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The Ready.Set.Retire! Blog

  

The Retirement Success in Maine Podcast Ep 095: Can I Predict If I'll Need Long-Term Care Insurance?

Benjamin Smith, CFA

Executive Summary

Episode 95

When we sit down with our clients, one of the greatest fears in retirement is needing Long-Term Care services as we age. But our long-term care needs are often undefined. We don’t know how we’ll age. Some of us do know a bit about how our immediate family has aged and what their experience with long-term care has been, but is that relevant for us?

With our clients, we can roughly game plan whether our current retirement assets and savings might be enough to support one or two people’s long-term care needs. But it’s certainly a guess and it only discusses the financial component of long-term care. What about the burden on my family? What is their role going to be and how should they be involved in my aging process? Is it possible to strategize an Eldercare strategy for each of us individually? So, that is exactly what this show is about!

Our next guest spent 4 years specializing in molecular genetics and data science at UC Berkeley and did all things technical foundations, including biology, chemistry, physics, data science, computer science, statistics, and linear algebra. She has spent the last few years pushing for the early adoption of AI in biotech and healthcare. She is an Ex-NASA data scientist building the future of financial planning tools for eldercare using Artificial Intelligence. She’s the founder of Waterlily Planning, a software that leverages AI to help you personalize your long-term care plans. Please welcome Lily Vittayarukskul to The Retirement Success in Maine Podcast!

What You'll Learn In This Podcast Episode:

Chapters:

Welcome, Lily Vittayarukskul! [3:15]

How does the Waterlily software work? [10:46]

Examining Waterlily’s output, using Ben! [15:00]

Caregiving and Long-Term Care. [24:39]

What’s the future of Long-Term Care in the United States? [37:04]

What is a Successful Retirement to Lily? [47:34]

Episode conclusion. [50:46]

Resources:

Watch the Episode Here!

The Waterlily Blog!

More About Waterlily!

Our GPA Team!

Listen Here:

 

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Transcript:

Ben Smith:

Hello. Welcome, everybody, to the Retirement Success in Maine podcast. My name is Ben Smith. Allow me to introduce my co-hosts, the Timothy Berners-Lee and Neil deGrasse Tyson to my Bill Nye, Curtis Worcester and Austin Minor. How are you guys doing today?

Curtis Worcester:

Doing well. I think I'm worried here. We're getting a little smart with these names. I don't know what's coming here.

Austin Minor:

Exactly. I agree.

Ben Smith:

I think it'll be apparent to everybody. They'll go, at some point in the next minute or so, they'll go, "Okay, I get it. Yep. There it is."

Austin Minor:

Absolutely.

Ben Smith:

Of course, one of the things, when we sit down with many of our clients, we've been hearing obviously just not, they want to talk to people with intelligence, as we are, but not to that level, but one of their greatest fears in retirement is needing long-term care services as we age. I think the hard part is, as they're asking us is, "Hey, what's my long-term care need going to be?" We're not medical experts. We don't have the crystal ball to break out to know exactly what people's future is. We don't know when people are going to pass away. We don't know any of that, but we do know a little bit about maybe how our immediate family has aged.

We know what their experience with maybe long-term care has been. The question I think that gets asked to us is, is that relevant for me? As financial advisors, we spend some time with clients thinking through what that experience might've been. Using averages, we could estimate what a cost might be. Loss of personal independence due to care needs becomes more likely as you age, and with proper planning, long-term care can be a dignified experience free of burden for the individual, but also their loved ones. Just to give you some statistics about how widely, how important long-term care is, in the US alone, 70% of Americans are going to require long-term care. 91% of them are going to require their family members to step in and 54% will not be able to afford the $140,000 out-of-pocket costs to pay for the care they need.

With our clients, we can, again, as we said, we can roughly game plan whether our current retirement assets and savings might be enough to support one or two people's long-term care needs, but it's certainly a guess and it's somewhat rough, and it only discusses the financial component of long-term care. What about the burden on my family? What is their role going to be, and how should they be involved in my aging process? Is it possible to strategize an elder care strategy for each of us individually? That's exactly what our show is about today, strategizing my elder care journey.

