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Top 6 Technologies That Improve Claims Adjustment in 2024

Cem Dilmegani
Updated on Jan 10
4 min read

When policyholders notify insurers of a loss, insurers are aware that they will soon have to make payments to their customers to meet their legal obligations. These are referred to as “reported but unsettled claims.” Insurance firms set up statutory reserves (compliance obligations) and additional claims reserves to meet their liabilities and protect themselves from insolvency.

However, in order to calculate the amount of claims reserves, insurers must have as much information as possible about the cost of claimants’ damages. Insurance firms employ claims adjusters to forecast liabilities. Nowadays, firms can support claims adjusters with  technological tools to improve the speed and accuracy of initial claim inquiry. This article will discuss 6 technologies that insurers can use to better manage their risks via ensuring an effective claims adjustment process.

What is claim adjustment?  

Claim adjustment (also referred as loss adjustment) is the initial evaluation of damage with the goal of predicting an insurance company’s liability. It is the second phase of claims processing, which begins following the submission of the first notice of loss (FNOL). Typically, claims adjusters:

  • Evaluate the damage.
  • Interview with witnesses or claimants.
  • Investigates police or medical reports.
  • Evaluate the insurance policy.

By considering those, claims adjusters predict:

  1. Whether the policy of the insured covers the particular claim of the customer. 
  2. If the claim is covered by the policy, adjusters estimate the cost and report it to the insurance company for the preparation of the payment.

Claims adjustment can be enhanced thanks to technological advancements. The following sections will introduce such opportunities.

1. Video chat

Video chat platforms allow obtaining data in real time. The insured can provide detailed visual information regarding damage and location of incident thanks to such platforms. As a result, the claims adjuster can have an initial prediction about the liability. 

Video chat capabilities also reduce potential insurance fraud. Obtaining real-time data is crucial for insurers because fraudsters might inflate claims by manipulating data. Fraudsters have less time to alter the truth with an instant video connection. 

Another advantage of video chat capabilities during claims processing is that it improves customer retention. According to EY, the speed and quality of claims processing influence nearly 90% of clients’ decisions to switch insurance providers. Video chat capabilities offer the convenient and automated claims processing many customers demand.    

2. Advanced analytics

By utilizing historical data, advanced analytics can forecast the cost of a loss. Consider a category 4 hurricane that will hit a specific area. If level 4 hurricanes regularly strike this area, insurers can use advanced analytics to assess possible damage and short-term obligations.

3. Custom mobile apps

Custom mobile apps are effective tools for speeding up whole claims processing including claims adjustment phase due to following reasons:

  • Both insureds and insurers can upload data about the details of the damage and instantaneously share with many experts which is more convenient for both insurance companies and the customers. 
  • Customers can fastly submit the FNOL and questionnaire form by using apps. 
  • Customers can check the status of their claims via using such devices. 

According to KPMG, fully digital claims processing is a priority for more than 20% of business insurance customers, while they sign for insurance coverage. When we consider the general demand for digital services in financial sectors, we expect that mobile apps will be a reason for a competitive advantage for insurance companies.

Insurance businesses can build/outsource their own specialized mobile apps to better serve their clients and improve essential insurance functions such as claims adjustment and processing. Collaboration with general solution suppliers is also feasible. Nest Forms, for example, offers form filling and data collection services for a variety of industries, including insurance.

If you need more information regarding claims processing strategy you can read our Claims Processing Transformation: Trends, Tech & Strategy article

4. Computer vision

Computer vision models can assist claims adjusters for estimating the cost of the claims and determining frauds. Such models can use videos and images that are uploaded via FNOL for the assessment.

Also, such models can work 24/7 despite the claims adjusters. Thus, for insurance companies deploying computer vision models can be beneficial in the long run.

5. Optical character recognition/ handwriting recognition

Applications of  NLP such as optical character recognition (OCR), handwriting recognition (HWR), and intelligent document processing (IDP) automate the extraction of unstructured data from printed and handwritten documents for claims adjusters. 

When it comes to underwriting, claims processing, and fraud investigations, the insurance sector deals with a lot of printed and handwritten papers. Data extraction that is not automated results in inefficiencies owing to time spent on repetitive procedures. For example, according to an Accenture research, underwriters spend more than half of their time inputting and extracting data from papers.

Claims adjusters, like underwriters, cope with a variety of written documentation. A claim adjuster, for example, should review official reports, questionnaire forms, and the policy’s conditions before deciding a claim. This process can be automated using OCR and HWR technology.

6. IoT

We are surrounded with smart devices such as smartphones, watches, homes, cars, factories etc. IoT devices provide data for insurers which is beneficial for their many practices including claims adjustment. 

The use of IoT devices increases the likelihood of fraud detection. Claims adjusters can better evaluate whether an incident is covered by policy or not thanks to the IoT because they have better access to data. Consider a car insurance case to see which new data sources claims adjusters have access to.

  • Exact time and location of accident: In the days before smart automobiles, claims adjusters couldn’t be certain of the specific location and timing of an accident. When a car’s airbags inflate, insurance companies are now immediately notified of the specifics of the accident. As a result, fraudsters are limited in their ability to bend the truth in order to inflate damage.
  • Whether or not drivers obey the rules before the accident: Before the IoT, the main source for determining whether or not drivers followed the laws before an accident was driver and witness claims (if any). Claims adjusters may now obtain this information with confidence and quickly identify drivers who break the law.

It is also worth noting that in some circumstances, using drones to gather data regarding claims might be advantageous to insurance firms. For instance, following a disaster such as a hurricane, IoT devices like drones could be used to assess insureds’ losses in the disaster area.

You can check our sortable/filterable list of top insurance suites where you can find platforms that improve your underwriting, claims processing or fraud detection capabilities.

If you need further information regarding claims adjustment and the insurance sector in general we can help:

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Access Cem's 2 decades of B2B tech experience as a tech consultant, enterprise leader, startup entrepreneur & industry analyst. Leverage insights informing top Fortune 500 every month.
Cem Dilmegani
Principal Analyst
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Cem Dilmegani
Principal Analyst

Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.

Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

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