AI and Its Impact on Automotive Claims by Olivier Baudoux
AI and Its Impact on Automotive Claims by Olivier Baudoux
Thanks to four trends, AI can improve efficiency and cycle time and meet policyholder expectations for a streamlined, digital auto claims experience.

For more than six decades, innovators have attempted to unlock the full potential of artificial intelligence (AI). It wasn’t until the past decade that the science finally caught up to expectations. Today, the AI market is on track to reach $500 billion by 2024. COVID-19 has fast-tracked AI adoption and acceptance.

McKinsey & Company says that “insurance will shift from its current state of ‘detect and repair’ to ‘predict and prevent,’ transforming every aspect of the industry in the process.”

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AI-enabled solutions have opened up new possibilities for auto insurers and collision repairers. From detecting a car accident with IoT technology, to instantly processing a payment for completed repairs, the opportunities are endless. First on the list for most carriers, however, is using AI to automate the appraisal process and produce a “touchless” estimate. This can improve efficiency, shorten cycle time and meet policyholder expectations for a streamlined, digital claims experience. Now, thanks to these four trends, creating that experience is within reach.

1. Shifting Methods of Inspection

Prior to COVID-19, virtual estimating was reserved for low-severity claims. However, the need for social distancing during the pandemic and changing consumer demands spurred the adoption of virtual inspection methods. In April 2020, Mitchell data shows that the use of virtual, or photo-based, estimating more than doubled from earlier in the year. Just one year later, LexisNexis Risk Solutions reported that virtual claims handling has now “settled to a level of a little over 60%.”

This shift opened the door to the long-term aspiration of “touchless” claims and leveraging AI in the appraisal process. Over the last year, virtualization—considered the first level of automation—has resulted in estimate efficiency and consistency gains. From images, appraisers can complete approximately 15 to 20 estimates per day versus three to four out in the field. This has prompted more carriers—nearly 70%, according to LexisNexis Risk Solutions—to embark on the claims automation journey.

2. The Prevalence of Big Data

According to the Center for Insurance Policy and Research, “The successes of AI are also being facilitated by the massive amounts of data we have today. The wealth of data we now create is astonishing, and the speed at which data is generated has only made data management tools like AI even more important.”

The property and casualty industry has always thrived on capturing, analyzing and interpreting data. Whether it’s from mobile devices, automobile IoT sensors or other sources, this data gives decision makers the information necessary to personalize customer interactions and address issues. When it comes to touchless estimating, though, data alone isn’t enough. Access to a comprehensive library of vehicle, repair and historical claims information is needed—along with the ability to quickly interpret that information using AI. In the case of Mitchell Intelligent Estimating, claim details and images are collected. AI then analyzes the data, comparing it with Mitchell’s comprehensive library of vehicle and repair information that spans more than 30 years. From there, the machine-learning algorithms translate the output into component-level estimate lines for appraiser review and approval.

3. Human-Machine Collaboration

Just as humans continually learn and improve, so do machines. As highlighted in Insurance Thought Leadership, “good machine learning systems involve feedback loops…. By letting the machine know what happens on the ‘real world’ side of things, machines learn and improve”—no different from claims adjusters!

Support for a human-machine feedback loop is critical to automating the claims process and can lead to vast improvements in speed and accuracy. An appraiser’s feedback helps teach the machine to make better decisions. As AI-powered solutions remove repeatable tasks, employees have more time to focus on complex claims that may require extra scrutiny.

4. The Growth of Cloud Computing and Open Ecosystems

AI’s dependence on data increases the need for cloud-based systems that can access and aggregate vast amounts of information, making it available from anywhere. These systems help organizations reduce development and maintenance costs, enhance security and accessibility and improve speed, reliability and scalability.

Like cloud computing, open ecosystems are also vital to AI and touchless estimating. Open ecosystems allow AI to easily access data, analytics and software across platforms and providers, giving carriers the ability to create a cohesive, end-to-end claims experience. They also introduce flexibility and choice, PropertyCasualty360 reported.

See also: Designing a Digital Insurance Ecosystem

For instance, through Mitchell Intelligent Open Platform, carriers can select the AI that best meets their needs. That includes AI algorithms developed internally, provided by Mitchell or delivered through third parties such as Tractable or Claim Genius. The AI output is used to produce a partial or complete appraisal.

The Future of AI-Enabled Claims

By 2030, McKinsey & Company predicts that more than half of current claims activities will be replaced by AI-enabled automation. “Claims for personal lines and small-business insurance are largely automated, enabling carriers to achieve straight-through processing rates of more than 90% and dramatically reducing claims processing times from days to hours or minutes.”

With the science now ready to deliver on its decades-old promises, the auto insurance industry has reached a turning point. Carriers can either invest in AI or run the risk of being stranded by the side of the road. Ultimately, organizations that embrace this “new” technology to deliver a digitally driven claims experience will be best-positioned to gain market share and consumer loyalty.

Source: M Power

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