Curtis Worcester:

That's right, Ben. Like all of our shows, we like to bring in a guest. Our guest today, our guest's parents came to the United States each without a penny to their name. Her dad came from Thailand, where his formerly wealthy family lost it all due to the war. Her mother came from Cambodia, narrowly escaping the Cambodian genocide as a child. Our guest personally grew up in a low socioeconomic community and has been privileged to have helped her parents rise to a middle class, through their entrepreneurial endeavors. Our guest has spent four years specializing in molecular genetics and data science at UC Berkeley and did all things technical foundations including biology, chemistry, physics, data science, computer science, statistics, and linear algebra.

Ben Smith:

As one does.

Curtis Worcester:

Yeah, exactly. She has spent the last few years pushing for the early adoption of AI in biotech and healthcare. Again, our guest today is an ex-NASA data scientist building the future of financial planning tools for elder care using artificial intelligence, or again, AI. She is the founder of Waterlily Planning, a software that leverages AI to help you personalize your long-term care plans. With that, please welcome Lily Vittayarukskul to the Retirement Success in Maine podcast. Lily, thank you so much for coming on our show today.

Lily Vittayarukskul:

Awesome. Thank you for having me.

Ben Smith:

Lily, of course, with all of our shows, we want to hear a little bit about you and get to know you a little bit first, so want to just hear a little bit about your parents' journey and how that influenced your life and your academic pursuits, and why data science?

Lily Vittayarukskul:

These are really good questions. I'll share a little bit more that you probably can't see online or read online, which is, my dad actually never had an opportunity to pursue higher education. Instead, he actually ended up working day and nights with the smaller businesses that he built together with my mom in order to get my mom through her higher education. My mom ended up getting a master's in business. That opened up a lot of opportunities to pursue bigger, more strategic business opportunities and really opened my eyes to how the right educational path leads to the right career path that could lead to more stable wealth. Seeing that progression of going from in poverty to having more stable wealth was really eye-opening to me. I know that made me realize that I didn't want to pursue education for the sake of pursuing education, but actually, as a way to optimize the career path that I wanted to build for myself.

I wasn't interested in data science, actually by itself. It was only in context of another field that I was already fascinated by, which is genetics. The difficult thing about genetics, before we had 23andMe and whatnot, is that it relied a lot on archaic algorithms that no one understood. We were just taught to memorize these really complex algorithms to solve for this use case in genetics. At the same time that I was studying genetics is when data science opened up for the first time to undergrads at Berkeley. I just saw this huge opportunity to leverage that big data approach to data science, to genetics.

Austin Minor:

That is very cool and very excited to talk to you today. This is really neat stuff. What I wanted to ask you is, how did your data science background, artificial intelligence and long-term care turn into a business for you?

Lily Vittayarukskul:

I was actually fast-tracked as a young kid into aerospace engineering. I did not at all build this career path. I think things just happen to you. Life just happens. When I was doing my internship at JPL, the robotics side of NASA when I was a teenager, that's when something happened in my family where one of my immediate family members was diagnosed with cancer. For a little over two years, we had to navigate our own long-term care event where we saw her health drastically decrease. Her room, we had a two-story house, we had to move her room to the first floor.

Just all the aspects of taking care of her physically, emotionally, and the financial surprises mimicked a lot of the same devastating effects of families caring for aging loved ones, like our aging parents. That made me pivot my career from aerospace into healthcare. I kept my technical background in machine learning and AI, pursued that for a little over a decade in the healthcare industry. I realized that it's been a little over a decade later and not much has changed for families on this topic, and no one was really looking at it from that more empathetic view.

Curtis Worcester:

I appreciate that insight and background. I want to fast-forward to today and Waterlily. Can you just walk us through Waterlily? How does your software generally work and what are the plans for you in the future with it?

Lily Vittayarukskul:

An advisor or an advisor's client today could actually fill out an intake form where we ask a little over two dozen questions about the client. We ask basic demographic questions, basic health, basic financial. In about one or two seconds, we actually take that data and run them through our AI models to build out these onboarding slides for a client that an advisor can present that essentially tells the client their long-term care story, specifically the cost and care trajectory if and when they were to need long-term care.

