Life insurance policies and annuity contracts pay death benefits to survivors when the insured passes away. Health insurance pays benefits to doctors and hospitals to treat covered expenses. In both cases, benefits paid out by insurers may exceed the amount of premiums paid in by insureds. An insurance company’s profitability depends on accurately estimating life expectancy and healthcare costs. Artificial Intelligence (AI) makes this possible and offers benefits to consumers as well.
How Life Expectancy and Healthcare Costs Impact Annuities
Annuities and life insurance are similar because they are both intended to protect income.
The main difference is that life insurance pays a beneficiary when a life is cut short, while annuity contracts are intended to pay a benefit for living a long time.
Insurers use life expectancy data and health information to ensure they price both products appropriately. This data enables insurers to more effectively align their potential exposure with their earnings potential, and AI plays a pivotal role in facilitating this process.
How AI Works
AI is the field of computer science focused on getting computers to solve problems the way humans do. This requires the programmers to train the machine.
The training comes from algorithms that teach the computer to make decisions it has not been explicitly programmed to make. This requires huge amounts of data to help the machine recognize patterns from relevant inputs and outcomes.
These training algorithms are referred to as AI models.
The Prevalence of AI in Life and Healthcare Underwriting
In 2019, the Society of Actuaries conducted a survey of 28 major insurance companies. The study found that 100% of respondents used AI algorithms to underwrite life and health policies.
Underwriting is the process of rating specific risks to determine what an insured will pay for coverage.
Insurance companies assume the risks of individual insureds as part of a much larger risk pool. Pooling many similar risks together creates a group with predictable characteristics.
The cost of a loss within the group is absorbed by the premium income generated by the entire pool.
The better an insurance company’s ability to predict the likelihood of a specific loss, the better it can determine the appropriate cost to insure that loss.
AI can help insurance companies more accurately predict losses and price policies. It can help insurers determine which risks are acceptable and which they should avoid.
Each of these impacts profitability and is a reason insurers invest in AI.
According to a recent study conducted by Accenture, 65% of insurance companies surveyed said they plan to invest more than $10 million into AI over the next three years.
AI’s Impact on Cost Efficiency and Profit
The impact AI can have on an insurer’s profitability goes beyond improving the underwriting process. Global consulting firm, Deloitte, estimates that AI ”will increase labor productivity about 37% by 2025.”
For example, AI can identify customers at risk of canceling or lapsing coverage. It can prompt agents to talk with these customers proactively to reduce attrition rates. Doing this in a way that portrays greater empathy can be beneficial to an insurance company.
Accenture found that a third of all consumers surveyed who expressed dissatisfaction with recent claims experiences represent about $170 billion in renewal premiums that could migrate to other carriers.
AI can help agents boost goodwill, create stronger relationships between insurance companies and clients and improve profitability. Furthermore, there are also benefits for consumers.
The Benefits AI Offers Insurance Consumers
Consumers also benefit when insurance companies use AI to determine life expectancy and healthcare costs when underwriting policies. AI delivers ease and convenience to customers.
Management consultants, McKinsey & Company, expect that by 2030 the process of underwriting will be “reduced to a few seconds” as AI automates a process that currently takes up to 45 days.
They suggest this will allow insurance companies to quote policies in real time. Some of the related benefits to the consumer include:
- No physical exams
- No blood samples
- Faster underwriting decisions
- A less invasive process
- Cost reduction
- Ease of doing business
- Easy electronic filing
- Potentially more accurate underwriting
McKinsey believes that the result will also empower “consumers to make decisions about how their actions influence coverage, insurability, and price.”
This is because an AI-based underwriting process considers data one might not associate with life or health insurance, including:
- Prescription history
- DMV records (moving violations, reckless driving violations, DWI arrests)
- Felony charges or convictions
- Medical records
- Credit scores (past bankruptcies)
Since an AI algorithm is trained to identify recognizable patterns, it can furnish underwriters with probability models that establish connections between behaviors and favorable outcomes.
Obvious examples include a non-smoker who runs daily and works in a library compared to a heavy equipment operator who smokes. AI can also identify less obvious factors that affect life expectancy and potential health issues.
The use of this data may also create potential privacy issues or other risks.
The Potential Risks of AI to Consumers
Insurance companies must take care when using AI. Recognizing specific patterns may lead AI to create “learned” statistical biases.
Factoring in so much unrelated data may cause an AI model to reach a conclusion about a set of factors that is discriminatory. It could also suggest business practices that are predatory.
Increased digitization opens insurers up to new data for underwriting use, but also to more fraud. They will have to give careful attention to their data to prevent privacy and security concerns.
As with many aspects of investing, annuity investors and consumers shopping for health insurance should research providers and work with licensed financial professionals who can help them make the best decisions for their situation.
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