AI transforms insurance: See 8 examples of how it works

Thorsten Hein
Principal Product Marketing Manager, Risk, Fraud & Compliance Solutions, SAS

The data-rich insurance industry has always relied on analytics – and increasingly, artificial intelligence (AI) – to transform the way data is used for business advantage. For years, the insurance sector has used data and analytical methods to manage potential risks, improve customer service, provide accurate pricing and drive profitability. Adding newer AI tools to the mix delivers even more value.

Here are eight examples of how adopting AI in insurance solutions can boost value for customers, insurance companies and even shareholders.

1. Stronger fraud detection and prevention

Fraudulent insurance claims cost companies billions annually. Advanced analytics helps improve insurance fraud detection by analyzing patterns and identifying anomalies that could indicate fraudulent activity. Predictive analytics, working together with machine learning techniques, provides even stronger fraud prevention and detection.

AI-driven fraud detection uses advanced machine learning algorithms to analyze patterns and identify anomalies that may signal fraudulent activity. By employing predictive models and deep learning techniques, insurers can automatically flag suspicious claims for further investigation.

This AI-powered capability helps insurance companies save money by reducing fraudulent payouts and lowering manual efforts. It also benefits customers by keeping insurance premiums lower. The decrease in fraud-related losses has a direct, positive impact on profitability and shareholder value.

Move insurance forward

Using data and AI insurance solutions responsibly helps you fight fraud, optimize processes, improve customer loyalty and make better predictions – giving the edge you need to continuously innovate, from quote to claim.

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2. Improved customer service and experience

When it comes to customer service and AI, most people think about the role of large language models (LLMs) for chatbots used for customer dialogs. But AI, especially generative AI (GenAI), can do so much more.

By harnessing AI in insurance solutions to analyze customer data, businesses gain deeper insights into customer behavior and preferences, allowing them to offer highly personalized products and services. For example, AI-driven models can identify the types of coverage most valued by different customer segments, enabling insurers to tailor their offerings more effectively.

AI capabilities also position insurers to provide faster, more accurate responses to customer inquiries and streamline claims processing through real-time data analysis. This leads to improved customer satisfaction and higher retention rates, both of which are essential for sustained profitability. Satisfied customers are more likely to remain loyal and recommend their insurer, fueling further growth.

3. Optimized underwriting processes

Underwriting establishes the risk profile and appropriate premium for each insurance policy. But traditional underwriting methods rely heavily on historical data, which can be less accurate than real-time data.

Yet real-time data can be incomplete and not entirely free of bias.

Underwriters using AI tools and technologies can incorporate vast amounts of data from a wide range of sources, including alternative data like social media, credit scores and telematics. They can also generate synthetic data to avoid data scarcity and privacy constraints. This diverse data pool enhances the accuracy of risk assessments.

By using AI and business intelligence tools, insurers can streamline the underwriting process to make it faster and more precise. This reduces operational costs and minimizes risk exposure. Improved underwriting accuracy in financial services industries also translates to better financial performance and lower loss ratios.

Insurers race ahead to adopt generative AI

A study by Coleman Parkes of 236 insurance industry decision makers showed that 9 out of 10 insurers planned to invest in generative AI over the next year. Insurers surveyed cited data privacy and security as two of their biggest concerns about GenAI. They also cited the need for training, governance technology, transparency and accountability.

On the upside, organizations that have embraced GenAI (across all sectors) are seeing big benefits that include greater customer retention, improved employee experience and satisfaction, and reduced operational costs.

As AI continues to evolve, its role in shaping the future of insurance will become even more significant, making it imperative for insurers to adopt and integrate agentic AI into their digital strategies today. Thorsten Hein Principal Product Marketing Manager, Risk, Fraud & Compliance Solutions SAS

Read the blog post Read a blog post about agentic AI for insurance

4. Efficient claims processing

Timely, accurate claims processing is critical to any successful insurance business. AI streamlines insurance claims analytics and management by enabling real-time analysis, accelerating the entire process. Advanced AI-driven systems can automate various steps in the claims workflow, from initial reporting to final settlement.

AI-enhanced claims processing improves customer satisfaction by reducing wait times and increasing transparency. For insurance companies, it lowers administrative costs and minimizes the likelihood of errors or fraudulent claims going undetected. Ultimately, this boosts the company's reputation and profitability.

5. Predictive modeling and risk management

For certain types of insurance, such as property and casualty or life insurance, AI-powered predictive modeling can be the core of a winning strategy. By integrating data from IoT devices and sensors, insurers can monitor the condition of insured assets in real time and predict potential issues before they escalate.

This proactive approach using AI in insurance not only reduces the risk of large claims but also delivers value to customers by preventing losses and extending the lifespan of their assets. For shareholders, the reduction in claims frequency and severity results in better financial stability and enhanced profit margins.

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6. Enhanced marketing and customer acquisition

AI in insurance gives insurers new ways to optimize their marketing strategies and customer acquisition efforts. By analyzing demographic data, purchasing behaviors and digital footprints, AI models can identify potential customers who are most likely to need their products. AI-driven insights also help insurers craft highly targeted and cost-effective marketing campaigns.

This precise approach reduces the cost of acquiring new customers and maximizes return on marketing investment. Shareholders benefit from these efforts, which lead to higher growth rates and more effective use of marketing budgets.

7. Better customer retention strategies

Retaining existing customers is always more cost-effective than acquiring new ones. Providing an excellent customer experience is key to achieving this goal. AI-powered insights into customer behavior give insurers the information they need to predict which customers are at risk of churning. By identifying the factors contributing to dissatisfaction, insurers can take proactive steps to improve retention.

For example, AI can help insurers offer personalized incentives or more attractive policy options to customers who have considered leaving. High retention rates reflect customers who have received tailored, attentive service, leading to a stable and loyal customer base that drives recurring revenue.

8. Competitive advantage through innovation

By continuously innovating and strengthening their AI capabilities, insurance companies can stay ahead of market trends. In turn, they can adapt quickly to changes in customer needs and regulatory requirements.

As AI-driven innovation helps differentiate insurance products and services, it also optimizes internal processes and boosts operational efficiency. Shareholders recognize that staying at the forefront of AI innovation is crucial for securing long-term market growth and sustainability.

The long view for AI in insurance

AI has transformed the insurance industry, with emerging technologies like GenAI continuing to drive significant change. From enhanced fraud detection to improved customer service, streamlined claims processing and more effective risk management, AI holds immense potential for those who embrace innovation.

For today and tomorrow, AI can open the door to exploring new opportunities. For instance, the use of synthetic data can help insurers address biases and create more equitable models.

Insurance companies that use the power of data and AI can expect ongoing improvements in customer satisfaction, operational efficiency and financial performance. These successes pave the way for long-term success.

AI transforms insurance

See 8 examples of how it works