Written by Sri Ramaswamy and Sabine VanderLinden

Artificial Intelligence (AI) promises to revolutionize many industries and the insurance sector stands at the forefront of this technological transformation. However, as AI streamlines processes and enhances decision-making, a darker side emerges—algorithmic denial. 

This practice, where automated systems make critical decisions about insurance claims, is reshaping the landscape of commercial insurance, often at the expense of those it's meant to protect.

The Human Face of Algorithmic Denial

Consider the story of Frances Walter, an 85-year-old woman living in Atlanta whose experience brings the cold reality of algorithmic denial into sharp focus. After shattering her shoulder, Walter found herself at the mercy of an AI-driven decision that would profoundly impact her recovery, Walter's Medicare Advantage insurer, Security Health Plan, relied on an algorithm developed by NaviHealth to predict her recovery time. 

The algorithm's verdict? 16.6 days. On the 17th day, despite medical notes indicating severe pain and an inability to perform basic tasks independently, Walter's insurer cut off payment for her care.

This case starkly illustrates the human cost of algorithmic decision-making in insurance. Walter's story is not an isolated incident but a symptom of a broader trend where algorithms are increasingly used to deny claims, often without sufficient oversight or consideration of individual circumstances. 

The Efficiency Paradox

The insurance industry's embrace of AI is driven by the promise of increased efficiency and cost reduction. AI technologies are indeed streamlining processes across the board, from claims processing and underwriting to customer service. This automation not only speeds up processes but also reduces the likelihood of human error, theoretically improving accuracy and efficiency.

Sri Ramaswamy, CEO of Charlee.ai and a leading expert in AI for insurance emphasizes the potential benefits:

"At Charlee.ai, we believe that fairness and transparency are non-negotiable in the insurance industry. Our AI models are meticulously designed and validated by industry experts to eliminate bias, ensuring that every decision is rooted in objectivity and trust. By combining cutting-edge technology with domain expertise, we are setting a new standard for ethical AI in insurance."

However, the efficiency gained through AI comes with a significant caveat. The same algorithms that process claims at lightning speed can also deny them just as quickly, often without the nuanced understanding that human reviewers might provide.

The Dark Side of Automation

The impact of algorithmic denial extends far beyond individual cases. Major insurers like Cigna, Humana and UnitedHealthcare have faced scrutiny for using AI to deny claims and prior authorization requests, particularly for Medicare Advantage plan holders requiring post-acute care. These denials have been significantly higher for post-acute care compared to other types of care, raising concerns about the use of AI to prioritize financial gain over patient health.

Sometimes, claims are only accepted on medical grounds with a detailed review of the patient's file, often in under two seconds. This process has been criticized for prioritizing cost savings over patient care, as it can lead to denials without thorough consideration of medical necessity.

Bias and Ethical Concerns

The use of AI in insurance claim processing introduces risks of algorithmic bias, where certain demographic groups might be unfairly targeted or disadvantaged due to the data and algorithms used. AI systems can inadvertently perpetuate existing biases if they are trained on biased data, leading to discriminatory practices in claim approvals and premium pricing.

Ramaswamy addresses these concerns:

"The insurance ecosystem thrives on trust, and at Charlee.ai, we are committed to upholding that trust through compliance and innovation. By collaborating with regulators and industry experts, we ensure that our AI solutions not only meet but exceed the standards of fairness, accuracy, and transparency. Our goal is to empower insurers to make better, unbiased decisions while safeguarding the integrity of the industry."

The Regulatory Response

The growing awareness of these issues has prompted regulatory bodies and consumer protection agencies to call for greater transparency and accountability in the use of AI by insurers. States like Colorado and California are developing guidelines and legislation to hold insurers accountable for the use of AI, ensuring that these systems do not unfairly discriminate against protected classes.

Striking a Balance

As the insurance industry continues to evolve with AI, the challenge lies in striking a balance between efficiency and fairness. While AI offers significant potential for improving operations, it also poses challenges related to transparency and equitable treatment of all consumers.

Addressing these challenges requires:

1. Careful regulation and oversight of AI systems in insurance.
2. Development of responsible AI practices that prioritize fairness and transparency.
3. Provide model explanations 
4. Integration of human oversight in critical decision-making processes.
5. Continuous testing and improvement of AI models to mitigate bias.
6. Enhanced collaboration between data scientists, compliance teams, and domain experts to address potential issues at every stage of AI development and deployment.

Where do we go from here?

The story of algorithmic denial in insurance is still unfolding. As we navigate this new landscape, it's crucial to remember that behind every denied claim is a human story—a person like Frances Walter, whose life can be profoundly affected by an algorithm's decision.

The promise of AI in insurance is undeniable, but so too are the risks. As we move forward, the industry must prioritize ethical considerations, transparency, and human-centered approaches to ensure that the efficiency gained through AI doesn't come at the cost of the very people insurance is meant to protect.

In the end, the true measure of AI's success in insurance will not be the speed of processing or the reduction of costs but its ability to serve policyholders fairly, transparently, and compassionately. 

Only then can we say that AI's promise in insurance has truly been fulfilled.