AI-powered underwriting: The future of personalized insurance

Underwriters continue to spend an outsized amount of time hunting for critical information buried in unstructured data and fragmented systems—slowing risk assessment and decision-making. It’s no surprise, then, that insurance carriers are looking for ways to make underwriting faster, smarter and more accurate. With technology evolving rapidly, artificial intelligence (AI) is quickly becoming an essential solution for improving efficiency, reducing errors, and delivering personalized policies.

Across the insurance industry, leaders are recognizing that digitalization, innovation, and AI-powered data strategies are key to achieving future readiness. In fact, according to CGI’s Voice of Our Clients, AI implementations are on the rise, with 40% of industry executives citing AI as their top innovation priority over the next three years.

Smarter predictions, better decisions

Traditionally, auto insurance underwriting has relied heavily on static data such as age, gender, vehicle type, mileage, and even education level. However, that’s starting to change. Insurers are now exploring more dynamic sources of information, like how often a person drives, what condition their vehicle is in, and even real-time factors like weather conditions collected via telematics apps or vehicle sensors. In the future, open data from sources like social media could also help underwriters paint a fuller picture of individual risk.

This is where AI and machine learning (ML) add value. They can recognize subtle patterns in these multiple data sources that humans can easily overlook, allowing for more accurate predictions and informed decision-making. For example, AI can identify correlations between someone’s lifestyle, job, or location and certain risk factors. That means underwriters get more accurate predictions and a more complete view of potential policyholders.

Personalized policies that fit

As carriers move away from traditional underwriting models, they can start offering more personalized products that match real-life behaviors. For example, a cautious, low-mileage driver who avoids hard braking and mostly drives during the day could qualify for a lower premium. Instead of being lumped into a generic pricing category, their policy would reflect their actual driving habits.

This level of personalization is also transforming the life and pensions sector. AI can now analyze everything from health histories to daily activity data from smart devices. A smartwatch, for example, can provide insights into a user’s fitness, sleep, and heart rate. If this data can lead to better coverage or lower premiums, customers may be more willing to agree to share it.

Over time, as AI systems learn from more data, the underwriting process will move from grouping people into broad risk categories to building individual risk models, unlocking highly customized pricing and policy options.

Faster decisions, more satisfied customers

Today’s customers expect more from their insurance providers. They want transparent, fair pricing and policies that reflect their needs. AI helps carriers meet those expectations by dramatically speeding up underwriting. What used to take days can now happen in seconds.

AI-powered chatbots, for example, can interact with potential customers, gather their info, and provide quotes instantly—all with minimal human intervention. The results are less paperwork, quicker responses, and a smoother customer experience.

Some insurers are already achieving tangible results using AI. One large financial services firm collaborated with CGI to launch an AI-driven chatbot to help reduce costs, streamline customer care, and improve client satisfaction. The chatbot currently automates the end-to-end customer care process, handling approximately 500,000 customer support conversations annually and reducing costs by approximately $2.2 million. Overall, customer satisfaction has increased, partly due to the chatbot's 24/7 availability, which has resulted in faster customer service.

Three strategies for starting your AI journey

As with any transformational change, a gradual, cautious, and secure approach is essential. Here are three key starting points for effectively integrating AI:

1. Improve customer service: As seen in the example above, chatbots can retrieve policy or claims information and provide customers with quick and accurate responses. It’s a low-risk solution that operates 24/7 to reduce costs and human error.
2. Automate routine tasks: AI can streamline rule-based, repetitive tasks that don't involve sensitive decision-making, including policy submissions, claims intake and form processing. With tools like CGI Elements360 Workbench, underwriters can focus on higher-value work while AI handles time-consuming administrative tasks.
3. Detect fraud and anomalies early: AI can scan massive datasets for patterns and red flags that might indicate fraud. It’s a powerful way to refine pricing strategies and sharpen risk assessment.

For AI adoption to succeed, it’s crucial to build trust, both with internal teams and with customers. Employees need to see AI as a support tool, not a replacement. At the same time, customers deserve transparency in how AI-driven decisions are made.

To safely implement and expand AI adoption, insurers must create strategies that include three key components:

1. Impact assessments: performance must be regularly monitored and measured.
2. Transparent decision-making: decisions must have clear metrics and explanations.
3. Gradual scaling: expansion must be based on data-driven insights to reinforce trust over time.

This approach will help insurers ensure a smooth and effective transformation, while minimizing risks.

Keeping AI responsible and secure

To unlock the potential of AI in underwriting, it needs to be implemented responsibly. The following guardrails will ensure the responsible use of AI:

• Ethical frameworks: Biases in training data or improper design can lead to discriminatory outcomes. Continuous oversight and refinement of AI algorithms ensure fairness and objectivity.
• Human-in-the-loop procedures: AI outputs should be a supporting tool rather than a replacement for humans in the decision-making process.
• Data privacy: Since AI systems rely on vast amounts of personal and sensitive information, insurance carriers must navigate stringent data protection regulations, such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA), to ensure that consumer data is handled securely and responsibly.

Partnering for long-term success

There’s no doubt that the future of insurance underwriting is digital. Carriers that embrace AI can expect to see better customer experiences, greater efficiency, and more growth opportunities. At CGI, we’re helping insurers lead this transformation with our advanced AI capabilities. Contact me to discover how our team of experts can help you capitalize on new opportunities in today’s digital landscape.