Can AI replace the role of surveyors in Motor insurance?

After the quarter of the 21st century, the role of Artificial Intelligence (AI) is becoming a significant development in almost every domain like defense, IT sector, banking, manufacturing etc. For instance, the use of AI and drone technology in Russia-Ukraine theater is a living example of it. In this process, Artificial Intelligence (AI) has also entered into the insurance sector. For different stakeholders of insurance paradigm, the role of AI has been different. Therefore, it has become a matter of debate specially with respect to role of surveyors in motor insurance. Let’s delve into specific question related to it – Can AI replace the role of surveyors?

Before getting into details of the discussion, let’s understand the role of surveyors in Motor insurance. Surveyors are basically third-party stakeholder who provide objective and unbiased information, often acting as neutral experts in situations to balance out interest of two parties i.e., insured (policyholder) and insurer (insurance company). Their primary responsibility is to conduct thorough inspections of damaged vehicles to determine the extent of damage, identify the cause, and estimate the cost of repairs. Surveyors act as the eyes and ears of the insurance company on the ground, ensuring that claims are genuine and accurately represented.

Making of the debate

With the surge of AI, now insurance companies have started using these technologies to get done works that the surveyors conventionally performed. For instance, some leading technology companies like Claim Genius, Sirius Point, Tractable, Guidewire, etc, have entered into the insurance domain. For instance, Sirius Point uses AI to analyze driver behavior and risk. Similarly, Tractable is a company that leverages AI to automate insurance claims processing. On the same line, Guidewire is a software company that provides AI-driven solutions for insurance carriers. These developments have raised the relevance of third-party surveyors in motor insurance.

Let’s understand these dynamics with an example, conventionally surveyors used to verify policy details, examine the accident scene (when necessary), and prepare detailed reports that help insurers make informed decisions about claim settlements. Now the same work is being performed by the technology companies. These techs take photograph of the vehicle, assess the loss and subsequently recommend to the insurer about the liability by indemnifying losses.

From the prism of insurers

Over the period of time, insurance companies have fed up with the lack of integrity among surveyors. Massive corruption, negligence at work, and a lack of dedication by surveyors have harmed insurance companies significantly. Insurance companies are serious about it. According to a 2020 report by the IRDAI, the motor insurance leakage in India is estimated to be around 17-20%. This translates to a loss of around ₹ 20,000-25,000 crore annually. The primary causes of leakage include unreported claims, misstated policy details, and third-party payments in lieu of surveyors. The real picture of leakages could be even scarier. Therefore, insurers are keen to bring technology to reduce the element of discretionary power.

Along with this, the quality of work of the surveyors is also threatening their existence in insurance companies. For instance, photos taken by the surveyors are not in line with the demand required by the insurers. Sometimes, damages are allowed by the surveyors that violate principles of insurance, like the principle of indemnity and the principle of proximate cause. It means surveyors allow repairs/replacements that are not in line with the impact. Similarly, in some cases, repair is required but the replacement is given by surveyors.

Also, some surveyors reject claims to please insurance companies, which not only harms customer satisfaction but also the insurer as well. It is so because once the insured approaches the court, the insurer has to pay the amount with interest and expenses. Thereby, the recent report published in TOI shows that in the motor own-damage segment, unlike New India, which has a claims repudiation ratio of only 0.2%, other companies like Iffco Tokio (5.8%) have a high rate of rejection.

Surveyors’ frame of reference

If we look at the same changes from the prism of 3rd third-party stakeholder, i.e., a surveyor, it also holds value. One of the prime effects of AI would be job loss. As per stats, in the Indian insurance sector, there are roughly 14,000 licensed surveyors. Their families are dependent on this, and thereby, economic relations in terms of purchasing power are closely related. Therefore, it would not be fair to imagine the insurance sector to grow under the umbrella of “Jobless Growth”.

Similarly, AI is a mechanical humanoid. It means it would think as per the data input given. There is less possibility that AI would think beyond the data feed. Therefore, there is a high possibility of manipulation by the dealership/workshop through biased data. There would be no 3rd party in question. Recently, I have dealt with a case where the issue of NCB was involved. If one goes by just the previous insurer, NCB was correct. Once you go into details, then only you can witness the fraud done by the insured. Such technicalities could not be assessed by AI since data could be manipulated.

Also, not all damages are visible in photographs. Internal mechanical issues, prior damages, and context around an accident require physical inspection and expert interpretation. Human surveyors excel at making nuanced judgments that AI may misinterpret or overlook. For instance, if an approving officer faces an issue concerning assessment, whom would he/she call to clear the doubt? AI?

Also, would AI be able to distinguish between external damage and internal breakdown? For instance, recently, I came to know about the case where a spur gear was broken in the gearbox. How would AI determine that a mechanical breakdown has damaged the case or external impacts have damaged the gearbox case and spur gear?

The flip side of the issue

On the same line, liability in road accidents often involves interpreting intent, environmental conditions, and third-party interactions — areas where human reasoning is still superior. During the visits in case of major loss, I have witnessed that surveyors take a note of the facts produced by the insured. Subsequently, based on the information provided, the concerned surveyor assesses the claim and fixes the liability of the insurer after indemnifying losses. Also, Many policyholders value human interaction, especially during stressful events like accidents. Surveyors provide empathy and clarity, which AI struggles to replicate.

Similarly, Insurance regulation in many jurisdictions still mandates human oversight in the claim evaluation process. Full automation may conflict with current legal frameworks. Even if IRDAI allows full automation, the insured would be at the backfoot because who would be made responsible in the court of law? The insurer would put the blame on AI, and the dealership/workshop would put forward AI. Is it possible to bring AI into the court of law for prosecution? In such a scenario, approving officers would be on the receiving end for recovery instead of the surveyor in case of auditing or legal proceedings.

Hybrid Approach: The Future of Surveying

Rather than full replacement, the most probable scenario is a hybrid model where AI augments surveyors rather than replaces them. Thus, the role of surveyors should be intact, but they should be integrated with the AI for the best use of AI. It would create a win-win situation for all stakeholders. It would increase efficiency in claim processing. For instance, AI handles routine assessments and documentation, allowing surveyors to focus on complex or high-value cases. It is so most of the time of surveyor is wasted on documentation and compliance.

Similarly, it would lead to consistency in the process. For example, Standardized AI evaluations reduce variance in damage estimates. Therefore, it would help surveyors in case of ambiguity, in case of loss, or damage. In such a case, the concerned surveyor may take a specific loss and assess using AI to know the age of the loss and make a decision accordingly.  Thus, AI tools can serve as decision aids for less experienced surveyors.

Also, during peak periods (e.g., after natural disasters), insurance companies have noted fraud and corruption by the officials because pressure to handle a large number of claims in a shorter period would lead to discretionary power. Often, the discretionary power breeds corruption. In such a scenario, AI can process bulk claims rapidly, supporting overwhelmed human teams.

In conclusion

AI holds transformative potential for the motor insurance industry, particularly in automating routine tasks, reducing fraud, and accelerating claim settlements. However, it is unlikely to fully replace the role of human surveyors in the foreseeable future. The complex, context-rich, and interpersonal aspects of surveying require human judgment, ethical reasoning, and empathy — qualities that AI has yet to replicate.

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