and prevention, AI algorithms can analyze patterns and anomalies in claims data to detect and prevent potentially fraudulent activities, reduce losses and operational costs, and contribute to overall profitability.

Claims processing optimization is another area where AI can reduce the time and resources required for settlement, resulting in faster claims processing and improved customer satisfaction.

But AI predictive analytics can play a bigger role in generating new revenues in two new ways:

• Marketing at the point of sale.  At this point in the customer journey, AI predictive analytics can enable insurers to target specific demographics with tailored marketing campaigns based on customer personas from their book of business. That data is available for AI models within PAS and can be easily leveraged. Targeted marketing efforts can increase lead conversion rates and generate more sales opportunities.
• Optimize inforce customers. Machine learning models can analyze customer data, behaviors, and market trends to recommend different products and highlight cross-sell and upsell opportunities to brokers and agents, further pushing them along to the agents through PAS record-keeping systems. Recommending additional coverage or complementary products based on nano-segmentation, highly personalized and specifically tailored to individual customers at the right moment in their sales journeys, can increase premiums dramatically.

This means that agencies don’t necessarily need to rely on their agents to pull their customer lists to generate opportunities. Instead, they can monitor and track the needs of their customers automatically and follow through on fulfillment, optimizing their agents’ resources and performance. This is also extremely important in an industry suffering from a current 30% agent turnover, leaving behind a corresponding 30% orphaned policies that generate only 50% premiums compared with a serviced policyholder.

The Final Word

It’s a new world for insurers’ PAS systems. By incorporating AI and ML, insurers can optimize processes, enhance customer experiences, and make data-driven decisions while also impacting their bottom lines by generating new opportunities for their distribution channels, with minimum resources and heightened efficiency.

PAS’ indelible impact on operational efficiency, customer satisfaction, product flexibility, data analysis, risk management, and compliance can indirectly contribute to revenue growth by attracting and retaining customers, optimizing pricing, and responding effectively to market changes.

To learn more about Sapiens and Atidot’s partnership, click here.