What Is AI Document Automation for Insurance?

Make Better, Human-Centric Claims Decisions with Insurance Document Automation

Insurance teams are drowning under the volume and complexity of claims documents, creating bottlenecks that ripple through every aspect of operations.

Adjusters spend countless hours sorting and reading documents to extract and understand key information, slowing down claims processing, increasing the risk of costly errors, and frustrating policyholders.

That's why forward-thinking carriers use AI document automation for insurance.

In this article, we'll explore what is document automation for insurance, including how the technology works and how it benefits carriers by reducing claims leakage, futureproofing claims departments, and enabling adjusters to work more effectively & efficiently.

We'll also discuss how insurance document automation makes workflows faster and more accurate & secure via processing, categorizing, and extracting data from complex documents.

What Is Insurance Document Automation

Document automation for insurance uses AI to process claims documents and collect data to provide time-saving insights to adjusters, investigators, lawyers, and underwriters.

It provides features like scanning documents in bulk, extracting structured & unstructured data, categorizing & organizing data for information retrieval, and generating summaries to understand claims details.

But instead of AI replacing insurance workers, which can jeopardize claims decisions, compliance, and ethics, document automation for insurance claims processing enables creativity and intuition so workers can make faster & fairer decisions.

Types of AI for Insurance Document Automation

Owl.co's document automation for insurance is powered by a custom vision-language model (VLM) that handles the entire lifecycle of document processing, from receiving document batches to gaining actionable insights.

But here's the catch: not all AI insurance document automation is created equal. What are the different types of AI technology for insurance documentation and how do they work?

Optical-Character Recognition (OCR)

Traditional methods often fall short with processing accuracy. A standard approach, optical-character recognition (OCR), reads text from images but can't grasp context, decipher messy characters, or adapt to the endless, different layouts that define real-world documents.

Intelligent-Character Recognition (ICR)

Intelligent-character recognition (ICR) is a variation of OCR for handwritten text. But it fares poorly with cursive writing and relies on shared, rigid models that struggle to adapt to unique handwritings.

Natural-Language Processing (NLP)

Natural-language processing (NLP) is a high-level field of AI that enables AI to understand, interpret, generate, and interact with human language. It uses machine learning to study large amounts of text data, powering many AI systems like language-learning models (LLMs).

When combined with visual elements, LLMs can take the form of a vision-language model (VLM) for superior precision.

Vision-Language Models

A breakthrough for the insurance industry, VLMs are AI systems that don't just read text, but actually understand context like humans. A VLM is a multimodal LLM, combining images and text to account for a text’s position on a page, comprehend or fill in missing context, etc.

Owl.co's AI document-processing tool for insurance, OwlVision, combines OCR and ICR for base-level processing before subjecting documents to our customized VLM for enhanced accuracy and quality control.

This process enables OwlVision's best-in-class precision levels for AI document automation, enabling advanced features like AI document classification for insurance and data extraction & organization.

A VLM can:

• Tell which documents need to go to legal, which warrant investigation, etc.;
• Decipher barely legible scrawl and messy handwriting; and
• Learn to classify document types and segment & link claim documents together.

Additionally, AI document automation powered by a VLM can:

• Extract the right datapoint from a complex document because it knows where the datapoint typically appears and what it looks like;
• Validate information against existing policy data to flag inconsistencies and potential compliance risks; and
• Generate summaries that highlight the most critical information for human review.

Why Leaders Choose Insurance Document Automation

Insurance leaders choose AI document automation to scale claims operations, improve policyholder satisfaction, and adapt to shifting regulations while futureproofing their organization.

Ultimately, with robust AI document automation that's accountable, effective, and ethical, leaders can build a new future for insurance.

Scaling Claims Operations

The typical insurance claim has dozens or sometimes hundreds of documents, medical records, workplace assessments, external datapoints, and more. And many adjusters unsustainably handle upwards of 125 claims per month.

Plus, the claims-handling workforce is shrinking while caseloads rise. Even if you could increase headcounts, the team-scaling fallacy means biases in claims decisions would grow as well.

Document automation for insurance is critical because manual processes for handling volume don't scale anymore. Adjusters aren't just processing more documents—they’re processing more document types from more sources and in more formats.

Improving Policyholder Satisfaction

Policyholders expect you can handle their cases quickly and transparently.

An industry report reveals that a whopping 31% of claimants on average feel unhappy with their providers, and among them, 60% cited settlement speed and 45% closing-process issues as reasons.

When you can't deliver on expectations, you erode trust and drive away customers. AI document automation for insurance enables claims teams to deliver faster & fairer outcomes so carriers can optimize retention rates and support claimants when they most need help.

Strengthen Compliance and Futureproof Operations

The regulatory environment is cracking down on insurance carriers, requiring meticulous documentation and audit trails. In the past several years alone, direct compliance costs have surged by 40%. Every decision needs to be justified and every process traceable.

Enterprise providers of AI document automation for insurance like Owl.co build accountability into their technology with citations, explainability, human-in-the-loop features, and more to protect claims teams.

How Insurance Document Automation Helps Insurance Teams

AI document automation handles both versatility and volume. Each insurance department faces unique challenges, but the underlying problem remains the same: too many documents, too little time, and too much room for human error.

