When people can no longer perform the everyday activities of life without some kind of assistance, the clear priority should be to ensure their health and dignity. Money should not be a prohibitive factor. Yet in too many cases, quality long-term care is hindered by financial concerns.
Consider, for example, that Americans who live past the age of 70 can expect on average to spend $172,000 for long-term care over their lifetimes.1 But most families (as many as 83%2) say it would be impossible or very difficult to afford $60,000 for annual in-home or assisted living care expenses.
Life and health insurance companies are working to help bridge this ever-widening gap with long-term care insurance (LTCI). And thanks to a broad range of new innovations enabled by AI, Microsoft and our partners are helping to improve LTCI for policyholders and insurers alike. This is part of our vision for intelligent insurance and our work with Microsoft Cloud for Financial Services.
In this case, helping to make long-term care more accessible and affordable is good not just for enhancing societal well-being and reducing the strain on public resources, but also for the viability of a critical insurance product.
The unique challenges of long-term care insurance
LTCI insures people for a very costly circumstance that is very likely to occur.
About 70% of seniors will require long-term care at some point in their lives,3 and Americans spend more than $471 billion annually for long-term care.4 Yet Medicaid covers only 42% of long-term costs. LTCI aims to address a significant portion of long-term care costs by covering a range of services for people who need assistance with daily living activities—for example, bathing, dressing, and eating—over an extended period, often provided at home.
Despite the prevalence and urgency of the need, however, LTCI has proven challenging for insurers. Rising healthcare costs and higher-than-expected claims have created unforeseen financial pressures. People are living longer, increasing the likelihood of needing to use LTCI, and fewer customers than expected are letting their policies lapse. For insurers, this results in profitability challenges and uncertainty, while customers face higher premiums, and thus reduced access.
How AI can help improve LTCI profitability and growth
The success of insurance companies in addressing the growing need for LTCI will depend on a variety of factors, including education, awareness, and the efficiency and effectiveness of regulation. Above all, technology holds the key for transformation in profitability and growth.
We are seeing tangible results in AI innovation with our insurance customers worldwide that have direct relevance for LTCI providers. These potential benefits are prompting many insurers to accelerate their cloud migration and data management investments—a transition that is key to the LTCI sector, which lags other insurance segments. With the scale, security, and resilience of the Microsoft Cloud combined with the advanced data and analytics capabilities of Microsoft Fabric and the AI development opportunities enabled by Azure AI Studio, insurance companies can innovate rapidly and confidently to meet their specific needs.
The future of insurance in the era of AI
Here are some of the important benefits that insurers can apply to their LTCI offerings.
Enhance underwriting and claims management
AI can streamline underwriting and claims processing in ways that improve both accuracy and efficiency. One important area of focus is straight-through processing (STP)—the automation of an entire workflow, from the initial data entry to the final decision, without the need for human intervention. STP helps to reduce delays, minimize errors, and free up valuable human resources.
In the underwriting process, AI helps enable STP for tasks such as analyzing historical data, assessing risk factors, and predicting the likelihood of claims, which helps underwriters make more informed decisions and reduces the time required for manual reviews. It can also handle a larger volume of applications without a corresponding increase in resources.
In claims processing, STP can automate the assessment and triage of claims—for example, by quickly extracting and analyzing information from a wide range of documents, including medical records, policy applications, and claims forms. Many insurers have long used optical character recognition (OCR) technology to digitize these types of documents. But the addition of generative AI supercharges how they can be understood, evaluated, and acted upon.
Automate contact center experiences
With generative AI’s natural language processing and content creation capabilities, insurers can optimize contact center operations in ways that help both the customer and the company.
AI-enabled copilots and virtual assistants can handle larger volumes of routine inquiries, helping agents and customer service representatives provide faster, more accurate responses to policyholders’ questions about coverage, claims status, and more. For example, John Hancock implemented a new AI solution to provide support for common customer issues and questions, which helps call center representatives focus their efforts and expertise on the most complex cases, with better customer experiences and reduced wait times.
Automated systems can understand and respond to customer inquiries in a conversational way, and even authenticate caller identities with voice biometrics, streamlining the identification process and enhancing security. For LTCI, AI can enable corresponding benefits through more efficient operations, better resource allocation, and enhanced customer experiences.
Prevent fraud, waste, and abuse
In the realm of fraud detection, advanced analytics and AI-powered tools can analyze vast amounts of data from healthcare vendor invoices to identify patterns and anomalies indicative of fraudulent activities in a timely manner. With better insights, insurers can proactively detect and prevent fraud, helping ensure that legitimate claims are processed swiftly while minimizing financial losses.
AI can also help insurers identify unusual patterns or anomalies that could indicate fraudulent or wasteful activities, such as flagging a particular facility if it consistently submits higher-than-average claims for certain treatments. Analyzing historical data can also help inform insurers to create more robust, data-driven processes to determine which facilities to audit or to benchmark best-in-class operators.
Expedite regulatory, contracting, and auditing activities
LTCI is inundated with regulatory, contracting, and auditing activities, many of which rely on cumbersome manual processes. AI can improve the efficiency of many of these workflows while also improving accuracy, turn-around times, and regulatory compliance. Data validation, risk assessment, and regulatory monitoring can all benefit. Moreover, AI’s predictive analytics can spot potential compliance issues, and its enhanced reporting capabilities can aid strategic decision-making.
Advancing LTCI with AI and Microsoft
We believe that with focused, creative innovation with AI, LTCI providers and their customers can look forward to a bright future in which more people can live with dignity and financial security in their senior years, thanks to high-quality, robust insurance products and services. We are excited to work with industry and our global partner ecosystem to strengthen LTCI, in line with Microsoft’s responsible AI principles and our Secure Future Initiative.
To learn more about all our solutions, visit our Microsoft Cloud for Financial Services website.
1AARP, “Long-Term Care Costs May Double to $5.6 Trillion by 2047,” March 2018.
2KFF, “The Affordability of Long-Term Care and Support Services: Findings from a KFF Survey,” November 2023.
3Morningstar, “100 Must-Know Statistics About Long-Term Care: 2023 Edition,” March 2023.
4A Place for Mom, “Long-Term Care Statistics,” September 2023.
As director of insurance strategy in Microsoft’s Worldwide Financial Services group, Jeffery Williams helps insurers deploy Microsoft’s portfolio of cloud and business application solutions to build next-generation capabilities. He has more than 20 years of experience working with C-suite executives to help shape digital strategies that differentiate businesses, elevate digital experiences, and expand margins.