All Publications

Insurance Document Processing and the Opportunities in AI

insurance document processing and opportunities in AI

Customer acquisition and retention are the essential drivers of insurance revenue and profit.  Today’s insurers face a new breed of competitor who targets customer experience with smart technologies, such as AI, focused on removing friction from their interactions. As FinTechs have done in consumer banking, new InsureTechs transform customer experience through smart mobile apps, integrating the phone’s camera as an input channel, and collecting data to target personalized offerings.  Competing digitally means targeting AI and smarter technology at removing friction both from customer experience and the processing that directly supports it.  

We have already seen the adoption of Robotic Process Automation (RPA) in this industry, adopted mainly to automate repetitive, back office supporting processes.  As RPA has reached wider adoption, insurers now are realizing that the bigger opportunity for this technology is to use bots at the front line of customer engagement, where intelligent understanding and responding to customer needs pays off exponentially in revenue and profit.  Targeting bots directly at removing friction from engagement may soon eclipse the back office as the focus of AI investment.

It’s About Documents

No matter what technologies are used, insurers interact with their customers through the exchange of documents, messages and unstructured content.  As customer engagement gets more attention for AI and automation, the handling of documents in those processes remains an afterthought, pushed to the end of the process where users open documents from email and key data into their systems of engagement.  Transforming documents in real-time into process-ready data is critical to ensuring the right level of automation and decisions are available to the customer-facing process.  

Document handling needs to be at the front of automation, at the point of the customer touch, but this fact is so often overlooked because this process is not fully discovered, understood and mapped as a function of customer engagement. While both OCR and RPA can provide automation within these processes, they are often deployed incrementally in projects to optimize existing processes and not with an eye to the customer engagement process as a whole.    

One would think that the biggest friction points in all these customer experience journeys – from onboarding and underwriting through claims adjudication, upselling and compliance – had been addressed ages ago, but they really have not.  Now that scanning and service bureaus have been replaced by mobile cameras, email and other digital channels, it carries with it the impression that these functions have been digitized.  The basic problems of inputting content from these documents into customer processes, however much the input channels have been digitized, remains largely unaddressed, or handled in the same way that manual paper-based processes handled them.  

Changing the input channel and back office scanning solutions never solved the problem of document handling in front-line customer service experiences because insurers have not examined these capabilities as part of a process.  Insurance documents themselves also pose problems for automation.  These documents are complex, highly variable and often come in high volumes.  Notification of loss, reports, estimates, invoices and supporting documents are full of free-form text, nested tables, and variable information in unpredictable forms from variable sources, presenting a formidable processing challenge when handled individually, but becoming exponentially worse in any kind of volume.  Here, understanding the context, customer need and complexities of the documents themselves and addressing these issues as they occur are a significant opportunity for AI. 

The Challenge: Document Processes versus Processing

Two fundamental problems with document-handling still need to be understood clearly in order to automate the customer experiences around them.  These are process and processing – two distinct functions that often are assumed to be the same thing.  Process – the flow of events and actions - is where customer experience and engagement live, and automating these processes of engagement is the key to speed, quality and satisfaction.  Customer engagement is a process during which information – often from documents – must be located and verified directly from the points of engagement at which documents are received.  

Processing is how documents are located, prepared, identified, classified, and then read for data extraction, validation and release into the processes, systems and stakeholders for decision-making.  While insurers have largely digitized document input via smartphones and PDF attached to email, the actual processing of their content occurs at the end of the process, instead of the point of engagement.  As a result, insurers are losing the ‘now moment’ with customers by deferring the processing of the most valuable content their customers provide – claims, supporting documents, statements, reports, invoices – to the end of the process.  This branch process, rather than fully integrated document processing, causes additional friction, delay and frustration for customers, with less good data available in the now for next steps in decision-making and follow-up.    

Artificial Intelligence (AI), carefully deployed throughout document processing, can address these challenges, but all too often it is over-simplified as plug-n-play automation – OCR projects, for example – or, worse yet, focused only on one piece of the process, rather than its whole.  Transforming characters in a document into data is extremely critical, but understanding the context, relationships, entities and intent of the extracted data is what drives the actual benefits of automation.  AI has made major advancements in all of these areas – particularly for discovering and understanding the context required for entities, intent and role of the documents in the customer’s journey.  The opportunity for AI is in targeting the end-to-end processing of documents – not just the recognition of text step function – as an essential part of the customer journey. 

To better understand how to intensify Return on Experience (ROX) through deeper customer satisfaction, download our eBook: Accelerating Digital Agility in Insurance.

Customer Experience Digital Transformation Artificial Intelligence (AI) Mobile OCR Robotic Process Automation (RPA) Insurance Intelligent Capture
Reginald J. Twigg

Ph.D., Director Product Marketing at ABBYY

With a research background in Communication Theory, including Semiotics, Linguistics, and Speech Pathology, Reginald Twigg has been in Enterprise Software for the past two decades focusing on automating document processing applications (specifically, Capture and Enterprise Content Management - ECM) with emerging AI, ML, NLP and hyper-automation technologies.

Developing the earliest natural language processing (NLP) applications for ECM, later with Artificial Intelligence and Machine Learning (AI, ML), has led their introduction into Document Imaging and Capture while at FileNet and IBM. Now at ABBYY, a leader in intelligent document processing, he currently manages its enterprise markets for Digital Intelligence and Intelligent Document Processing.

Request information

Contact us to request more information on ABBYY solutions for Enterprise.

Thank you for submitting the form!

We'll get back to you shortly!

Subscribe for updates

Your subscription was successful! Kindly check your mailbox and confirm your subscription. If you don't see the email within a few minutes, check the spam/junk folder.

Connect with us
ABBYY Timeline

Raise your Process IQ