Your Guide to AI for Casualty Claims
The AI Playbook for Claims Professionals
Artificial intelligence (AI), with its predictive prowess and generative capabilities, has become a game-changer for insurers seeking enhanced efficiency and advanced risk analysis.
AI is quickly becoming table stakes, and many claims professionals are feeling the pressure to implement a solution quickly. But with so much noise, and technology changing so rapidly, it can feel overwhelming to get started.
Whether you’re a seasoned professional or just starting your journey, we’ll guide you on the initial steps to seamlessly integrate AI into your claims management strategy, revolutionizing how you assess, predict, and mitigate risks.
Keep reading as we discuss how insurers leverage AI technologies to navigate the complexities of claims processing.
Hi, I’m CLARAty the Meerkat!
I’m always on the lookout for signs that a claim is about to escalate. Come with me as we explore how augmented intelligence helps you achieve optimal claims outcomes.
Contents
Chapter 1
Defining AI in Casualty Claims
It seems like every industry is talking about artificial intelligence—but what does that really mean? Let’s dive deeper into these terms and explore new definitions around the role of AI.
What is AI? And what does it have to do with insurance?
“Artificial intelligence (AI) is a technology which enables computer systems to accomplish tasks that typically require a human’s intelligent behavior. Examples include gathering information, analyzing data by running a model, and making decisions.”-National Association of Insurance Commissioners
Just as GPS helps you navigate to your destination, AI technology can help you navigate to optimal claims outcomes. Your GPS isn’t driving for you; you still need to decide how to operate the vehicle, which route to take, and how to handle any unforeseen circumstances (yes, even self-driving cars still need human supervision).
Here are a few examples of how AI makes it easier for insurers to optimize claims management:
- Keep track of claims with automated alerts and insights.
- Know which claims to prioritize and when to take action (before claims become too costly).
- Select the best provider for optimal claim and patient outcomes
- Identify the best attorney for claims in litigation
- Instantly scan and analyze claim documents and medical records
Why is everyone talking about generative AI?
Lately, the hottest trend disrupting every industry is generative AI. Generative AI describes algorithms that can be used to create new content, including text, images or other media.
You may have heard a lot about new tools like ChatGPT, Bard, DALL-E, Midjourney and DeepMind. These are all examples of generative AI.
When applied to casualty claims, generative AI can help claims managers massively increase their productivity.
Examples of some of the tasks generative AI can help with include:
- Generating a summary of the claims lifecycle in narrative format attorney involvement predicted because of x & z factors in narrative form
- Grouping lists of recommended actions taken previously and their outcomes
- Explaining and alerting issues with claims and helping manage outliers
- Providing a summary of litigation strategies and outcomes
- Providing percentages for specific interventions needed based on claim info
For generative AI to reliably generate responses, its models need to be trained on a tremendous amount of data. ChatGPT was trained on tebibytes of data and billions of pages.
For generative AI to work for insurance, AI models must be trained on millions of closed claims to enable unmatched prediction accuracy.
Artificial intelligence, or augmented intelligence?
‘AI’ may stand for artificial intelligence, but when applied in combination with human expertise, it becomes augmented intelligence.
Augmented intelligence is the technology that helps humans to do their jobs more efficiently by handling the simpler tasks that are easy to automate and creating insights from complex data interactions that a human may miss.
4 common myths about AI in the insurance industry
AI has been a topic of discussion for years, and it’s no surprise people have concerns about its impact on the insurance industry. As the use of AI grows, many myths surround its implementation.
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Explore how AI can work hand-in-hand with human expertise to improve overall outcomes.
Chapter 2
How can AI support casualty claims management?
Claims professionals are under constant pressure to provide customers with efficient, accurate, and cost-effective services.
With the help of AI tools such as machine learning, natural language processing, and optical character recognition, claims professionals can now analyze vast amounts of data and extract actionable insights from complex documents, leading to better decision-making and improved outcomes.
Example 1: How AI helps minimize the impact of litigation
For workers compensation claims with attorney involvement, the average indemnity costs were 390% higher than for unrepresented claims ($77,807 vs. $15,936). The median cost was 740% higher.
AI can help claims professionals manage the research and analysis involved in the litigation process so they can focus on better legal outcomes.
Here’s how it works—
AI-powered tools predict litigation risk based on years of prior claims. These insights are most robust when working from a contributory database of claims sourced from numerous companies across the industry—not just internal data.
Pulling from this database, the AI can then identify tightly defined claim cohorts in specific jurisdictions that yield insights about the future direction of a claim.
How impactful is AI? Just a 1% reduction in claims with attorney involvement can save millions of dollars in legal fees and expenses.
How impactful is AI? Just a 1% reduction in claims with attorney involvement can save millions of dollars in legal fees and expenses.
