We’ve all heard the stories.
A perfectly drivable car is allegedly taken off the road for a few hours and returned with just enough damage to support an insurance claim. Elsewhere, repair bills are inflated, accidents are exaggerated and genuine damage is mixed with unrelated repairs.
Insurance fraud is not a new problem. What is changing is the technology available to insurers to detect it.
For years, processing a motor insurance claim has largely depended on physical inspections, paperwork and human judgment. An assessor examines the vehicle, determines the extent of the damage, estimates repair costs and submits a report before the insurer can make a decision.
The process is necessary, but it can be slow, particularly when claim volumes are high.
Artificial intelligence is beginning to change that equation.
Today, vehicle assessment technology can analyse photographs of damaged vehicles, identify affected components and compare the damage against extensive databases of vehicle parts, models and previous assessments.
This does not mean that human assessors are about to disappear. Instead, their roles are likely to change.
AI can handle some of the repetitive work that consumes an assessor’s time, allowing human experts to concentrate on cases that require professional judgment. A photograph uploaded by a customer could, for example, provide an initial assessment within minutes, with a human assessor subsequently reviewing and validating the findings.
For motorists, that could mean shorter waiting times and a less frustrating claims experience.
But speed is only one part of the opportunity.
Insurance depends heavily on accurate information. When two assessors examine similar damage and arrive at significantly different estimates, questions can arise over consistency. AI-assisted systems can help standardise the assessment process by applying the same criteria across claims.
The technology could also give insurers another tool in the fight against fraud.
Damage does not always tell the same story as the accident reported by a claimant. The location, severity and pattern of damage can sometimes raise questions about whether the vehicle was involved in the incident described.
AI systems can examine large volumes of images and data to identify patterns and inconsistencies that might otherwise be missed during a routine assessment.
That does not make the technology infallible.
AI can make mistakes. A photograph may not capture every aspect of a vehicle’s condition. Unusual damage may be difficult to interpret, while poor-quality images can affect the accuracy of an assessment.
There is also a larger question that the insurance industry must confront: how much decision-making should be handed over to machines?
A claim is not simply a collection of photographs and repair costs. Behind every claim is a customer who expects to be treated fairly. If technology is used to reject or delay a claim, insurers must be able to explain how that decision was reached and provide an avenue for human review.
That is why the future of insurance is unlikely to be about replacing people with machines.
It will be about combining the speed and analytical power of technology with the judgment, accountability and empathy of people.
In Kenya, where the insurance industry continues to grapple with fraud, efficiency and customer confidence, that combination could be particularly important.
MUA Insurance Kenya, is already exploring how vehicle assessment technology can support this transition. The broader lesson, however, extends beyond one insurer.
The motor insurance claim of the future may begin with a photograph uploaded from a customer’s phone, be analysed by an artificial intelligence system within minutes and then reviewed by a human expert before a decision is made.
So, will your next motor vehicle insurance claims assessor be human?
Quite possibly.
But increasingly, they will have a very capable machine working alongside them.
(The writer Mercy Ndegwa is the Head of Operations at MUA Insurance Kenya)
