One of the biggest hassles car owners face is when it comes to car repair and insurance claims. This process can be time-consuming, costly, and sometimes confusing. What if AI could assist with that?

A software and services company, Solera, is aiming to transform the vehicle claims space by offering a touchless experience, powered by AI, that applies algorithms from an accurate vehicle-repair database.

Dr. Rana Farag is the AI global portfolio lead at Solera, with technical expertise in sustainability and AI in the aftermarket, claims, and insurance industry.

Frankie Youd spoke to Dr. Farag, to learn more about her involvement with AI and how Solera’s AI works on the collected data.

Dr. Rana Farag

Just Auto (JA): How did you become involved with the AI sector?

Rana Farag (RF): I studied computer science and engineering and from a very young age I took an interest in artificial intelligence and its applications in the real world, not just the theoretical side. I was interested in how we can apply technology to solve real world problems.

I published my bachelor thesis, AI applications on epidemiology. I got a scholarship here in Madrid, that’s what brought me to Spain for the first time to work on artificial intelligence applications to improve vehicle handling and stability.

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That’s how I started marrying the world of AI and vehicles. After a little while, I was recruited in Solera to lead the launch of two new AI products. In nine months, they promoted me to lead the team. Now I’m heading the AI product portfolio of Solera globally.

I help the company define the AI strategy for vehicle claims, build product in the form of building blocks to serve the different segments that we operate in. It’s a sector where AI can bring a lot of value, a lot of automation and cost reduction.

How does Solera use AI to assist the industry?

If we look at this from a top-level point of view, AI’s benefit in general is bringing automation, cost reduction and bringing knowledge that is not there. Knowledge can be in documents and documentation, but in the moment that I need it, I don’t have it until I go and consult it.

Automation is one of the major things that our clients want to have available.

Automation is one of the major things that our clients want to have available. Take, for example, the insurance sector. One of the main topics that they are working towards is customer satisfaction and customer retention. They want to keep the customers happy; customers want a very reduced key-to-key time. We work on how we can make a long journey of a traditional claim workflows that will take weeks happen within minutes. It’s something that we work hard on, and we are achieving that with our customers.

If we think about dealerships and body shops, you get a customer entering through the door and they want to know what’s going to happen next, naturally. They don’t want to go into the waiting room for thirty minutes. They don’t want to wait for the parts to be sourced in three weeks and go back and forth to get a resolution, all the uncertainty. That’s exactly what we help them to avoid. The customer is there in front of you, so it’s a case of how can we serve them as fast as possible?

We have many case studies with body shops, so just by sending photos of the damage to their vehicle, the customer can get within minutes an assessment of what’s going to happen with the vehicle, when to come, how much the cost of repair is, the level of support available and so on.

What is the process used for producing a repair cost estimate?

We take photos of the damage and with the VIN number we know exactly which model we are dealing with, what the options are, materials, parts. We know from research centres if it’s this model, and it’s this car, with this material, this would be the time required and this would be the way of preparation.

If we are replacing, we know exactly from the OEM how to replace, how long it will take, and we can give the best proposal for the repair. And it is all based on data, all based on science. That brings a lot of efficiencies and cost reduction for our customers. They can be advised on what parts can be repaired over, say, parts to be disposed and replaced. Not only do they save money, but there is a sustainability benefit also. Instead of throwing away a very valid part, repairing it can lower carbon footprint as well as cost.

How does Solera’s AI process work?

Solera is a data company. We’re founded on data, and that’s what makes us different. We have invested in data, data infrastructure, ways to treat data, standardise data – even before the hype of artificial intelligence came along, we were very busy.

Our customers get the power of AI that has learned on data, but also retrospectively, they get to understand what was the first assessment, what was the AI prediction then? What was the last assessment? They’re able to see those graphs, thresholds, understand much more.

This all brings a lot of value for them, and a lot of value for us because with repairs we were able to adapt the AI and personalise it.

We have historical data from many years. The value comes from the sheer amount of data that we processed every day, the number of claims that we processed every day. That allows us to adapt and understand market trends and update our AI in real-time.

What are some challenges your customers face?

For our customers, skilled assessors and skilled people who can tell them what’s going to happen with the car is a traditional challenge. They also have a problem with standardisation. This can be helped by AI because AI is always as good as the data that it learns from and here we ensure that we apply the top standards of data preparation; we also work with research centres around the world. We don’t only take data from the market, we collaborate with research centres that can evaluate the best way to repair, inform on how much time is needed to do the repair.

We don’t only take data from the market, we collaborate with research centres that can evaluate the best way to repair, inform on how much time is needed to do the repair.

AI can also serve as the skilled assessor just in a second, giving an assessment and connecting everything together. Connecting the standards of the market to what the insurance industry would want, to the optimal path of repair, optimal use of the body shop, connecting all the dots.

What are some sustainability benefits AI offers?

This year we’ve been having discussions with salvage yards. For the AI team there is an opportunity  to discover ways to work together more efficiently, help them with the inventory, identifying parts, using forecasts and establishing how can we reuse the greener parts.

Having the AI recommend the usage of greener parts is important; the whole ecosystem is waking up to this AI revolution and they are asking what more can we do?

The AI impact for sustainability is something that I’m very interested in.

One example we are looking into is the impact caused by the shop visits themselves. You don’t need to take your car all the way to the body shop and back to have the first assessment done. We have customers in the Netherlands that have deployed a new solution and have told us that using the AI with remote assessment has helped them to cut down the vehicle trips of almost all the vehicles that they assess per year  – in half. That’s a very important carbon footprint reduction.

We also have the ‘repairability index’, which builds on that data standardisation that we’ve been speaking about. When the AI ‘sees’ a piece, a part, that could be repaired and not necessarily replaced, that’s a flag that we put on it to say repair this piece, and that’s what affects repairability. Our AI can improve the repairability index by at least 10%.

By working closer with big outfits in the salvage area, sustainability is boosted; just buy less, consume less and then you’re more sustainable.

What are your predictions for automotive AI in 2024?

I expect to see lots of improved models, less hallucinations, more realistic models, and more realistic outputs, especially when it comes to large language models and generative AI.

In the insurance landscape, I’m already seeing a lot of interest from the different sectors, budgets provisioned to work on AI, adoption barriers being demolished, and people willing to explore more, which is very exciting. 

I think the automotive sector and the insurance sector historically have been slower movers with the adoption of technologies. They would take their time; they would work on something now that people would see in five years. Customer expectations are changing; their expectation comes from their mobile phones – they’re seeing them updated all the time. With the AI revolution that they’re seeing happening, they will expect the same pace of change and improvement from car manufacturing, or their insurance.

I think the automotive sector and the insurance sector historically have been slower movers with the adoption of technologies.

With the revolution of AI, with big data comes big responsibility. Once you have data stored in your infrastructure, you need to make sure that data is saved. You have to be clear that when a treatment of the data is saved, what you’re then building on top of would not cause any harm to anyone and adheres to all standards, for your customers and more broadly to society.

I think this year, we will see a lot of advancement when it comes to insurers and car manufacturers. This means the use of AI in general and generative AI as well, and crucially, meeting with customer expectations.