Curtis Worcester:

Wow.

Ben Smith:

Lily, I know we're going to go into a lot of things in what your software is doing and what it's working on, and really, the subject of our show today is strategizing our elder care journey. Obviously, our team has been beta testing that software. We've been going through it. It is completely fascinating. We are really shell-shocked with how much it can transform a lot of these conversations that we're having with our clients today or even the conversations we've been having on this show. At this point, we're episode, I think in the mid-90s here. Let's start with some foundational items here. What are some key motivating factors for engaging in long-term care planning?

Lily Vittayarukskul:

Long-term care is an extremely common event in retirement; extremely expensive and often burdens children and spouses extensively. What's surprising is that paying more for long-term care today is not necessarily equated to having higher quality of care. If you start planning today, the gist of it is that you actually get a shot of changing those negative outcomes, any of those negative outcomes with our software.

Ben Smith:

Gotcha. One thing to be clear is, this isn't the Trojan horse software to then sell long-term care insurance through Waterlily, right?

Lily Vittayarukskul:

I usually joke sometimes, but I'll just be very clear so it doesn't get used, because we don't sell any insurance product on our platform and we don't plan to sell any insurance products.

Austin Minor:

Awesome. I'm really fascinated to learn more about the data process here. When we're dealing with clients, it can be a tough thing to talk about, because there's so many different variables. Your website talks about using over 500 million data points, I believe. How are you able to draw conclusions from quantitative and qualitative data to create relevant output for end users?

Lily Vittayarukskul:

I think that's such a great question. It helps to contextualize the data a little bit more, which is, those half a billion data points actually refer to individuals that we're currently tracking in retirement today or who have recently passed in retirement. We know essentially their entire retirement picture, but we mostly focus on if they went through a long-term care event. We have the level of detail of which daughter stepped in for how many hours, for what physical limitations, and during this time, did they also experience additional hospitalization or nursing home visits, and how did those care needs progress over time? In other words, we followed that entire multi-year story for almost 50,000 lives and we have equal representation of demographics across the US in order to minimize bias in our algorithms.

Austin Minor:

Okay. Interesting. You said you follow real life situations and you're mapping that for data?

Lily Vittayarukskul:

Yes.

Austin Minor:

How do you ensure that your data is relevant and up to date as time goes along?

Lily Vittayarukskul:

For what it's worth, we don't go and gather this data ourselves from the population directly. We don't create the surveys and we don't have APIs directly to these individuals. We actually have both public and private access to academic institutional data as well as government institutional data, and we stitch that all together to essentially build out up to 20 years worth of data on any one life that we have. Those data sources are actively getting updated multiple times every year, actually, so we're always improving that and we're always gathering new data sources today, especially with our upcoming pilots with some enterprises to further build out the fidelity of our data sources.

Curtis Worcester:

I love that, Lily. You just teed up my next question perfectly. I really want to get to the output here where you're gathering the data, the data's up to date. You have all these sources, all the different data points. I want to know how you're actually able to identify unique costs that then can be personalized for each user. We all live in different places. We all have different challenges. For example, how are you able to predict that maybe it'll cost me $55,000 annually for in-home caregivers or then another $1,500 for medical equipment, or maybe $7,000 for installation of shower grab bars? This is the output we're getting. Can you speak to how that's happening and how it's accurate?

Lily Vittayarukskul:

I'll share first off the potential of our data, which is, we have a massive amount of historical data across home care versus institutional care. What are even healthcare costs, and being able to tease that away from long-term care costs, and associate that with conditions of a particular individual in their care journey. Where we particularly focus on today is specializing in care hours and separating family care hours versus professional care hours. We also ask in our intake form, "Hey, what is your zip code?"

Knowing where you live has a drastic effect on what that cost of getting those caregiving hours done, important as well as what's subsidized by family members, but also, what care environment are you going to be in as you have growing care needs over time. Whether you choose a facility or aging at home and the design of that also drastically affects your cost. We gather all your facts and your preferences in that intake form to be able to make, essentially, the projections of where are you likely going to live, how are family members going to step in, for how much, and how much care hours are you going to have over your long-term care event, which all contributes to cost?

