Car Claims Require a Data Engine

Car Claims Require a Data Engine

by omnius
Februar 6, 2019

With total car claims paid on the insurance market in Europe rising steadily, and global car ownership rates projected to grow in the coming decades, car insurers are being further incentivized to provide an efficient and scalable internal system which benefits policyholders and employees alike.

Insurers get a bad rap in this day and age. Considered to be dragging their feet when it comes to innovation and customer experience, in Europe, there is nonetheless a strong degree of trust in car insurance providers. But while the core business of insurance is an accepted and relatively trusted necessity, there is always room for improvement in customer interaction and care.

The EU is a traditional fortress of automotive manufacturing industry. With more than half its population owning cars in 2016 and a thriving technology sector developing everything from IoT sensor hardware to smart insurance blockchain strategies, it is a healthy breeding ground for new technologies which can optimize even more aspects of car ownership.

Below we look at the use of artificial intelligence to enhance claims processing.

The first step of car claims is getting the claim to the right place as quickly as possible. With AI, an insurer can rapidly index the case to route, prioritize and assign to the relevant department during the triage phase. For policyholders, a quick response is vital. If their feeling is that of being stuck in a sea of red tape, tensions arise, causing problems on both sides. Avoiding this is the first step in a positive car claim experience.

 Too much info
When it comes to car claims (indeed most types of claims), a common issue faced by insurers is a fundamentally human one: dealing with too much information. Given the strict and heavily regulated nature of insurance, claims documents are by design overloaded with disclaimers, explanations, definitions, and terminology. Even to the veteran eye, sifting through this mass of information is physically and mentally taxing, posing a significant time soak for classifiers and adjusters.

With self-learning algorithms, the processing roadblock posed by excessive information on official documents will be a thing of the past. AI rapidly detects and extracts this information on forms, and converts them to a structured format, easily digested and used by the insurance professional. AI can read virtually illegible handwriting with a better-than-human level of accuracy, and with a significantly quicker output rate.

Divide and conquer
Another common problem is that separate documents are submitted as a single file or claim document. Manually dividing such disparate elements as damage photos, identification documents, and repair invoices is a laborious affair for a human.  AI, however, can efficiently classify the different types of documents present within each claim, diverting them into relevant piles. It is also able to identify from an early stage which documents are missing from the claim filed.



Pattern recognition
By feeding the AI engine with data, patterns about specific customer behaviour can be identified – allowing for better fraud detection by flagging customers with a history of fraudulent car claims filed. By recording the circumstances and parameters surrounding a fraudulent claim, similarly executed future claims can then be marked as questionable and warranting further validation.

For example, patterns on equipment cost prices can be identified – allowing for quicker adjudication and appraisals, by cross-referencing this information with current market data and pricing trends. Eventually this means that insurers reach a point where there is ample historical data to rely on, especially within the damage evaluation process.


AI empowers claim handlers with greater efficiency and sufficient knowledge (of each claim case) by digitizing the necessary information – they can then evaluate claims with better accuracy and greater ease.

AI enables car insurers to digitalize processes by bypassing some of the tedious manual tasks currently necessary in adjudicating a claim. With AI reducing claim settlement times, customer satisfaction increases, ultimately leading to higher customer retention. Powerful AI propped up on vast data banks enable a hitherto unseen degree of responsiveness among today’s insurance providers.

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