The vehicle insurance sector accounts for a substantial share of the global insurance industry. By 2027, the market value of the sector is expected to reach a staggering US$ 1,096.2 bn.
In recent years, auto insurers have stood witness as their industry has undergone a massive transformation.
Today, the insurance industry as a whole is seeing a steep rise in digitalization. Innovative insurance providers, such as Insurtechs and tech startups, have ushered in a new way of doing business that has revolutionized the industry.
To keep up, traditional insurers, including those in the vehicle sector, are pivoting towards adopting advanced technologies, such as Artificial Intelligence (AI) and Machine Learning (ML), to optimize their operational and claims management processes.
The abundance of data insurance companies store presents a massive opportunity to gain valuable insights into customers and offers a clear pathway to improve business operations. AI has quickly become the go-to tool to unlock this data.
How has AI impacted the car insurance industry?
In 2018, the global AI in the Auto Insurance market was valued at US$ 1.0 Bn. By 2027, it is expected to reach US$ 5.5 Bn with a CAGR growth rate of 20.5% forecasted between the period of 2019 to 2027.
As new technologies continue to emerge, the vehicle insurance industry is rapidly evolving. The claims management process is one area where insurance providers are seeing a lot of opportunities in utilizing AI to optimize operations.
Historically, vehicle claims management has been a labor-intensive process. With varying levels of experience, insurance handlers are tasked with making evaluations based on somewhat subjective parameters. Often this unstructured process has led to significant delays in claims resolutions, ultimately leading to reduced customer satisfaction.
What’s more, the way to evaluate suspicious and fraudulent claims has been a less than standardized process, which has led to significant monetary losses for insurers due to unwarranted claims payouts.
More specific issues that vehicle insurers face in the claims management process include:
- Lack of correct identification of all historically occurred fraud
- Occurred fraud not being registered as fraud in databases
- Abrupt changes in insurance companies’ defrauding methods – making the analysis of historical data less valuable for identifying future fraud
- Inconsistencies between different claim adjusters concerning identification of which claims are referred for further investigation
- The inability to assess potential suspicious relationships
- Lack of capacity to investigate every suspicious claim identified promptly
Today, AI is changing all of that.
Optimizing the claims management process with AI technology helps to enhance the standardization of claims management operations, helping to improve the rate of claims resolutions significantly. This means that customers have their claims processed within days, sometimes even minutes, not weeks or even months – a clear benefit for both the insurer and their clients.
AI also helps address issues of fraudulent claims, helping to efficiently identify and flag suspicious claims through a systematic process.
Through AI technology, insurers can be assured that they will get the most out of their money.
AI powered claims management technologies
Vehicle insurance providers are embracing various AI technologies to optimize their claims management processes.
Natural Language Processing (NLP) is one tool that is being readily adopted.
It is inevitable that when processing vehicle claims, insurance handlers become inundated with stacks of documentation to sift through. The often arduous, manual process of claims management becomes more taxing the more documentation is involved. This is where NLP comes into play.
NLP is a field of AI that gives machines the ability to read and derive meaning from human languages. NLP offers insurers the ability to efficiently analyze a large bulk of textual data and automatically extract and analyze all information, significantly reducing the workload for claims handlers and allowing them to spend more time evaluating suspicious claims.
This moves us onto Suspicious and Fraud detection AI technologies. Suspicious and Fraud detection systems identify suspicious patterns in claims, utilizing sophisticated algorithms to assign suspicious scores to claims. Handlers can quickly fast-track resolutions for unsuspicious claims through this system, giving them more time to investigate suspicious claims.
For vehicle damage appraisals you want to have an understanding of what are the variables that have led to that score. With AI, exaggerated damage assessments, such as overinflated repair costs, claims for an unexpected medical procedure after an accident, or an abnormally long time between a vehicle accident and claim application, are easily detected and outlined for evaluation.
Causality and Link Detection AI Systems allow insurers to understand the root cause of potential suspicions. This technology enables insurers to uncover hidden connections and network relational correlations between suspicious claims, leading to further reduction of errors before a claim is approved.
Vehicle insurers can further utilize AI technologies such as Claim Paid Amount Prediction to benchmark claims’ paid amounts and predict the appropriate claim amount to be paid to claimants.
The AI is a brain that is continuously learning. The more it is applied, the more it learns new processes and standards that will strengthen its accuracy in evaluations.
Getting the most value from AI
Implementing AI into claims management operations has become a business imperative for many vehicle insurance companies. The goal of any AI solution is to ensure that data is interpretable and that it draws valuable conclusions.
Not all AI models will provide value to an insurance company. What is essential for insurance companies is to work with data scientist experts that can understand their unique challenges and implement systems that will provide real monetary value.
umAI recently worked with a leading Israeli insurance provider to help it get the most out of AI technology to optimize its claims management processes. With umAI, the company utilized advanced AI to standardize claims management processes. It achieved a reduction in claims processing time by 54.4% and a 1.5% reduction in unnecessary and fraudulent payouts leading to $2.1M in annual savings. To find out more about how the insurer achieved these results, read more in our case study.
AI is transforming the vehicle insurance industry in many ways. To optimize claims management processes, vehicle insurers must look to the latest technologies to advance their competitive advantage.
To learn more about implementing AI into your claims management process, get in touch with us today.