How Generative AI Affects Insurance Claims Processes and Underwriting

Claims

Claims processing is under strain due to numerous outside factors including a rising number of claims, legacy systems and customer expectations, and increased claims complexity. Insurers are using generative AI (gen AI) to change the way they operate and improve decision-making. In the face of industry demands and the necessity to outpace competitors, insurers are turning to AI to deploy a platform that will enhance their user experience and create more value.

Here are some of the ways intelligent automation (IA) and gen AI improve the claims process:

• Personalized customer experiences: Greater understanding of policies and various documents, particularly concerning individual customer needs.
• Data analysis and pattern recognition: Added value in decision-making by accessing data efficiently.
• Automation of routine tasks: Manage repetitive work and synthesize work between employees (e.g., call representatives and claims adjustors).
• Risk assessment and fraud detection: Analyses of data sources and insurance policies, along with recognizing fraudulent claims.

Effective management is crucial to harness the full potential of gen AI across the team and to involve users in the transformative journey, addressing use cases and refining employee processes. To maximize gen AI's impact, concentrate on internal functions that may not be operating at their peak efficiency, utilizing gen AI to target specific process points for enhancement. While gen AI proves to be a valuable tool, it's essential to remember critical human elements, including ethical considerations, judgment, data privacy and adherence to regulatory compliance.

Underwriting

Underwriting holds a significant role in insurance operations to assess and manage risk, specifically to set appropriate terms and conditions for insurance policies. Insurers are turning to tech tools like gen AI to improve these processes and assessments.

Use cases

Risk assessment: Analyze large amounts of data to identify patterns and correlations that may not be apparent in traditional methods. Leveraging gen AI can enable insurers to assess risk with more accuracy and in turn leads to better-informed underwriting decisions.

Fraud detection: Improve fraud detection by using advanced analytics to uncover patterns of fraud. This enables the underwriter to spot inconsistencies provided by the applicant that can result in further investigation.

Policy renewal: Continuous monitoring of changes within behavior and history to assess whether or not adjustments to premiums are necessary.

Customer segmentation: Enable underwriters to categorize applicants according to multiple factors, allowing for more accurate and precise pricing and requirements.

While AI can increase underwriting productivity within insurance organizations, the adoption of generative AI poses organizational risks, raising questions about accountability in the event of unforeseen complications. To avoid risk, clarifying responsibilities within an organization is crucial in navigating potential challenges arising from the use of this advanced technology.

Revolutionizing Claims Management

As it stands today, the growth and variety of products and services in the insurance space is phenomenal. But managing this level of growth and opportunity has not yet matured enough to always enable insurers to gain the highest return on investments (ROIs). Insurers who await the perfect automation solution fall behind, while those who have embraced it find themselves at a standstill. So, how can insurers break free from stagnation and genuinely revolutionize the claims process?

• Consumer-centric approach: Identify customer needs for enhanced customer experience and evaluate improvements necessary for our own customer service.
• Strategic automation adoption: Utilize automation for its intended purpose and explore creative applications to maximize value.
• Employee-focused technological integration: Assess how technology impacts and benefits employees and designate a central figure to oversee the innovative strategy.
• Collaborative process evaluation: Team collaboration to identify process gaps and leverage intelligent automation (IA) to address numerous use cases.
  

The challenge of claims transformation lies in breaking down the transformation into manageable steps to avoid overwhelming the organization. Starting with major overhauls may lead to counterproductive perspectives if success is not achieved immediately, as the insurance industry is still in a phase known as 'speed dating' with technology.

The seamless integration of people, processes and technology is crucial for successfully evolving internal frameworks, with proper diligence and objectives designed to maximize and implement a growth-driven transformation.

To learn more about key stages to success and the true value of intelligent automation in insurance, read our e-book, Breaking Down Barriers in the Insurance Industry.