As artificial intelligence (AI) promises to revolutionize nearly every aspect of the way we live and work, AI in the insurance industry is already driving game-changing results for insurers. And as customer expectations get higher, fraud schemes increase in complexity, and insurers are pressed to improve the bottom line, AI technology is enabling the industry to keep pace.
Key business metrics accelerated by the use of AI in insurance
AI has served the insurance industry for more than a decade, setting new standards for operational efficiency and bottom line metrics while improving the customer experience.
1. Improved customer experience
Customers expect a quick and easy insurance experience, and as insurers struggle to meet this expectation, policyholders are taking their business elsewhere. One report projects that $34B in insurance premiums is at risk each year due to dissatisfied claimants switching insurers, with more than 60% of those surveyed identifying settlement speed as a cause of their dissatisfaction. AI-based claims processing provides the speed needed to deliver on customer expectations while effectively mitigating fraud and risk. For example, a large travel insurer introduced AI-based automation and reduced claims processing from three+ weeks to minutes. And we're seeing the same in underwriting. Advanced underwriting AI capabilities enable insurers to rapidly spot suspicious activity and accelerate the underwriting process with confidence.
2. Improved loss and combined ratios
The use of AI in insurance has proven to be an important tool for improving the combined ratio. Shift’s analysis of millions of claims indicates that property insurers are able to successfully stop an incremental $60,000 for every 1,000 claims analyzed using AI-powered claims fraud detection, and auto insurers achieved an incremental $43,000 for every 1,000 claims. Additionally, adoption of AI-powered subrogation and recovery strategies have the potential to recoup up to an additional 7% of a claim’s total value. And while these individual gains are impactful, a comprehensive AI insurance technology solution can amplify those results, improving the combined ratio by up to 6 points.
3. Increased operational efficiency
As the insurance industry balances the need for both speed and accuracy, a shrinking talent pool is amplifying the challenge to remain efficient. Fortunately, AI has proven itself valuable in this area. For example, AI in subrogation and recovery injects significant efficiency into the process, effectively applying the expertise and experience of an insurer's best subrogation specialists at scale. The application to underwriting is similar, allowing insurers to automate with accuracy. And since advanced AI can not only detect, but also explain the reasons and rationale for alerts and decisions, less experienced team members can make a larger impacts.
Applications of AI in the insurance industry
1. Underwriting Risk Detection and Decisioning
As pressure to accelerate underwriting decisions increases, and a new set of challenges related to digital fraud are threatening to derail any progress towards a better customer experience, advanced AI strategies are successfully fighting back against hidden risk and fraud in policies. Effective solutions leverage a whole suite of AI capabilities, first using it to prepare data for fraud detection by unifying it across internal and external sources, then using methods such as supervised learning and unsupervised learning to connect data to fraud trends including effective document fraud analysis. Finally, advanced network detection models are able to find connections, and deliver those insights to underwriters to help them mitigate fraud, optimize pricing, and spot policy risk before the policy is written.
Impacts of AI in Underwriting Risk Detection and Decisioning
- Improve the customer experience by balancing speed with accuracy
- Mitigate premium leakage and digital fraud with AI detection models
- Optimize pricing and avoid premium increases
- Support underwriting teams to drive operational efficiency
Case Study: Top 5 insurer adopts AI in insurance underwriting, predicts $30M+ in mitigation annually
2. Claims Processing and Decisioning
Policyholders often become dissatisfied when claims processing is lengthy or complex. AI-based insurance solutions are able to address this challenge, creating a fast, fair, and consistent claims processing experience across all channels while minimizing claims losses. Additionally, AI models built for the insurance industry can process claims documents with the same or greater accuracy than that of an experienced human claims adjuster, freeing up top talent to work on important cases and tasks that further add to the bottom line and positively impact the policyholder experience.
Impacts of AI-Based Claims Processing and Decisioning
- Provide consistency, speed and transparency for customers
- Reduce loss and improve claims outcomes
- Save time for human adjusters
- Increase straight through processing
Case Study: Travel insurer implements AI to claims processing and achieves 57% automation while reducing processing time from weeks to minutes
3. Claims Fraud Detection
With the cost of claims fraud reaching $308 billion per year, and up to 2-3% of an insurer’s combined ratio coming from fraudulent claims, the use of AI in insurance fraud detection is an essential tool for maximizing profitability. With the initial introduction of automation, costs came down but it incidents of fraud increased. Best-in-class AI insurance technology can effectively mitigate the risks introduced by automation. Analyzing claims earmarked for automation can spot irregularities, such as doctored or reused photos and documents, that indicate a claim may be illegitimate. Those claims can then be removed from the automation workflow for further review and investigation.
Impacts of AI in Claims Fraud Detection
- Find and prevent more fraud with greater speed
- Make concrete improvements to the combined ratio
- Securely integrate and leverage siloed data sources
- Avoid higher prices as a way to offset costs
Case Study: Large P&C insurer stops $12M in fraud with AI-based detection
4. Subrogation Detection
Approximately 15% of P&C claims are closed with missed subrogation opportunities, costing the insurance industry between $15-20 billion annually. When looking at the potential impact AI-powered subrogation and recovery strategies can have, Shift’s own research has shown that insurers stand to recoup up to an additional 7% of a claim’s total value when AI is applied to the problem.
Impacts of AI in subrogation detection:
- Reduced claim loss
- Improved deductible recovery
- Create larger impact with less experienced team members
- Enable experienced team members to save time and focus on resolving claims
Case Study: Top 25 P&C insurer uses AI to achieve recurring average subrogation recovery of over $1M per month
The future of AI in insurance
In recent years, the use of AI in insurance has made it possible for insurers to overcome some of the industry's biggest challenges while setting new standards for efficiency and profitability. In the future, AI in insurance will continue to play an increasingly important role, eventually transforming the entire industry. And while risks and challenges are inherent to adopting any new technology, Shift's recent survey of insurance leaders found that 81% of respondents consider AI to be an important part of their innovation roadmap, signaling that the potential benefits and opportunity costs outweigh any perceived risks.
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