Ben Smith:

Lily, I think just helpful to maybe give an example. In terms of just picking on myself here a little bit, I, of course, went in and used myself as, go in and create, go through the survey, answer about things about my family and my history and current family relationships. Again, I know there's still a little beta mode happening here, so anything I say, I just want to say is, this is just what we're working on today, and we're still there, but let's assume Waterlily is in its final form. I've gone through the onboarding process and the survey. After that, here's some of the output I got, just so people can hear this as an example, I think is helpful. Waterlily assumes that I'm going to need 9,144 hours of care, and the net cost of care is going to be $67,710.

The prediction is that I'm 49% likely to need long-term care and there's confidence levels that you're giving there, so it's 71% confidence of that being the number, and that I'll likely need long-term care at 81 years of age, and that's a 73% confidence. Again, 9100 hours of care of the span of six years. Again, highly confident in that, 76%. What's simply amazing is that you've gone further than just going, here's a number, here's a dollar amount, save to it, which I feel like, as financial advisors, is what we have. There are some averages and estimates and those sorts of things. You've now gone further than just, here's some hours, here's some dollars, but you've then mapped out my family's investment in my care, so you're showing that professional services of the 9100 hours, that I'm going to need 3500 hours of professional care.

My wife is going to provide me about 3500 hours. I'm not going to tell her that part yet. My son's going to provide 1800 hours and other family's going to chip in for another 257 hours. What's really cool about that is then the next step is, then we go answer questions about my wife and my son and my other family. Geez, maybe my wife is debilitated. Maybe she's a quadriplegic and she can't take care of me, so then I can allocate hours to, let's insert another family member or another friend, so we can then start mapping out not just the cost, but it could be, hey, here's how we go through that. Talk to us about mapping out those family roles and how you created Waterlily and why that's important to truly get an accurate picture of our personal care.

Lily Vittayarukskul:

Simply put, it goes back to the data and just how much it lays out that work for us, which is, if we know which daughter stepped in for this particular household who had these demographic information and had these diagnoses associated with them, then what we're essentially doing is, we're mapping you to historical lives that we've had that look like you and that look like your family structure, and how did they go through long-term care, and how did family members step in? We took all those lives that looked most like you, and then we built that regression into the average of, what is the most likely proportion of hours that your spouse is going to take on or your children or other family members versus a professional?

Simply put, we're not making our own fancy algorithm of building this growth rate of family involvement, but actually the way to explain it to clients is, we're just mapping you as close as possible to other people that look like you and they've already gone through this. This gets really interesting because what we've done is, we've opened up some insights that you've never had before. It's an interesting psychological experiment because now, how does that affect your intention with how you want to go about aging or who do you want to involve? I think it looks different to just let it happen to you versus you now know what's going to happen and you probably have a opinion on what you want to change about it as well.

Ben Smith:

Yeah, Lily, I'll just follow that up is, I thought the fascinating insight is not that you're just doing data and then just saying, "Okay, this is likely your experience in terms of financial," which I think is the default mode of us as financial advisors is, we only care about the money, so here's the money and here's how much you have. Let's get the overall out of pocket cost out of this.

Now we can work on it and we can build around it and we can talk through it, where going that extra step of, we've really got to talk about aging process just generally with your entire dynamic because all of a sudden, if somebody can't step in or things are changing in your family over time of, hey, this might shift more costs or less costs here in how you're cared for, so it's going to impact the financial part. I thought that was really brilliantly done about inserting that family dynamic and mapping that relationship out. We're just going to get more accuracy with our clients because of that. It's just a highlight. I just wanted the insight. Maybe not a question, but just something that I thought was well done.

Lily Vittayarukskul:

No, I appreciate it. I think it's pretty profound how you encapsulated that by yourself about, "Wait, Lily, there's all these variables that affect cost, but these are actually much more profound relational conversations to be had with the client as well. That just makes doing our job better or more effective."

