Intelligent Document Processing for Insurance

Tackling Digital Transformation in Business Processes

Processing claims document is an intricate process. It requires a whole infrastructure around staffing, training, capacity forecasting, and business rules set to a manual process, as well as IT systems that support the processing.

Until now, it’s been tough to automate because of the complexity of the documents. After all, it takes human-like cognition to sort through all of the details. And with increased digitization in the insurance industry, demand for automation is soaring. Market pressures are spurring transformation and demand for scale, but it’s not so simple. Or hasn’t been, so far.

Intelligent Document Processing (IDP) is a next-generation solution for extracting data from complex, unstructured documents, such as the forms required for an insurance claim. When documents have a complex structure and/or are unstructured, they most often require manual processing. Documents with these characteristics cannot be meaningfully processed by an OCR.

As an illustration of how IDP works for insurance processes, let’s first examine the insurance claims process today. Other insurance processes will follow a similar design.

Let’s break down our example

The Existing OCR and Manual Claims Process

The diagram above illustrates the current state of claims processing at many firms. The process is costly, slow, and will not scale well to match demand fluctuations.

1. Input. First, claims processing takes in unstructured documents and claims forms at the front end of the process (some documents are well-structured and do not present an extraction problem).

2. OCR extraction. These forms are run through a scanner or OCR to extract the needed information.

3. Because these forms are complex, unstructured documents, the OCR is capable of extracting data from only 10-15% of the documents.

4. The remaining 85-90% of the documents that failed OCR extraction are sent to a workstream for manual processing.

5. The extracted data is sent to the claims transaction processing system and onward.

Since this is the legacy way to process claim documents, a business infrastructure has been built to make the process flow smoothly. But it’s not enough to handle today’s digitization and document needs.

Unstructured Insurance Documents Create Roadblocks to Automation

The processes using complex, unstructured data are problematic because they are extremely difficult to automate. Extracting and making sense of the data received in documents from customers has traditionally been a human-intensive effort.

This creates a manual process bottleneck:

1. Fully digitized back-office processes are needed

2. Processes using unstructured, complex documents are a transformation roadblock

3. The complexity of these documents has required a manual processing step which blocks efforts to automate

Infrrd’s IDP solution, however, can process insurance documents that are complex and unstructured.

Here’s what a more automated and efficient claims process looks like

Now 80-85% (or more) of the documents are automated. The remaining are sent to a manual correction workflow where only anomalies are presented to the staff, not the entire set of extraction tasks.

The result is a better, smarter claims process that is innovative and competitive.

1. With this solution: The complex claims processing time is reduced from days to hours.

2. The process provides a better CX with faster response time and reduced rework.

3. The manual workload is significantly reduced, allowing staff to be repurposed.

4. System management is reduced, since there is no OCR template management.

5. The solution eliminates legacy systems that were needed to support the manual effort.

Infrrd’s IDP Solution for Insurance

Infrrd’s (IDP) automates the extraction of data from structured and unstructured documents, eliminating the need for manually gathering, entering, and validating data. Unlike the technologies that came before it, IDP can handle document complexity and variation using multiple AI technologies and machine learning. Insurance firms are deploying IDP to increase process automation, which is otherwise hindered by manual data entry bottlenecks and OCR limitations.

Infrrd’s IDP solutions also integrate with the insurer’s legacy, backend, and digital applications reducing the cost of integration, enhancements, and changes required in existing systems.

Insurance Document Types

Infrrd’s IDP platform can process a broad set of insurance document types that are complex and unstructured. Example insurance document types are listed below.

P&C Workflow Documents - claim form, police report, accident scene and vehicle damage pictures, vehicle operator driver's license, insurance copy, bills, invoices, receipts, etc.

Life Insurance Workflow Documents - claimant completed form, death certificate, obituary, original contract, HIPPA authorization, etc.

When New Document Types Enter the Process - Infrrd’s solution can not only the documents listed about but it can handle new documents and documents it has never seen before. This is accomplished using machine learning and other adaptive technologies.

Improve Process KPIs and SLAs

The impact of removing these bottlenecks can have an outsized impact on business operations. By automating data extraction from complex documents, Infrrd allows you to transform the end-to-end insurance process.

Infrrd can improve KPIs and SLAs performance for these insurance process metrics:

Cost - Automation significantly reduces the manual input need to run a process smoothly. OpEx costs can be reduced.

Processing Time - Automation can process 8x faster than humans.

Rework - Less rework is needed with better-than-human accuracy and predictive analytics provided by IDP.

CX - IDP helps create a better customer experience as the process is faster, requires less effort, and is more predictable.

Scalability - The automated process allows you to add or decrease capability on-demand, without adding headcount.

Process Efficiencies - IDP can improve process efficiency by improving agility, speed, cost, time, manual effort.

Intelligent Document Processing For Insurance

Tackling Digital Transformation in Business Processes

Let’s break down our example

The Existing OCR and Manual Claims Process

The diagram above illustrates the current state of claims processing at many firms. The process is costly, slow, and will not scale well to match demand fluctuations.

1. Input. First, claims processing takes in unstructured documents and claims forms at the front end of the process (some documents are well-structured and do not present an extraction problem).

2. OCR extraction. These forms are run through a scanner or OCR to extract the needed information.

3. Because these forms are complex, unstructured documents, the OCR is capable of extracting data from only 10-15% of the documents.

4. The remaining 85-90% of the documents that failed OCR extraction are sent to a workstream for manual processing.

5. The extracted data is sent to the claims transaction processing system and onward.

Since this is the legacy way to process claim documents, a business infrastructure has been built to make the process flow smoothly. But it’s not enough to handle today’s digitization and document needs.

Unstructured Insurance Documents Create Roadblocks to Automation

Explore Use Cases

Infrrd’s IDP solution, however, can process insurance documents that are complex and unstructured

Complex insurance documents have one or more of these characteristics

Unstructured insurance documents have one or more of these characteristics

Automate Data Extraction From Unstructured, Complex Insurance Documents

Here’s what a more automated and efficient claims process looks like

Infrrd’s IDP Solution for Insurance

Insurance Industry Segments Serviced by Infrrd

Insurance Document Types

Solutions for Insurance Back-Office Processes

Improve Process KPIs and SLAs

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