--AI is helping organizations reduce claims processing times from days to minutes. Half of all insurance claims processing activities will be replaced by AI-based automation by 2030.
--AI is playing a pivotal role in reducing fraud. For example, the technology can quickly compare an incident with other cases and assess whether the damage lines up with the amount that is being requested in a claim.
--A digital insurance process can drive a 20% increase in customer satisfaction scores and a 25% to 30% reduction in related expenses, and AI can help organizations provide the digital-first solutions that customers prefer nowadays.
AI is having a transformative effect on the insurance industry, helping organizations with everything from speeding up claims processing to reducing fraud. According to Juniper Research, investments in AI are expected to save auto, property, life and health insurers almost $1.3 billion in 2023, up from $300 million in 2019.
These savings are helping organizations offer more cost-effective, personalized insurance solutions, resulting in increased customer satisfaction and loyalty. In this article, we will explore some of the key ways AI is making a big difference for financial organizations with insurance offerings.
1. Automating processes across the insurance lifecycle
Historically, processing a claim has been one of the most time-consuming tasks in the insurance lifecycle, requiring a significant amount of human intervention. Policyholders must call their insurance providers and then wait on hold, or for a call back, before handing over personal information and, eventually, relaying the details of the incident. When too much time passes between the incident and the report, there's a good chance that stress and possible trauma may also distort the recollection of events.
AI is helping organizations reduce claims processing times from days to minutes. According to McKinsey, half of all insurance claims processing activities will be replaced by AI-based automation by 2030. Claimants can submit damage evidence digitally, and advanced AI algorithms can identify patterns in photos or videos of the damage, check for signs of fraud and predict costs to repair. If the algorithms do not detect any issues with the claim, the result is a faster, more pleasant process for policyholders. Not to mention, a much more cost-effective solution for the insurer.
According to Accenture, a majority of policyholders view settlement speed as the primary consideration when choosing an insurance product or service. Faster claims processing means faster pay-outs and happier customers.
See also: Key Challenges on AI, Machine Learning
2. Reducing fraud
Fraud is one of the greatest threats to financial companies and insurers. It can also harm policyholders when it occurs too frequently, as organizations need to charge higher premiums to recover their losses and the legal costs of pursuing fraud cases.
AI is playing a pivotal role in helping reduce fraud in insurance. For example, in the underwriting stage, advanced analytics can help identify signs of fraud. The technology can identify abnormal behavioral patterns or inflated claims by quickly comparing an incident with other cases and assessing whether the damage lines up appropriately with the amount that is being requested.
Incidents involving vehicle or property damage can be particularly dramatic. The affected parties are not always calm while gathering photo or video evidence. Visual intelligence applications, a specific type of AI, can play an important role here, helping guide the policyholder through the evidence-gathering process. AI-driven applications can help claimants collect credible, accurate evidence, eliminating opportunities to exaggerate or tamper with it before submission.
Finally, when combined with IoT devices, AI technology can detect any unexplained delays between an incident and the submission of evidence--for example, by examining timestamps and geolocations to determine whether there has been any evidence tampering.
3. Improving the customer experience
Until recently, trust between an insurance provider and end customers was primarily established through face-to-face interactions.
Consumers nowadays prefer a digital-first process to contract insurance services and resolve incidents in the quickest way possible. The social changes brought on by COVID-19 have also increased the demand for solutions that don’t require an in-person presence.
According to McKinsey, a digital insurance process can drive a 20% increase in customer satisfaction scores and a 25% to 30% reduction in related expenses. AI can help organizations provide these digital-first solutions. By automating repetitive work, organizations can reduce operational costs and focus more on showing their customers that they’re prioritizing their requests and working toward a solution.
When organizations can personalize their customer support and make the insurance process as simple, transparent and efficient as possible, the result can be a boost in both short-term customer satisfaction and long-term customer loyalty.
See also: The Importance of Explainable AI
The AI-driven future of insurance
AI empowers organizations offering insurance-related services with better data and insights to make better decisions. As a result, financial institutions can enhance their insurance offerings, streamline operations, improve customer experiences and maintain competitiveness in this rapidly evolving landscape. As AI advances, we can expect more organizations to onboard the technology to refine their offerings and stay at the forefront of the industry's digital transformation.