In an increasingly automated world, artificial intelligence (AI) is transforming industries, and insurance is no exception. While AI promises efficiency and speed in claims processing, it also introduces a new frontier of challenges when your claim is denied by an algorithm. This article delves into what happens when AI denies your insurance claim, your rights, how to fight back, and the evolving landscape of AI in insurance.

The Rise of AI in Insurance Claims

Insurance companies are rapidly adopting AI for various functions, from underwriting and fraud detection to, crucially, claims processing. AI systems are designed to analyze vast amounts of data, identify patterns, and make rapid decisions. This can lead to:

• Faster Processing: AI can process claims in minutes, far quicker than human review.
• Cost Reduction: Automating routine tasks can significantly reduce administrative overhead for insurers.
• Fraud Detection: Algorithms can flag suspicious patterns that might indicate fraudulent claims, potentially saving insurers billions.
• Risk Assessment: AI helps insurers assess risk more precisely, leading to more tailored policies and pricing.

However, this efficiency often comes at a cost, particularly for policyholders who find their legitimate claims denied by an opaque algorithmic decision. Reports indicate a troubling rise in claim denials, with some major insurers showing denial rates as high as 33%. This “AI arms race” among insurers to streamline operations can, at times, prioritize cost-cutting over fair and nuanced claim assessment.

How AI Denies Claims

AI-powered systems deny claims by:

• Identifying “Errors” or “Inconsistencies”: AI algorithms might flag minor discrepancies in documentation, coding errors, or missing information as grounds for denial.
• Lack of Contextual Understanding: AI struggles with the nuances of individual cases. Complex medical conditions, unique travel arrangements, or unforeseen circumstances often fall outside the “standard patterns” the AI is trained on, leading to unjustified rejections.
• Algorithmic Bias: If the data used to train the AI contains biases, the AI can perpetuate and even amplify them. This can lead to unfair denials for certain demographics or for treatments that deviate from a pre-defined norm.
• Pre-existing Condition Flags: In property insurance, drones and AI might identify “pre-existing” issues or un-reported risks, leading to claims being denied based on manipulated coverage terms.
• “Medical Necessity” Determinations: In health insurance, AI might deem a treatment or service “not medically necessary” based on its data, even if a human medical professional strongly advocates for it. This can lead to delays in crucial care.

A prime example comes from the healthcare sector, where an algorithm called “nH Predict” used by UnitedHealth Group was found to override clinical judgment and deny rehabilitation care to seriously ill patients. The algorithm’s projections often conflicted with Medicare rules, leading to premature payment denials for stroke victims, cancer patients, and amputees.

What Happens When Your Claim is Denied by AI?

The immediate impact of an AI-driven denial can be significant and distressing:

• Unexpected Financial Burden: Denied claims often result in surprise bills and substantial out-of-pocket expenses.
• Delayed or Forgone Care: For health insurance, a denial can mean postponing or abandoning necessary treatments, potentially worsening health outcomes.
• Administrative Burden: Policyholders and even healthcare providers spend countless hours appealing these denials, diverting time and resources.
• Erosion of Trust: The experience of being “digitally ghosted” by an insurer, with no clear human explanation for a denial, can severely damage trust in the insurance system.

Your Rights and How to Fight Back

In the UK, consumers have specific rights when facing an automated decision, especially if it significantly impacts their lives.

1. Understand the Reason for Denial: The first crucial step is to obtain a detailed explanation for the denial. Your insurer is legally obligated to provide this. Look for specific codes, policy clauses, or data points cited as the reason. If the reason is unclear, contact the insurance company for clarification.

2. Request Human Intervention (Right to Review): Under UK GDPR regulations, you have a clear right to demand a human review of any automated decision that significantly affects you. This is a powerful right that many policyholders are unaware of. Insurers are generally required to offer an appeals process that includes human oversight.

3. Collaborate with Relevant Parties:

• Healthcare Providers: If it’s a medical claim, work closely with your billing and coding team. They can help identify any errors in medical records or coding that might have triggered the AI’s denial. They can also provide supporting documentation to establish medical necessity.
• Brokers: If you purchased your policy through an insurance broker, they might be able to assist in making a complaint on your behalf.

4. The Internal Appeals Process: Formalize your complaint with the insurance company.

• Be Clear and Concise: Include your name, policy number, claim number, and clearly mark the communication as a “complaint.”
• Provide Evidence: Attach any supporting documentation, such as medical reports, photos, original application forms, and detailed explanations of why you believe the claim should be paid.
• State Your Desired Outcome: Clearly articulate what you want the insurer to do to rectify the situation.
• Keep Records: Maintain a meticulous record of all interactions, including dates, names of individuals spoken to, and summaries of conversations.

5. External Review – The Financial Ombudsman Service (FOS): If you are unhappy with the insurer’s final response, or if they fail to respond within eight weeks, you can escalate your complaint to the Financial Ombudsman Service (FOS). The FOS is an independent, free service that investigates complaints between consumers and financial companies.

• Impartial Review: The FOS will consider all facts and circumstances, including policy wording, relevant laws, regulations, and industry best practices.
• Binding Decisions: If the FOS finds that the insurer acted unfairly, they have the power to instruct the insurer to explain its actions, apologize, and pay compensation or take other appropriate steps to rectify the situation.

6. Legal Advice: If all else fails, or if the claim is substantial, seeking professional legal guidance is advisable. Lawyers specializing in insurance disputes can help navigate complex legal frameworks and advocate on your behalf.

The “AI Arms Race” in Appeals

Interestingly, just as insurers leverage AI to deny claims, a counter-movement is emerging where AI is being used to fight back. Companies are developing AI-powered tools that:

• Analyze Denied Claims: These systems can identify the precise reason for rejection by analyzing denial letters and cross-referencing them with medical guidelines and patient history.
• Generate Appeal Letters: AI can auto-generate compelling appeal letters, citing clinical guidelines, insurer policies, and relevant legal precedents, significantly reducing the time and effort required for appeals.
• Automate Follow-ups: Some AI voice agents are being trained to call insurance companies, follow up on appeal statuses, and persistently engage with insurers to ensure timely resolution.

This “AI vs. AI” scenario has the potential to level the playing field, forcing insurers to reconsider blanket denials if every rejection is met with a swift, well-supported appeal.

The Future of AI in Insurance

The role of AI in insurance is only set to expand. We can expect:

• Enhanced Predictive Analytics: AI will become even more adept at forecasting claim denials, allowing insurers to take proactive measures, but also potentially leading to more targeted denials.
• Increased Automation: More routine tasks in claims processing will be fully automated, freeing up human staff for more complex cases requiring empathy and nuanced judgment.
• Integration with Other Technologies: AI will increasingly integrate with blockchain (for tamper-proof records), robotic process automation (RPA), and the Internet of Things (IoT) to further streamline processes and enhance fraud detection.
• Greater Focus on Governance and Ethics: As AI becomes more pervasive, there will be increasing pressure for robust governance frameworks, transparency in AI practices, and ethical considerations to prevent bias and ensure fairness. Regulators like the UK’s Financial Conduct Authority (FCA) are already raising concerns about bias and discrimination in AI-driven decisions.
• “Explainable AI” (XAI): There’s a growing need for AI systems to be more transparent, allowing for human understanding of how and why a decision was reached, especially in high-stakes situations like insurance claims.

Ultimately, while AI offers immense potential for efficiency in the insurance sector, its deployment must be balanced with robust human oversight, accountability, and a steadfast commitment to consumer rights. As policyholders, understanding these developments and knowing your rights is paramount to navigating the evolving landscape of AI-driven insurance claims.