Waterlily, a startup that aims to predict long-term care needs using artificial intelligence, secured $7 million in seed funding.
The funding was led by John Kim, founding partner of Brewer Lane Ventures, with participation from Genworth, Nationwide, Edward Jones and others. Waterlily previously raised a $2.2 million pre-seed round. The funding will be used to grow the company’s platform and scale customized data-driven solutions.
Using personalized data and predictive algorithms, the platform generates a custom care plan, which can be analyzed against personal financial data, insurance coverage and healthcare trends to preserve family savings throughout the care journey, according to the company. It can also break down various financial products into simple terms to help families understand their potential cost and returns on investment.
Waterlily works with financial advisors and insurance carriers or distributors, with clients like Prudential and insurance wholesaler Financial Independence Group. Some consumers may also be eligible to access the product via Waterlily’s organizational partners, including several Fortune100 companies.
“Traditional financial planning tools have just not kept pace with the long-term care complexity and uncertainty out there,” Brewer Lane Ventures’ Kim said in a statement. “Waterlily is addressing one of the single most critical gaps in financial security and is well-positioned to help millions of families needing better tools to manage the financial challenges of aging.”
The round is unprecedented for long-term care startups, executives say.
“This space almost never receives funding,” Waterlily co-founder and CEO Lily Vittayarukskul told Fierce Healthcare. But given how many people are aging daily, the market opportunity is great, she added. “It’s a massively growing problem.”
Vittayarukskul, an aerospace engineer by trade, pivoted to med tech after her aunt was diagnosed with terminal cancer. Her family was torn apart by decisions over how to pay for and care for her. “It just financially devastated us. We didn’t realize how this really sits outside standard healthcare coverage,” Vittayarukskul said. Having a plan would have made all the difference, she added.
Just like Vittayarukskul and her family, millions of Americans are unprepared for the financial burden of such a journey, she argues. Many don’t realize that health insurance does not fully cover long-term care.
The platform works like this: An intake questionnaire compiles a family’s unique social needs and financial and medical information. It takes about three minutes to complete. Then, machine learning algorithms predict a user’s likelihood of needing long-term care, the age at which their needs will begin, how their needs will progress over what time period and how many hours or months of care family, caregivers or care facilities will provide.
Traditionally, financial advisers have to work off national averages instead of tailored data, Vittayarukskul said. Waterlily’s algorithm is based on half a billion data points collected from private, government, academic and provider sources. These data offer equal demographic representation across the U.S., which helps minimize bias in the algorithm, Vittayarukskul said.
The platform itself does not recommend anything, she stressed. It is intended to be an unbiased educational tool that financial professionals can use with their clients in long-term care planning. The company also engages consumers who sign up for its product online and asks whether they would like to connect with a financial adviser using their platform. Waterlily does not earn commissions or lead generation fees, per Vittayarukskul.
Though Waterlily is starting its work with the insurance industry, Vittayarukskul also hopes that down the line, the government will be more involved. Washington recently became the first state to offer a public health insurance option and a new employee-paid long-term care benefit.
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