How Does Artificial Intelligence Accelerate Claims Processing In Insurance?

Claims Processing

All parties involved find it challenging in the moments following a vehicle accident. The drivers need to process the trauma, take care of any injuries with medical attention, share information, and figure out how to get their damaged cars fixed or replaced. The most effective and affordable way to resolve the claims must be determined by insurance companies after conducting damage assessments.

How artificial intelligence accelerates claims processing In Insurance? Claims processing is one of the most important insurance operations. 87% of customers say that the effectiveness of claims processing influences their decision to choose a vendor.

In this article, we outline the different types of AI models that can be applied to various claims-processing tasks to assist executives in making investment decisions.

What Is The Role Of AI In The Insurance Industry?

In 2017, artificial intelligence (AI) demonstrated its value in a number of business sectors by quickly building automated, controlled environments that maximize productivity.

Insurance companies, in particular, seem to stand to gain significantly from investing in AI-enabled technology that can not only automate the scheduling of executive-level tasks but also improve service quality by assisting agents in making accurate decisions and unfalsifiable judgments.

Related Reading: Uses Of Artificial Intelligence In The Insurance Industry

AI-enabled Innovations And Solutions

Insurance companies now face 3 major challenges:

  • Reaching out to prospective customers at the right time
  • Providing the right set of products that suit customer requirements
  • Fastest claim support to loyal customers and rejection of spurious claims

A technologically advanced system that helps keep all of their employees in sync is what insurance companies are aiming for. These staff members range from agents, brokers, and claim investigators, to market and support staff. The insurance ecosystem is further complicated by this group of employees and redundant procedures.

How Does Artificial Intelligence Accelerate Claims Processing In Insurance?

1. Automate Data Capturing And Fnol With Nlp

NLP, a subset of AI, recognizes text data and extracts meaning from it. Because NLP deals with written texts and language, it enables automated claims processing for insurance companies. The use of chatbots and optical character recognition (OCR), two of the main NLP applications, specifically enhances the processing of insurance claims.

  • OCR: The technology that can read handwritten text and numbers is based on artificial intelligence. As a result of regulations, insurers frequently use printed documents and paper-based forms. OCR thus becomes a crucial tool for raising operational effectiveness. Insurers can gain from OCR-driven models to automate data capturing from paper-based documents rather than typing information by hand.
  • Chatbots: Chatbots can expedite the reporting of damage. Customer wait times for the first notice of loss (FNOL) in the past were lengthy. However, today’s NLP-powered chatbots can direct users to take pictures and videos of the damage, which can then be instantly translated into a description of the damage.

2. Speed Up Claims Adjustment With Computer Vision

The process by which AI models can extract meaning from visual inputs like images and videos is known as computer vision. By analyzing geospatial data (GIS) gathered from satellites, as well as videos or images taken by customers or drones, computer vision models assist claims adjusters. To assess damage to cars, factories, homes, disasters, etc. immediately, insurance companies, for instance, use drones outfitted with computer vision technology.

Claims Processing

3. Detect Fraud With Advanced Analytics

Fraud detection and prevention are effective uses of advanced analytics. According to the FBI, fraudulent claims cost the US economy more than $40 billion every year. alone. It puts a strain on insurers, causing them to increase premium costs.

The relevance of claims has traditionally been manually examined by insurers to ascertain whether or not they are fraudulent. This process has been time-consuming and ineffective. For instance, according to McKinsey, of every 10 health insurance claims that are submitted, insurers may classify up to 7 of them as unusual, which means they could be false or fraudulent based on company policy. Re-examining 70% of claims is an irrational suspicion rate that demonstrates that people are ineffective fraud detectors.

Insurance companies can more effectively lower the cost of fraud by combining monitored and unsupervised ML models with behavioral analytics.

Read our articles on IoT insurance, blockchain insurance, low-code insurance, and digital twins in insurance to find out more about current insurance trends.

To deploy your AI/ML models more effectively, your company might find it helpful to look through our lists of AI platforms, AI developments, and AI consultants.

AI Ramps Up

According to John Goodson, chief technology officer at CCC Intelligent Solutions, a provider of technology solutions for the automotive and insurance industries, these elements taken together make for a particularly compelling case for implementing artificial intelligence in claims processing. (As a standalone entity, CCC is not an insurer.)

AI is increasingly being used to process insurance claims. In 2021, CCC reported a 50% increase year over year in the use of advanced AI for processing claims. The business claims that more than 9 million distinct claims have been routed through its deep learning AI solution; this number increased by more than 80% in 2021.

Ai In The Insurance Industry Today

74% of customers currently say they would like to interact with modern technology and value the computer-generated system of insurance advice, according to a survey by Accenture.

Businesses that automated some of their claims processing procedures early on saw significant reductions in processing costs and processing times, as well as an improvement in service quality. Talking about early adopters, Allstate Business Insurance has also recently developed ABIe in partnership with EIS. ABIe, also known as Abbie, is a virtual assistant program powered by artificial intelligence (AI) that was created to assist Allstate insurance agents in seeking details on ABI’s business insurance offerings. We can only hope that as time goes on, we will hear about more insurance companies implementing AI.

Insurers can reach potential customers, research their in-the-moment needs, gain insight into the risk magnitude of their profile, and ultimately develop custom solutions thanks to the potent combination of machine learning, advanced analytics, and IoT sensors.

Future Of AI In The Insurance Industry

In spite of difficulties that seem to depress the current market, insurers continue to be optimistic about AI’s potential in the insurance sector. Insurance companies must develop an enterprise-level strategy to implement AI so that it provides more than just improved customer experience in order to fully benefit from it.

In the insurance sector, businesses are already developing a variety of AI applications, including automated self-service guidance, damage analysis through image recognition, and claims management.

When it comes to image recognition, bots that comb through images and videos would handle the overall damage analysis, cost estimation, and claim settlement. In this way, businesses can eventually fully rely on image recognition technology for first-level claim automation, leading to the automatic settlement of claims or resolution of insurance fraud detection.

Insurance companies can strive to reduce the time and resources spent managing or monitoring claims by working on smart automation of existing workflows, improving process efficiency, and improving customer experience.

Ada Parker