Underwriters have always walked a fine line — juggling risk assessment and profitability while navigating an ever-changing market. But today, the pressure is higher than ever. Economic uncertainties, evolving customer expectations and emerging risks are altering the insurance landscape. At the same time, efficiency gaps, stricter regulations and rapid advancements in technology are transforming how policies are assessed and issued — faster than most can keep up. The question is no longer whether underwriting will change, but how quickly and effectively the industry can adapt.

According to a recent whitepaper from HCLTech, Modern Approach to Underwriting Intelligence Process, underwriting losses persist in the US property/casualty industry. Yet, underwriters spend 40% of their time on non-core activities, leading to an estimated efficiency loss of $85 billion to $160 billion over five years starting in 2023. At the same time, the commercial insurance industry must contend with macroeconomic factors such as inflation, sluggish rate growth and emerging risks.

Amid these shifts, the rise of AI and, more recently, GenAI is transforming underwriting. While AI has already streamlined data analysis and decision-making, GenAI is poised to take underwriting intelligence to the next level. HCLTech’s Trends and Insights team recently spoke with Kaye Hacker, Vice President of Insurance at HCLTech, to explore how AI and GenAI are shaping the future of underwriting.

The complexity of underwriting and the need for efficiency

Underwriting is inherently complex, involving vast amounts of structured and unstructured data. As Hacker pointed out, the growing availability of data is both an opportunity and a challenge. “Underwriting has tons of data, internal and external, that they need to refer to. If you think about different ways AI has been adopted, it’s around how insurers summarize and use policy information, automate decision modeling and conduct risk assessments,” she noted.

While traditional AI has been in use for years, underwriting still faces bottlenecks in terms of speed and efficiency. With increasing regulatory requirements and customer expectations for faster policy issuance, insurers are actively exploring ways to integrate GenAI to streamline workflows and improve decision-making.

GenAI is emerging as one of the most sought-after innovations in underwriting. However, the industry is still in the early stages of understanding how to harness its full potential. “GenAI is being chased by most insurers right now. I think that's probably the biggest, hottest trend that everybody's talking about. In underwriting, there’s still plenty of opportunities. We’re just on the edge of the advancements,” she said.

According to another whitepaper from HCLTech, Transformation Trends in Life Insurance: New Business and Underwriting, underwriters are now under greater scrutiny to make more precise risk assessments and proactively manage their portfolios. The challenge is to shift from hindsight, where underwriting decisions are evaluated after the fact, to foresight, where risks are monitored in real-time to better anticipate potential impacts.

The whitepaper highlights how HCLTech has built an ecosystem of IPs and product partnerships to drive complete automation and transformation, from the new business and underwriting process to final policy delivery.

Challenges in AI-driven underwriting

Despite the excitement around AI and GenAI, there are significant challenges in integrating these technologies into underwriting. One major hurdle is the cultural shift required among underwriters. “Underwriting has always been a human-based discipline where underwriters pride themselves on judgment and decision-making. When you bring in GenAI, it can be challenging for professionals who believe that their expertise is irreplaceable,” explained Hacker.

Rather than replacing human judgment, AI is positioned as a tool to enhance underwriting capabilities by providing deeper insights and faster data processing. The key challenge for insurers is to ensure that underwriters see AI as an enabler rather than a threat.

Another critical challenge is regulatory compliance. The insurance industry operates under strict guidelines and any AI-driven decision-making must adhere to these regulations.

“Ensuring that the decisions made are compliant with all the rules is crucial. There’s no tolerance for missing regulations or being non-compliant,” said Hacker.

Additionally, data quality remains a crucial factor in AI implementation. Many organizations are eager to adopt AI but lack the proper data infrastructure to support it. “The models are only as good as the data input. If there are issues with the data, the outcomes will be flawed,” cautioned Hacker. To successfully integrate GenAI into underwriting, insurers need a clear strategy that includes:

• A balanced approach: AI should complement human expertise rather than replace it
• Robust governance: A well-defined AI governance framework is essential to ensure regulatory compliance and ethical AI usage
• Data readiness: Organizations must invest in data management strategies to ensure high-quality inputs for AI models

Enhancing customer experience: Speed, transparency and trust

One of the most significant impacts of AI in underwriting is on the customer experience. As Hacker highlighted, the ultimate goal of these technological advancements is to improve service speed, application processing and overall customer satisfaction.

"One of the reasons that insurers focus on efficiency, especially in an underwriting environment, is about the customer experience. It’s to make sure that they are providing the right outcomes quickly, not just individually for customers, but as a group," said Hacker.

Insurance customers rely on fair pricing and efficient claims handling. The underwriting process, along with claims processing, policy issuance and operational costs, directly influences the price a customer pays for coverage. AI-driven efficiency enables insurers to make faster decisions, reduce processing costs and pass those benefits on to the customer.

"The more effective you can be with GenAI, whether it’s for quicker decision-making, evaluating vast amounts of data faster or serving insights to underwriters in real-time, it reduces costs and, ultimately, helps deliver better pricing and faster service to customers," she said.

GenAI also has the potential to make digital insurance platforms more intuitive and efficient, ensuring that customers receive policy approvals, claims settlements and support faster than ever before. However, while AI promises speed, insurers must balance this with fairness, transparency and responsible governance.

"Customers need to feel confident that GenAI is being used responsibly. There are varying perceptions about AI; some embrace it, while others are more skeptical. That’s why insurers must ensure transparency, eliminate bias in models and demonstrate ethical AI usage. A strong governance framework is essential to build trust and confidence," added Hacker.

This balance between efficiency and ethics will define the next phase of AI-driven underwriting, ensuring that while automation accelerates processes, customer confidence in the system remains unwavering.