Insurance companies that deal with property & casualty policies know the business relies on vast numbers of documents and images, whether for underwriting, servicing policies, processing claims, or claims adjudication and subrogation. At the same time, companies are pursuing digital transformation efforts, which means they need to find a way to automate document processing in property & casualty insurance.

It’s a tall order because many of the documents contain unstructured content, making them difficult to deal with for insurance workflow automation approaches that rely on keywords, rule-based methods and templates. What’s required is an intelligent document processing system (also known as hyperautomation) that uses artificial intelligence technologies to “read” unstructured documents much like a human does. Such a solution brings immediate value to all lines of property & casualty insurance, from auto and home to commercial, workers’ compensation, and more.

Download the Gartner Report: 2020 Market Guide for Text Analytics

Download Now

Property & Casualty Insurance Process Automation Key Benefits

image shows that indico's intelligent process automation can lead to a 4 times increase in process capacity

Capacity Expansion:

Grow property & casualty revenue without adding expense

image shows that Indico's intelligent process automation can lead to an 85% reduction in process cycle time

Cycle Time Improvements:

Get work done faster, from underwriting to claims processing

image shows that indico's intelligent process automation can lead to an 80% reduction in the amount of total resources required

Increase Efficiency:

Free up employee time for higher-value work

Knowledge Capture:

Codify and streamline property & casualty processes

Compete Effectively:

With stalwarts and insuretech startups alike

Customer Satisfaction:

Improve client response time

knowledge workers automating manual document-based workflows

Limitations of early P&C insurance automation attempts

For years P&C insurers have been trying to automate various processes, with limited success. That’s because these attempts often used rule- or template-based approaches that don’t work well with the unstructured content that dominates P&C insurance processes. 

Consider the P&C policy underwriting process. For a property insurance policy, underwriting involves collecting various documents that describe the property in question, so the underwriter can accurately assign a value to it and calculate replacement costs. 

Customers may submit various forms to aid in this value analysis, many of them in unstructured and sometimes complex formats, including PDFs and Word documents as well as photographs. Typically, a front-desk team would review these documents as they arrive, typically by email. The team would read each document, looking for relevant information that is then rekeyed into a downstream system that collects the data for the underwriter. 

The data entry job is labor-intensive, time-consuming and monotonous, making it prone to error. That’s why P&C insurers have been trying to automate it, initially by using rule- and template-based approaches that look for certain keywords. 

Such an approach is all but futile given all the unstructured content involved in the P&C underwriting process. Templates and rules work only on highly structured content; they rely on the data being in the same place from one document to the next. 

For years P&C insurers have been trying to automate various processes, with limited success. That’s because these attempts often used rule- or template-based approaches that don’t work well with the unstructured content that dominates P&C insurance processes. 

Consider the P&C policy underwriting process. For a property insurance policy, underwriting involves collecting various documents that describe the property in question, so the underwriter can accurately assign a value to it and calculate replacement costs. 

Customers may submit various forms to aid in this value analysis, many of them in unstructured and sometimes complex formats, including PDFs and Word documents as well as photographs. Typically, a front-desk team would review these documents as they arrive, typically by email. The team would read each document, looking for relevant information that is then rekeyed into a downstream system that collects the data for the underwriter. 

The data entry job is labor-intensive, time-consuming and monotonous, making it prone to error. That’s why P&C insurers have been trying to automate it, initially by using rule- and template-based approaches that look for certain keywords. 

Such an approach is all but futile given all the unstructured content involved in the P&C underwriting process. Templates and rules work only on highly structured content; they rely on the data being in the same place from one document to the next. 

Automate Your Most Complex Document-Based Workflows

What About OCR and RPA?

Optical character recognition (OCR) is another approach often touted as a P&C insurance process automation solution. OCR is a machine learning technology that can be used to convert documents such as PDFs into a machine-readable format. While that’s useful, it doesn’t address how to extract the relevant data.

Using robotic process automation (RPA) in insurance likewise suffers from limitations when it comes to unstructured content. As its name implies, RPA uses software robots to perform tasks that are highly structured and repetitive, involving the same keystrokes over and over.

But that’s not how the P&C underwriting process works. It requires a human to read documents and make judgements about which data to extract. Any other P&C insurance process that involves unstructured content, which is most of them, will suffer the same fate when it comes to OCR and RPA. (RPA can complement intelligent document processing in insurance automation, however. More on that below.)

Optical character recognition (OCR) is another approach often touted as a P&C insurance process automation solution. OCR is a machine learning technology that can be used to convert documents such as PDFs into a machine-readable format. While that’s useful, it doesn’t address how to extract the relevant data.

Using robotic process automation (RPA) in insurance likewise suffers from limitations when it comes to unstructured content. As its name implies, RPA uses software robots to perform tasks that are highly structured and repetitive, involving the same keystrokes over and over.

But that’s not how the P&C underwriting process works. It requires a human to read documents and make judgements about which data to extract. Any other P&C insurance process that involves unstructured content, which is most of them, will suffer the same fate when it comes to OCR and RPA. (RPA can complement intelligent document processing in insurance automation, however. More on that below.)

P&C Insurance Process Automation with IPA

Indico’s approach to intelligent document processing, Intelligent Process Automation (IPA), is fundamentally different from RPA and templated approaches because IPA can understand document context much like a human does. Our IPA platform is built on top of a database containing some 500 million labeled data points – enough to enable it to understand human language and context. It would take even the largest P&C insurance carrier years to accumulate that much data and build its own model.

Indico also applies AI technology known as transfer learning to enable users to create custom models that can automate virtually any P&C insurance process. It takes only about 200 documents in order to train a process automation model that delivers around 95% accuracy. Another key point: you don’t need data scientists to build AI process automation models. Rather, it’s the business people involved in each process who train the automation models – those who know the processes best. (For more on this point, check out our Intelligent Process Automation page.)

