Leveraging AI to reduce risk and increase fleet management efficiency

The motor fleet insurance industry faces many challenges in today’s dynamic environment. From drawn-out claims processes to supply chain issues, there are many opportunities to evolve and embrace new technologies. A recent report found that only 32% of insurance decision-makers feel they know enough about their fleet and drivers to get the most out of their fleet insurance – a clear indication that fleet managers are struggling with a lack of data and insights to make the right decisions for their businesses.

The good news is that new technologies, specifically artificial intelligence (AI) software solutions, are helping to give them the insights they need.

Let’s take a deeper look at the current challenges fleet managers are facing, and how new technologies can alleviate these issues.

What kind of challenges are fleet owners facing right now?

There are several challenges affecting the automobile industry right now. Here are a few of them:

Semiconductor shortage impacting fleet repairs

In 2022, automobile makers faced a severe semiconductor shortage due to the cancellation of orders for microprocessors in 2020.

As video game and other consumer electronics companies have already snapped up the capacity left on the table, it became difficult for auto manufacturers to get their hands on what they need. It caused a severe shortage of new and used cars in the marketplace, adversely affecting automobile makers and threatening to disrupt their operations.

Moreover, due to such shortages, automakers cut production by 10.5 million units in 2021 and 3.6 million units in 2022. This shortage means fleet managers don’t have easy access to new vehicles if their current ones get damaged, and fleet repair costs are much higher now.

Extremely slow claims processing times

Automobile fleet managers are increasingly struggling with slow claims processing times, resulting in costly delays and loss of business opportunities. Thirty-six percent of fleet managers think the insurance process is too time-consuming.

Not only is it a waste of time for fleet managers to remain present at the insurer’s office for hours on end, but in some cases, the process can be delayed further. Ultimately, it can create cash flow issues when purchasing new vehicles or executing repairs on existing ones.

A long wait time for claims processing also increases the likelihood that fleet managers will become frustrated with their current insurers and seek out another provider who may offer faster turnaround times. With so many insurance companies vying for customers, it’s crucial to be competitive and offer attractive services that can set them apart.

Lack of accurate damage inspection and cost estimate analysis

The process of inspecting and analyzing damages to vehicles can be a time-consuming and costly endeavor. Manual fleet inspections also require more time than automated methods, leading to increased labor costs and a higher risk of errors due to human fatigue or oversight. What’s more, manual inspections can be influenced by external factors such as rough weather or terrain that can impact the accuracy of the assessment.

We know that accurate inspections are essential for preventing financial losses. However, when relying on manual inspection processes, there might be some inconsistencies in reporting. Without the ability to accurately assess the damage, the potential for losing money increases significantly due to incorrect cost analyses and estimates. Also, inaccurate data can cause issues in asset tracking, fleet management, and forecasting future costs.

How is AI changing the fleet insurance industry?

Now that we’ve discussed how current systems impact fleet managers and their businesses, let’s look at how artificial intelligence (AI) can solve these issues.

Here are a few ways AI-led solutions can help fleet managers:

Conduct deep-dive inspections anywhere, any time

With AI-driven software integrated into mobile devices, managers can ensure their fleets are operating in compliance with safety regulations and quickly identify potential issues that could lead to costly repairs or accidents.

AI technology can also help fleet managers stay on top of fleet maintenance schedules for their vehicles, as it can detect changes in performance levels that exceed the manufacturer’s original specifications. This helps ensure vehicles remain roadworthy and safe at all times.

Additionally, the inspection process can even happen remotely, before the vehicle is returned by the customer or driver. The user can initiate a damage assessment from their mobile device without the need to commute anywhere, cutting down processing times when the vehicle is physically returned. Fleet managers can then initiate the claims and repair processes immediately, and reduce the overall time that vehicle is out of the market.

By providing real-time information about their fleets’ condition and safety status accessible from anywhere, fleet managers can proactively avoid accidents by catching problems before they arise as well.

Automation of the claims process

AI solutions allow insurance providers to streamline claims by automating processes and reducing human effort. Underwriters or policyholders can easily capture evidence, process claims documents, analyze data, and make decisions quickly. Ultimately, it allows insurers to process claims in a fraction of the time it usually takes.

In addition, fleet managers no longer have to wait for an insurance agent or adjuster to verify the claim before processing it. Previously, it used to take days or weeks to process, but now it can be done in hours and sometimes minutes. This capability helps fleet managers ensure business continuity at all times.

Integrate fraud detection using Visual Intelligence

Visual Intelligence, an advanced form of AI computer vision, is quickly becoming an invaluable resource for insurers to detect fraudulent claims. AI helps to bridge the gap between incomplete data sources and accurate analysis, providing a more holistic view of fraud cases.

AI-driven fraud detection automates the process of identifying suspicious activities by using algorithms to compare claim details with data from other claims or open-source websites. Using geolocation verification, insurers can accurately establish the origin and destination of vehicles or people to identify suspicious patterns or activities that may indicate a fraudulent claim.

When insurers can assess risks more accurately, they can respond faster to potential threats while improving their customer experience.

Final takeaway

Overall, AI adoption in fleet management has increased due to its ability to automate time-consuming and manual tasks such as inspections and repairs or fleet maintenance. It allows insurance providers to streamline their internal processes and offer better customer service. At the same time, fleet managers can be assured that slow claims processes and supply chain shortages won’t affect their business as their providers have access to more intuitive and intelligent technology.

Ultimately, AI can free up valuable resources so businesses can focus on more strategic initiatives.

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Author: Julio Pernía Aznar, CEO of Bdeo