Key benefits of AI in streamlining litigation management
By automating routine tasks such as document review and legal research, claims professionals can focus on more complex tasks such as strategy development and communication with parties involved in the litigation process.
- Avoid litigation by quickly determining which cases are at risk and recommend de-escalation tactics
- Improve outcomes by selecting top-performing attorneys fit for each case
- Optimize legal strategies by using data to decide whether to replace counsel or pursue settlement
Example 2: How AI offers a second set of eyes on medical records and legal demand letter reviews
AI can help claims adjusters by automating the review and analysis of medical records and legal demands.
AI automates medical records transcription, extracts and organizes important details about each claim, and makes that information available to claims adjusters, NCMs, attorneys, and anyone involved in making claims decisions.
Using AI to review medical records and legal demands reduces review time by 80-90%. Every page read saves 1.8 minutes—over hundreds of documents, that adds up to major savings.
Key benefits of AI for medical records and legal demands
By automating the review and analysis of medical records and legal demands, claims adjusters can more quickly identify important details and potential issues—and with greater accuracy.
- Quickly respond to changes
- Reduce time to review claims
- Reduce the risk of human error
- Proactively manage claims
- Extract key medical information
Use cases for AI in commercial casualty insurance
Insurance companies are using AI in various processes such as underwriting, risk management, claims processing, and customer service. These companies use AI-powered algorithms to analyze historical data, identify patterns, and make predictions.
They also use augmented intelligence to automate manual processes such as data entry, claims processing, and underwriting.
Case study
Where insurers can get started with using AI
- Straight-through claims processing to expedite the resolution of claims more accurately by analyzing claims data
- Automate the underwriting process, resulting in faster and more precise risk assessments by analyzing extensive data such as health records, demographic information, and lifestyle habits and providing personalized insurance products
- Assist in fraud detection by detecting anomalies or unusual patterns in vast amounts of data, allowing companies to reduce the risk of fraudulent claims and save money
- Enhance the customer experience by offering personalized recommendations and providing convenient and efficient channels for interaction with insurance providers
- Optimize pricing and profitability by evaluating substantial amounts of data to evaluate risk levels and pricing accordingly
- Improve industry benchmarking by participating in the contributory database to better train models that move the industry forward
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Dive into the role of AI in casualty claims management to enhance decision-making and reduce litigation.
Chapter 3
How to adopt AI for casualty claims management
CLARA Analytics is the leading casualty claims intelligence platform for risk professionals and the AI decision support assistant for adjusters used at carriers, MGA/MGUs, reinsurers and self-insured organizations for loss cost and expense savings.
We help leading insurers accelerate AI adoption with CLARAty.ai, our mature AI platform with generative and predictive AI models developed specifically for casualty claims.
How does CLARA work?
CLARA’s AI solutions are powered by our contributory database. This contributory database enables CLARA to offer accurate, insurance-specific insights.
The contributory database is a growing repository of casualty claims outcomes from 2017. While every casualty claim is unique, our solutions can find similar cases in the database and relay important information to claims professionals. Our AI also adapts to new data as the nature of claims, treatment, and litigation change.
CLARA’s contributory database is much more robust than other systems, which simply organize pieces for the user. Our system not only organizes the pieces but also builds the puzzle, making it an invaluable tool for claims professionals.
How accurate are CLARA’s AI predictions?
When it comes to AI, the larger the contributory database, the more accurate the predictions.
AI is known to introduce bias (it’s learning from humans, after all), but a larger dataset helps to minimize that risk.
If you were to try to build AI models on internal data, you probably wouldn’t have enough data to determine which physician or attorney is suitable for the particular claim to achieve the best outcomes.
Training AI models on millions of closed claims enables unmatched prediction accuracy and a depth in benchmarking that gives the users insights into new markets.
CLARAfied and CLARAvoyant: Use cases for AI claims management
What does the AI experience look like with CLARA? Let’s take a peek at the future of claims.
CLARA Analytics is revolutionizing casualty claims intelligence with generative AI.
Conclusion
Supporting the claims adjuster of tomorrow
The future of claims management is undeniably intertwined with the harmonious collaboration between artificial intelligence and human expertise.
At CLARA, we champion the concept of AI as augmented intelligence, recognizing that its true power lies in supporting, not replacing, the claims adjuster of tomorrow. Our platform, designed with this vision in mind, serves as a valuable ally in training new adjusters and bolstering the capabilities of seasoned professionals.
By harnessing the collective wisdom derived from millions of settled claims, CLARA’s AI insurance platform directly provides predictive and prescriptive insights where claim adjusters operate.
Join us as we redefine the landscape of insurance through the lens of augmented intelligence.