Insurance document automation benefits claims adjusters, fraud investigators, and legal teams by freeing them from tedious tasks so they can use their creativity and intuition to make better & faster decisions.

Claims Handling

Using AI for claims processing transforms an adjuster's role and expands an insurance carrier's capacity.

• Faster Triage and Assignment: Instead of spending hours sorting through documents, adjusters can leverage AI document automation to categorize first notices of loss, medical notes, workplace assessments, and more, and route them to correct workflows.
• Automated Data Extraction: Document automation for insurance accurately extracts datapoints like injury details, workplace conditions, and more to feed actionable insights to adjusters, empowering their human judgment.

The impact on turnaround and quality is dramatic. Adjusters can handle 40–50% more cases without working longer hours and spend more time on meaningful tasks rather than hunting for information buried in paperwork.

Special Investigation Units (SIU) and Fraud

With document automation, SIU teams can instantly find details that don't add up and become alerted to patterns & inconsistencies that suggest fraud or disqualifying claim circumstances.

• Real-Time Anomaly Detection: AI can quickly ingest and analyze vast volumes of structured & unstructured document data so investigators can uncover critical details more effectively and efficiently than what a human with tight deadlines might miss.
• Reliable Tools for Fair Decisions: Precise data-extraction technology in AI document automation with human-feedback mechanisms gives investigators confidence to make fair and ethical conclusions, reducing claims leakage and supporting genuine claimants.

AI document automation isn't meant to replace human workers. Instead, it's a powerful tool to embolden an investigator's inner detective, helping them solve cases faster, better, and fairer.

Legal Teams

Legal teams need everything documented perfectly because missing a single detail can trigger expensive legal challenges or put ongoing cases at risk.

• Automated Flagging: AI document automation flags missing details, detects discrepancies, and provides helpful context, liberating lawyers to be the researchers they are. It can instantly compile relevant info and generate legal documents too.
• Airtight Audit Trails: With AI, every document, extraction, and decision point is logged and traceable, drastically simplifying lawyers' workflows and satisfying adjudicators, judges, and regulators with bulletproof documentation of processes.

Ultimately, AI document automation benefits legal teams by enabling them to focus on what they do best: using their creativity and intuition to protect insurance carriers and support claimants.

What to Look for in AI Document Automation for Insurance

Not all document automation solutions are built equally, and many aren't specialized for insurance claims.

If you're an insurance leader, here are some examples of what to look for when evaluating document-automation solutions:

1. Built for Insurance

The best document-automation solutions are purpose-built for insurance, trained on vast sets of claims data and industry-relevant user feedback.

This deep domain expertise ensures contextual understanding for clarity, accuracy, and speed in everything from data extraction to document classification.

2. Accountable by Design

Trust is a defining characteristic of the insurance industry. Don’t settle for anything less than a solution that is governable, empowers human accountability, and shows exactly how & why it generates its insights from extracted data.

Black-box systems are compliance nightmares that gut customer trust. However, explainable AI in insurance, for example, gives claims leaders the oversight and control needed for confidence and continuous improvement.

3. Secure and Compliant

With sensitive data from thousands of policyholders at stake—not to mention claimants' livelihoods sometimes—AI document automation should have the highest grade of security.

Compliance violations, data breaches, a lack of anti-bias features, etc., can cost millions and permanently damage your reputation and claimants' well-beings.

Toolkits with built-in compliance standards for SOC 2, GDPR, CCPA, and HIPAA protect both your organization and your customers.

4. Scalable and Adaptable

A good AI solution for document automation needs to be scalable given fluctuating volumes and often-changing document types & business needs. An AI system that continuously learns from & adapts to feedback for actionable claims insights is essential for sustainable growth.

An ideal document-automation toolkit should include core document-processing features as part of a holistic toolkit for tasks like insurance document generation based on processed data.

Enterprise Document Automation for Insurance with OwlVision

Document automation for insurance is important because it reduces manual data processing, optimizes accuracy, mitigates biases, lowers leakage costs, and saves time.

AI that extracts data with precision and provides actionable insights liberates claims teams to use critical-thinking skills to make better decisions and help policyholders.

That’s the advantage of Claims Intelligence, leveraging AI-enabled data & knowledge to transform insurance with human-centric solutions that boost the bottom line and support customers & their livelihoods.

OwlVision, part of Owl.co's AI solutions for insurance, includes comprehensive document automation features that empower teams with Claims Intelligence, including:

• Smart document ingestion, pulling structured & unstructured data from complex claims documents.
• Advanced classification and tagging to automatically segregate and label documents for easy information retrieval.
• Entity extraction and normalization to pinpoint the specific data your teams need, no matter how messy the source.
• Safe, deterministic AI that understands data inherent to unique claims with human-in-the-loop mechanisms for accountable & ethical outcomes.

The proof is in the results, such as:

• 97% precision in document processing—the industry's highest accuracy rate.
• 84% drop in claims-processing times.
• 30% fewer audits.
• 3x increase in employee trust of company mission & purpose.

Book a demo today and learn how to futureproof your organization with OwlVision and AI document automation for insurance.