January 9, 2023

Elevating Insurance Customer Experiences with Intelligent Document Processing

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Elevating Insurance Customer Experiences with Intelligent Document Processing

This blog depicts how to engage insurance customers more meaningfully and drive retention through Intelligent Document Processing (IDP).

Everyone wins when insurance companies can deliver richer, more efficient customer experiences. Clients get the support they need when they need it most, and insurance companies can gain market share through more efficient workflows and more vital brand relevance. Intelligent Document Processing (IDP) is one compelling way businesses can engage customers more meaningfully.

What makes IDP indispensable in this industry is that leaders are often bogged down with vast volumes of documents and information locked away in inaccessible formats. To make strategic business decisions and improve customer-facing processes, they need reliable access to this unstructured data. Manual attempts at finding and utilizing data are laborious and expensive. 

AI-Driven IDP is a cost-effective, scalable way to capture data from multiple sources and transform it, so a person or team has the clout to elevate customer experiences.

Between the rise in natural disasters and COVID-19, insurers certainly have their work cut out for them. Furthermore, several savvy digital-born companies have surfaced, leaving traditional insurance entities struggling to retain customers and gain new ones.

 The future of insurance is digital, but customer experience remains a battleground worth fighting for.

 Read on to learn how IDP powered by a robust Document Transformation Platform will enable insurers to become fast, agile, and responsive to deliver winning customer experiences.

Unstructured Data is a Burden

Insurance companies manage vast volumes of customer data, including onboarding documents, policy claims, and billing correspondences. However, with 80 percent of these documents and information locked away in Unstructured Data, residing in disparate systems, alchemizing it into a more robust customer experience is an undertaking.

To make things even more challenging, COVID-19 has accelerated the need to free up and leverage unstructured data to remain agile and to compete with nimble digital-only carriers.

What Role Does IDP Play in Customer Satisfaction?

Typically, there is a sense of urgency when insurers hear from customers. Understandably, clients expect immediate responses to their requests for support when things have gone wrong. If insurance carriers struggle to gather the necessary information to process claims promptly, they jeopardize accuracy and loyalty. 

Health insurance companies are averaging a 19.3% error rate, up 2% from the previous year. The AMA estimates this increase in inaccurate claim payments will cost the healthcare industry an additional $1.5 billion in needless administrative expenses this year alone.
- AMA’s Health Insurer Report Card 

With IDP, insurers have the tools at their fingertips to automatically process a high volume of documents, dramatically reducing the amount of time it takes to complete a claim and issues a payment.  

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Use Of Document Automation in Insurance Claims Processing

1. Processing documents from variety of file formats
Insurance companies often must process a wide variety of documents of different file types (almost 200 different file formats). This can include image files that need to be digitized, complex email attachments that require specialized processing, CAD drawings that require specialized knowledge, and documents stored in zip files as well as email attachments. First step is to standardize all documents from various file formats by converting it into a unified PDF format.

2. Digitize text from images / fax documents
It’s very common for customers to take a picture of various documents and send it for processing. Insurance companies have to OCR (Optical character recognition) these documents and extract text and numbers from these documents. Many times the quality of the image may not be great and could be skewed. This is where the sophistication of the OCR engines in detecting these inconsistencies and still do a good job to extract the relevant text and numbers from the image.

This not only includes extracting text but also includes extracting costs from invoices with the right context as shown in the example below.

4. Identify what document category this document belongs to
Document classification can help automate and streamline the claims processing process by quickly and accurately identifying the type of documents that are involved in a particular claim, and routing those documents to the appropriate claims processing workflow for further processing.

Document classification is a type of machine learning algorithm that is often used in claims processing to help automatically classify different types of documents that are involved in the claims process. Here are the common examples for document classification in claims processing / automation include:
   - Categorizing distinct forms of property damage documentation, like repair quotes, invoices, and pictures, to facilitate the accurate evaluation of property damage compensation that is to be disbursed.
   - Organizing various types of property damage records, including repair estimates, receipts, and photographs, to accurately determine the necessary level of property damage benefits.
   - Classifying different types of life insurance documents, such as death certificates, beneficiary documents, and insurance policies, to help determine the appropriate level of life insurance benefits that should be provided.
   - Classifying various insurance benefits documents, including those related to disability, unemployment, and accident benefits, to assess the appropriate amount of benefits to be allocated.

5. Extract context specific information from these documents
All the data needed to process a claim are typically scattered inside various documents received so far. For the insurer to process this data, it is important to extract key information from various documents and copy that evidence over to the insurance system to streamline the decision making.

This is where AI can be trained to look for the kind of information based on the claim context and extract that information and copy it over into a meaningful format for further downstream processing.

The following picture is an example of a roof claim that is processed and cataloged for further processing. Some of the information needed for the claims processing are automatically extracted from one or more documents and copied over to a centralized system to further reference downstream.

6. Identifying Missing / Duplicate documents
Insurance companies must ensure that all documents are accurate and up-to-date to ensure compliance with regulations. AI can identify which documents are missing, which are duplicates, and which may be potentially fraudulent.

Additionally, any outliers should be identified and flagged for further review. If any suspicious activity is suspected, the documents in question should be sent to a specialized unit for further investigation. AI can help insurance companies to maintain a comprehensive document review process and actively monitor documents to ensure accuracy and compliance.

Similarly, when securing new business, IDP enables carriers to streamline the customer onboarding experience. IDP improves efficiencies by reducing the volume of human error and efforts spent fixing mistakes, which positively affect retaining existing clients and attracting new ones.


A Field of Obstacles 

There are three unique obstacles challenging insurance companies like no other time in history. First, 2020 experienced over two and a half times more wildfires, floods, and other natural disasters than previous years, amounting to billions of dollars paid out in insurance claims. Second, during the same period, COVID-19 struck, and the industry experienced a massive influx of pandemic-related claims. Everyone was caught off guard, and even the savviest companies struggled to navigate these unchartered waters.

The final hurdle facing traditional insurance companies is the rapid growth of digital-born carriers. For instance, Lemonade is a start-up offering homeowner, renters, and pet insurance. The company operates on a fully AI-powered platform and can process claims in seconds. Older insurers must leverage technology to bring an elevated level of value to customers or risk becoming obsolete.

Document Transformation Fuels Intelligent Document Processing (IDP)

The intelligent insurance enterprise of the future needs to think beyond document management to solutions that bring significantly higher value to the customer experience. Document Transformation, an opportunity to augment agility and growth, is the next evolution of IDP. 

Insurance Leaders in the Real World 

By automating their high-volume claims filing processes with IDP, insurers can free up their inspectors to resolve exceptions and accomplish higher-value tasks that lead to happier customers.

Only 15% of business leaders surveyed consider themselves very effective in delivering relevant and reliable customer experiences.
Harvard Business Review


The Final Verdict

Many insurance leaders are overly involved with daily processes to see the forest for the trees; they cannot see the efficiencies that IDP can deliver. Ultimately, a robust solution will provide insight into a customer from end to end. When companies have immediate access to relevant client data, they can consistently and reliably serve them well and stand out in a highly competitive environment.

Adlib's upcoming IDP platform will empower insurers to deal head-on with their unstructured data to meet customer expectations with confidence and agility. After all, nothing bolsters brand loyalty like being there when your customers need you most.

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