The Future of AI in Motor Claims Processing
June 12, 2023

Artificial Intelligence (AI) is sparking discussion across all industries, with motor insurance being no exception. The technology is constantly evolving, with new advances and use cases being revealed by the day. Here we discuss the future of AI in motor claims, including its possible applications, and how it may benefit insurers and their customers.

Three use cases for AI in motor insurance claims

Artificial Intelligence has applications throughout every stage of the motor claims process, with some of these already being explored by insurers. Here are just a few of these use cases:

1- Customer service & FNOL chatbots

AI language models are changing the way we view customer service chatbots. They’re becoming smarter, more adaptable, and often harder to distinguish from their human counterparts. 

AI-powered chatbots could be used to automate parts of the customer service process – such as answering common queries, and collecting incident data at First Notification of Loss (FNOL) stage.

For example, AI could be deployed within an eNOL incident reporting application to guide customers through the FNOL process. It could be trained to collect specific information about the nature of the incident, damage to the vehicle, and details of policyholders/any third parties.

2- Visual Intelligence (VI) damage recognition

Visual Intelligence (VI) applies the machine learning capabilities of AI to visual media, such as images or video. In motor claims, it could be used to identify the scale of a vehicle’s damage after an incident, and estimate its repair requirements.

Using images uploaded by the policyholder, VI can be trained to recognise which areas of a vehicle have been damaged, and how badly. This could be used to identify total loss, and even inform engineering decisions – such as which parts need to be replaced, and which can be repaired. 

This has the potential to speed up deployment of repair services, as well as help to improve the accuracy and consistency of engineering/deployment decisions. 

3- AI assisted claims processing

From start to finish, the motor claims process incorporates many smaller tasks, some incredibly complex, and some repetitive. AI has the potential to assist with and even automate some of these processes, due to its ability to to analyse data, and implement decisions almost instantaneously.

AI’s machine learning nature means it can quite literally watch how your employees process claims, and apply the same logic and reasoning to automate some of the tasks involved.

For instance, AI could be used within the fraud assessment process to spot red flags and estimate risk – using data from previous fraudulent claims to identify trends. AI can analyse and understand immense amounts of claims data very quickly, allowing it to lighten workloads, and speed up decision making. 

Potential benefits of AI in motor claims

Potential benefits of AI within the motor insurance claims process

AI’s versatile applications pose numerous benefits for insurers, their customers, and their employees alike. Some of these include:

A streamlined customer experience

AI can make it quicker and easier for customers to initiate claims, assisting with document collection, data entry, and guiding incident reporting. 

Additionally, using AI-powered chatbots could facilitate round-the-clock customer service, answering queries and providing guidance throughout the claims journey. 

This would promote a more positive, tailored experience for insurance customers – alleviating many of the usual stressors that come with filing a motor claim.

Right-first-time decision making

AI integrations can be used to promote right-first-time decision making, analysing vast amounts of data to inform accurate service deployment, fraud prevention, and claims resolution.

VI damage detection makes it easier to assess which repair services are required, and allocate the vehicle to the correct solutions the first time around. This helps to prevent delays throughout the repair process, benefiting all parties involved in the claim.

Improved operational efficiency

Using AI can free up operational capacity within your organisation, allowing claims handlers to focus on more complex cases, while AI technology handles the more routine claims.

Machine learning is incredibly effective for tackling routine, administrative procedures – such as those found in less complex claims, like single-party incidents. This allows human resource to be allocated to claims with more technical requirements, such as multi-vehicle collisions, or incidents with split liability.

This benefits everyone involved in the claims process – streamlining the claims journey for your customers, improving workflow management, and providing a more fulfilling work environment for your employees.

Faster claims processing

Because of its ability to automate certain stages of the claims process, AI could lead to faster processing times for insurance claims. 

Machine learning capabilities allow AI to assess claims details, collect the information required, and use this to inform settlement decisions. This could reduce the overall duration of insurance claims, promoting faster resolution without compromising accuracy.

Data-driven insights

AI is able to work with immense amounts of data, and uncover valuable insights very quickly. This will allow insurers to make effective use of historical data to inform risk assessment, improve operational performance, and promote data-driven settlements.

This could be as simple as plugging the software into your database, allowing it to identify patterns and correlations to provide insights almost immediately. This enables insurers to utilise much more data than is possible when using human auditing and analysis.

In summary: AI in Motor Claims

Artificial Intelligence has the potential to impact all aspects of the motor claims process. Its applications include customer service chatbots, visual intelligence for assessing vehicle damage, and data analysis to inform – or even automate – claims processing.

These applications pose numerous benefits for insurers, their customers, and their employees alike, including:

  • A streamlined customer experience
  • Right-first-time decision making & repair deployment
  • Faster claims processing & resolution
  • Actionable insights from historical claims data

Embracing AI will allow insurers to streamline internal processes, improve customer satisfaction, and enhance operational performance. 

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