Indico Data named a leader in Everest Group’s intelligent document processing (IDP) PEAK Matrix® 2023
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             PEAK Matrix® 2022  
Indico Named as Major Contender and Star Performer in Everest Group's PEAK Matrix® for Intelligent Document Processing (IDP)
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Automated Claims Processing for Insurance Providers

How claims document processing automation increases business efficiency and customer satisfaction


F50 Insurance company achieves 300% ROI with Indico Data

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The ability to efficiently process claims is crucial for any commercial insurance company, but one that’s also labor-intensive, involving numerous unstructured documents and images. A solution lies in intelligent intake, which applies artificial intelligence to automate insurance claims processing and eliminate some 70% of manual document handling.

Commercial insurance claims tend to be complex, involving ACORD forms, images, names, dates, and more. And of course, insurers have to confirm the policy is active and the loss is covered, all of which has traditionally required human intervention. But intelligent insurance claims automation dramatically changes the equation, speeding the process by 4x or more.

Simply put, that means insurance companies can process more claims far faster. That keeps clients happy, which is crucial to client retention and can even be a competitive differentiator. Insurance claims automation also means it takes fewer employees to do the job, which frees up staff for more strategic work and helps your company grow without adding headcount.

The claims intake dilemma: speed vs. accuracy

When it comes to claims processing, commercial insurance companies historically have been forced to choose between speed and accuracy.

Choosing speed means increased risk of errors and non-compliance, making hasty adjudication decisions that can affect profitability, and negatively impacting the customer experience if things go awry.

But choosing accuracy means risk of losing out to more nimble competitors that offer a faster customer experience and frustrating customers with long settlement times. That, in turn, negatively impacts your net promoter score (NPS), ultimately leading to customers jumping ship.

“Claims dissatisfaction is a major factor in driving policyholders to switch to another company, with 74% of dissatisfied customers either saying they did change providers (26%) or are considering it (48%),” according to a 2022 Accenture study.

Learn how a F50 Insurance company achieves 300% return on investment with Indico Data.

Applying artificial intelligence to insurance claims

Intelligent intake platforms mean you no longer have to choose between speed and accuracy. The platforms employ numerous artificial intelligence technologies, including natural language processing, machine learning and transfer learning. Together, these technologies enable employees who actually process claims – such as claims handlers and loss adjusters – to build insurance claims processing automation models. There’s no need to involve data scientists, or even IT. That delivers a higher level of model accuracy and significant scalability, boosting insurers' ability to roll out automation models across the company.

Integration with insurance automation platforms

Part of the reason intelligent intake delivers a 70% reduction in manual document handling is integration with downstream insurance claims automation platforms such as Guidewire ClaimCenter. Today that’s a familiar swivel chair process, where a claims handler reads a claims email and attachments, looking for data to enter into Guidewire, including case owner, case status number, cause and date of loss, estimates for extent of loss, and the like.

With an intelligent intake solution such as Indico’s, AI models can “read” claim emails and attachments and pre-populate some 80% of the required fields in Guidewire ClaimCenter. This kind of automated claims handling not only dramatically speeds processing time but increases accuracy - because computers don’t get tired and make mistakes like people do. In fact, intelligent intake solutions that support staggered loop machine learning become more accurate over time by learning from when users accept or correct a model’s predictions and classifications.

View Episode 9 of Unstructured Unlocked, where Indico Data’s Christopher Wells talks with Steven Weiss, former Senior Vice President and Chief Underwriting Officer at Munich Re Specialty Group Insurance Service.

Automation in claims processing: Use cases

Claims automation for insurance can apply to a number of use cases. Following are just a few examples.

Help with corporate email in-boxes
Chief among the areas that are ripe for automated claims processing is the corporate email in-box. It’s common for insurance companies to have a single email address to which clients send claims information that constitute first notice of loss (FNOL).

Many of these emails contain not only potentially complex requests, but attachments, such as ACORD forms, photos showing building or vehicle damage, and the like. Much of this data will be unstructured, making it beyond the scope of a robotic process automation (RPA) solution for claims automation. But an intelligent intake platform can read and triage each email, determining where each should be routed. The platform can also extract attachments, and “read” them to find pertinent data and input it into downstream processing systems such as Guidewire. It adds up to faster insurance claims processing and improved customer satisfaction.

Automating workers’ compensation claims
Any form of claims litigation can be costly for a commercial insurance company, but workers’ compensation claims can be particularly painful because they involve two paper-heavy industries: medical and legal. Medical records can be hundreds of pages long, yet must be examined to comply with subpoenas, legal discovery requirements and the like.

Such examinations take extensive resources. But applying intelligent intake technology can ease the burden. With AI models that can reduce manual processing by 70% to 80%, insurance companies can dramatically increase their process capacity, make reviews faster and more effective, and reduce the need to outsource processing.

Efficiently deal with catastrophe claim surges
Dealing with surges in claim volume following catastrophes such as hurricanes, earthquakes, and floods can severely test any commercial insurance company. Claims that normally take only a day to process can stretch to several weeks amid the high volumes such events prompt.

An intelligent intake solution offers a remedy. Increasing the capacity of an automated claims processing solution is a simple matter of adding compute capacity; easily done in a cloud environment. Given the intelligent intake solution can automate as much as 80% of the process, that leaves only 20% for manual review. Whether that difference is made up with internal employees or third party administrators, it’s a much easier lift at far less expense.

Meet compliance requirements with explainable AI

A key concern in a highly regulated industry like insurance is the ability to explain why an automated, AI-based solution makes the decisions it does. If a claim is rejected, the insurance company must be able to explain in simple terms the reason behind that decision. A sound intelligent intake tool will make that easy, with an audit trail that makes clear – in plain English – the rationale behind each claim decision. Additionally, given insurance claims handlers create the automated models, the AI models naturally reflect the way these professionals think during the claims assessment process.

Read our blog: How intelligent automation speeds up insurance underwriting and claims processing.

Setting the stage for AI-based insurance analytics

Beyond claims handling automation, intelligent intake solutions also set up commercial insurance companies to take full advantage of AI-based analytics tools that promise more advances in claims handling, underwriting and more.

There’s no limit to the number of fields an intelligent intake solution can extract from the unstructured documents typically involved in a commercial insurance claim. While your Chief Claims Officer may require only, say, 20 fields, your data analytics team could well be interested in 100. That would give them more data to use for predictive applications, loss modeling, actuarial projects and more.

Fraud detection is just one example. More than 7,000 insurance companies collect over $1 trillion in premiums each year, the FBI estimates, making them a prime target for illegal activity. The total cost of insurance fraud exceeds $40 billion per year, the FBI says – and that doesn’t include health insurance.

With vast quantities of data at their disposal, analytics teams can employ AI-based tools that help them detect nefarious activity and reduce fraud.

Automation is clearly the future for commercial insurance companies. To learn more, click below for an interactive demo, a free trial or to get in touch with any questions.

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