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AI's Impact on Insurance Document Processing
Aditya Kathpalia
Aditya Kathpalia Posted on Mar 22, 2024   |  4 Min Read

As the insurance industry is becoming more and more digital-first, managing huge volumes of unstructured datasets across diverse documents poses significant operational challenges for insurers. Insurers have to work with an assortment of different documents such as handwritten notes, loss adjustment reports, statements of values (SOVs), policy documents, endorsements, claims images, regulatory filings, etc. This data is stored in an array of formats, ranging from PDFs to Word files, and image formats, further intensifying the complexity.

Challenges in Insurance Document Processing

To navigate these challenges, many insurers are transitioning from manual document processing to injecting AI to power automated document processing. As such, insurers can leverage intelligent document processing solutions to transform how they handle and extract insights from voluminous data repositories.

Challenges in Manual Insurance Document Processing

Here are some common challenges associated with manual document processing in the insurance industry:

I. Time-Consuming Document Handling

Insurance professionals, such as underwriters, handle documents manually, scouring inboxes or shared drives to compile relevant data. They have to manually check the accuracy, reconcile data between forms, and feed data into insurance administration software solutions. This not only impacts productivity but also increases the probability of errors.

II. Impact on Process Agility

In the insurance industry, businesses gain a competitive edge through agility. However, manual document processing impedes agility. In a competitive landscape where swift responses are crucial, manual document processing impedes agility. Agents, brokers, and underwriters typically spend a chunk of their work hours validating and compiling information, detracting them from the core focus on building relationships and responding swiftly to customers’ needs.

III. Inefficient Fraud Detection

Manual insurance data processing makes it challenging to detect fraud quickly and proactively. Every year, the insurance industry loses to the tune of $40 billion in insurance fraud. This figure alone underscores the importance of AI-driven insurance document processing.

How Does AI Help with Insurance Document Processing?

The use of AI in insurance can power intelligent document processing solutions with the following capabilities:

1. Powering Automated Data Extraction

AI algorithms can automatically extract data from a variety of document types, be it policy documents, loss adjustment reports, endorsements, claims images, and more. Extracting meaningful and relevant data from such sources reduces the reliance on manual data entry while improving data accuracy and minimizing errors.

2. Document Organization and Management

It is no secret that the insurance industry involves the use of several documents across functions. With Document Processing with Insurance AI, it is possible to sort, organize, and categorize documents for quicker storage and access. Whether it is customer support teams or claims adjustment teams, anyone can quickly find the relevant document in minimal time.

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3. Accelerated Processing Times

AI-powered insurance document processing solutions accelerate processing times in several ways. For one, the relevant data is already extracted and mapped against the appropriate fields and stored digitally. Second, the documents required are easily available in just a few clicks. Third, these integrate with other digital solutions to perform complex computations automatically. As a result, this end-to-end process automation reduces the time required to enter or validate data or hunt documents. It supercharges operational efficiency and frees up manual resources for more nuanced operations such as relationship-building or handling escalations.

4. Fraud Detection and Prevention

AI algorithms are highly efficient at detecting patterns or anomalies. This ability equips AI-powered document processing solutions with the ability to analyze data and document content to detect fraudulent patterns or extraordinary behavior in claims function. Such proactive fraud detection and prevention activities protect the interests of insurance policyholders and insurers by optimizing insurance costs.

5. Richer Customer Experience

AI document processing for claims minimizes claims processing timelines while maintaining transparency and accuracy. Intelligent document processing solutions make information readily accessible to customer support teams to assist customers better. Underwriters can use AI in insurance to make accurate risk predictions and personalize policies. With such value-addition at every touchpoint, insurers can deliver a positive customer while transacting with the insurer.

6. Data-Driven Insights and Analytics

Intelligent document processing solutions operate on a data-driven framework that allows them to extract and work with data available in insurance documents. With the data available insurance management platforms can identify trends, assess risks, and make well-rounded, informed decisions backed by solid data. Such a transition marks the departure from cumbersome paperwork to strategic data-led insights.

7. Scalable Document Processing Operations

AI-powered document processing solutions are highly agile and scalable. They have the ability to handle high volumes of data and continue extracting insights from it without compromising on speed, efficiency, and accuracy. Such scalability is instrumental for insurers when dealing with natural calamities or during seasons where the number of claims peaks due to various reasons. As a result, businesses can maintain a high degree of agility without relying on manual or limited resources that can quickly turn costly.

Conclusion

Insurance document processing is a loaded and strenuous task. However, with the advent of AI-powered document processing, harnessing the power of the data contained in the documents becomes possible in just a few clicks. The use of AI in insurance claims, underwriting, customer support, and other activities is bound to take the business to stellar heights.

Case in Focus

A leading independent insurance adjusting firm, renowned for offering exceptional claim services, faced challenges with inaccurate property claims estimation reports due to human errors and incorrect data. The reports lacked accuracy, leading to multiple quality checks before submission to insurance carriers. Using advanced tools and technologies like OCR, ML, Pytorch, and Fast AI, we implemented an advanced neural network AI model. The integrated solution revealed mistakes in loss estimates, matched roof materials, and provided accurate suggestions, resulting in an error-free claims process. As a result, the insurer was able to eliminate human errors, streamline claims processes and accelerate time to market through agile development methodology. For more details, refer to the detailed case study.

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