This approach to intelligent automation makes streamlining use cases such as auto claims, enrollment process and more a reality for any P&C insurer.

Indico’s approach to intelligent document processing, Intelligent Process Automation (IPA), is fundamentally different from RPA and templated approaches because IPA can understand document context much like a human does. Our IPA platform is built on top of a database containing some 500 million labeled data points – enough to enable it to understand human language and context. It would take even the largest P&C insurance carrier years to accumulate that much data and build its own model.

Indico also applies AI technology known as transfer learning to enable users to create custom models that can automate virtually any P&C insurance process. It takes only about 200 documents in order to train a process automation model that delivers around 95% accuracy. Another key point: you don’t need data scientists to build AI process automation models. Rather, it’s the business people involved in each process who train the automation models – those who know the processes best. (For more on this point, check out our Intelligent Process Automation page.)

This approach to intelligent automation makes streamlining use cases such as auto claims, enrollment process and more a reality for any P&C insurer.

Intelligent Process Automation in P&C Insurance Use Cases

IPA can be applied to a number of property & casualty insurance use cases, and in a variety of insurance categories, including:

  • Auto
  • Homeowner’s
  • Condominium
  • Renters
  • Landlords
  • Commercial property
  • Workers’ compensation
  • “Toys” including boats, motorcycles, snowmobiles, RVs, golf carts

Underwriting:

Automating the P&C insurance underwriting process requires dealing with numerous documents to be reviewed, with relevant data extracted and entered into a downstream processing system. An effective intelligent document processing tool can automate the process by “reading” these documents much like a human would to find the relevant data. It can also automate the process of data extraction and data entry, saving an untold number of hours that can then be dedicated to more valuable work.

Servicing P&C insurance policies

Numerous processes may be involved in servicing a P&C insurance policy over its lifetime, including:

  • Initial policy processing and printing
  • Processing any endorsements or riders to add, delete or otherwise change coverages
  • Audits to ensure P&C premiums are based on the correct level of potential exposure
  • Handling customer queries about their policies or claims

Many of these processes involve dealing with various forms of documentation, making them ripe for intelligent document processing.

First notice of loss (FNOL)

The claims process is rife with documents coming in from various stakeholders, including customers, adjusters, brokers, appraisers and more. The documents may arrive via email, fax, websites, or traditional mail. Here again, the traditional manual process calls for claims representatives to review the documents to find relevant data and enter it into the claims processing system.

The P&C claims process involves numerous steps including:

  • Accepting the initial claim (FNOL)
  • Validating the coverages in the insured’s policy
  • Assignment of an adjustor to validate the claim
  • Assignment of reserves to fund the claim
  • Disbursal of payment when the claim is settled

Many of these steps are transactional in nature, involving discrete steps and document reviews. An intelligent document processing tool can automate many of the steps in the P&C FNOL process including the document review process, extraction of key data points, and setting up the claim in the P&C company’s claims management tool. It can also validate that all required data is present before sending the claim to an adjuster. Simple claims may be automated end-to-end based on pre-defined business rules, perhaps with only a final review and sign-off required at the end of the process.

Claims adjudication and subrogation

The claim adjudication and subrogation process likewise consists of a number of steps that can be at least partially automated, including:

  • Claim validation, or the process through which the company decides that a claim is legitimate
  • Verifying proof of loss, through documentation, photos and interviews
  • Determining whether the firm can subrogate the claim and recover some losses
  • Investigating the claim to ensure it is not fraudulent
  • Legal review of the claim to ensure compliance

Applying intelligent processing to the numerous documents involved can streamline these processes and speed resolution of the claim, thus improving customer satisfaction.

How IPA Complements RPA

For some P&C insurance automation use cases it may make sense to use robotic process automation to complement IPA.

RPA works well on processes that are highly deterministic in nature and involve structured data. In that sense, it’s well-suited to automating repetitive tasks, making a process less labor-intensive for humans. IPA, on the other hand, is able to automate processes that involve unstructured data. 

A common IPA and RPA use case, then, is to use IPA to “read” unstructured content and translate it into a structured format before handling it off to an RPA tool. For example, the RPA tool may perform the initial document intake, then send the documents to an IPA tool for classification and data extraction. The IPA platform can then translate the extracted data into a structured format, such as a spreadsheet. The RPA tool can then take the now-structured data and automate the process of entering it into a downstream system, such as a claims processing system.

P&C Insurance Process Automation: Key Benefits

It’s challenging for P&C insurance companies to keep up with business requirements under the best of circumstances. But it’s imperative if firms are to achieve digital transformation. Indico’s intelligent document processing platform can help you take a big step in the digital transformation journey while delivering significant benefits, including:

Capacity Expansion:

Automation enables P&C adjusters, appraisers, examiners, investigators and other employees to be more productive, enabling the company to increase revenue without adding headcount.

Cycle time improvements:

Automating P&C insurance processes enables companies to get work done faster, even while increasing accuracy.

Increase efficiency:

By automating mundane tasks, you can free up employee time for more rewarding work that’s also more valuable for the company.

Knowledge capture:

Part of the value of a P&C insurance process automation exercise is codifying processes that may have existed for years with no formal agreement on how they are supposed to work. It’s also an opportunity to streamline processes to make them more effective.

Compete effectively:

Intelligent process automation ultimately makes your organization more competitive, putting you on equal footing with the most nimble insuretech startup and largest industry players alike

Customer Satisfaction:

Customer expectations are at an all-time high. Intelligent automation enables P&C insurers to exceed client demands by improving the speed and accuracy by which they are able to react to customer needs.