Ben Smith:

I think what we're seeing is, it's a very natural thing, I think, for people to talk about from an estate planning perspective. They go, "Okay, when I die, here's the natural power of attorney and executors of my estate." There's, "I can't have this person do this because they're probably not likely to be more inclined to do it." We've got to think about the relationships of people. I think we're more okay talking about, I want things to happen a certain way when I pass, but we're less likely to talk about how we want things to happen as we age and we maybe lose capacity. It just seems like a weird conversational conflict that happens there.

Lily Vittayarukskul:

I think, to be honest, this probably goes to my personal philosophy on this topic. The more fundamental psychological question to solve is just, aging is actually really scary. I think the scary part is the fact that we've associated our sense of identity with being able-bodied and being able to do a lot of things by ourselves as an independent person. During that time, we define who we are by ourselves and build our own families. Once we lose that physical ability or even cognitive ability, do we still now know who we are? I think a part of solving this problem is being able to look at our trajectory and start to build out more resiliency about who we are outside of our physical capabilities. I think that'll make us be more effective and satisfied with the decisions that we make.

Austin Minor:

Yeah, I definitely agree with that. I think it's nice for people to have a tool to use to actually enact that as well because I think it's something where they feel like they hit a dead end a lot of times. Going back to using Ben as an example here a little bit further, just to help our listeners understand how dynamic the process is here, using Ben as the example, what happens if, say, his son gets married and he now has grandkids that he's close to that would chip in for care, or what about the opposite? How would you map it out if family moves away or Ben and his wife retire away from their family? What would that look like?

Lily Vittayarukskul:

The really cool thing is that this isn't a one and done situation where if Ben mapped out his trajectory today, his snapshot, we actually do ask on a yearly basis if you could just double check your data to see if anything major has changed because if not, you're now a year later and you're still in the state. That's information to us that may help us build a more accurate snapshot of what your projection is going to look like.

If something changes where we now have a particular grandson of interest that wants to step in more, or the daughter who was going to be the secondary caregiver, that was going to devote 2000 hours, she now is living much farther away and her personality is such that it's not obvious to us that she would move closer if your need were to arise, so we want to remove her from the picture and recognize, okay, maybe we're covering that gap with grandchildren that we're really close to, at least to the best of my knowledge. I think that's the best we could do is take into account how the most dynamic thing is our relationships. How are our relationships changing over time, and how does that change my care plan and my financial plan?

Curtis Worcester:

I love that. As you were explaining that, Lily, I couldn't help but think about our roles here, myself, Ben and Austin. When we have these conversations with clients, all I was hearing was how important it is to stay accurate and up to date. We can map out these financial plans for someone and in five years, a lot can change. It's very important that this is just an ongoing part of your planning process, so I really appreciate that.

I want to keep going a step further here. I know part of Ben's example there involved family and caregiving. On a previous show or episode of our show, we had a guest on by the name of Iris Waichler. She was a caregiving expert. We talked with her about really the emotional weight of taking care of our family. The three of us, Ben, myself and Austin, we're located in the state of Maine. Actually, in the state of Maine, family caregivers were actually reimbursed for up to $2,000 annually.

That's part of a program called Respite for ME, Maine, ME. We have a link to an article of Forbes there that we can probably put in our show notes talking about that program. Essentially, these family members can get a bit of help with the money. With current demographics, obviously, here in the state of Maine, there are many aging members of our communities that need support. What I'm getting to, Lily, as a question for you, can our family structures how they are today continue to support our aging population, do you think? I know that's a loaded question.

Lily Vittayarukskul:

I would say that family involvement, I think we're only going to receive more and more pressure to have that be inevitable in our care plan because just of limitations in our healthcare system and how many people could actually help out. The hard part is, I think we have a pressure more now than ever before, with the strained healthcare system and long-term care systems, whether it's government or private, we feel this pressure to step in, but our workforce doesn't look the same as it did before where previously, it was optional for, let's just say a nuclear traditional family, for the wife to have to work.

Because of economic conditions today, in order to survive, essentially, we have to have a dual income household. Now you have a lot of women entering into the workforce now more than ever before as a requirement, but they still have to take on the caregiving duties of, if they raise, having children, raising those children, trying to grow in their career in order to earn enough, but then all of a sudden, we have aging parents right around the corner that we have to take care of.

Curtis Worcester:

Exactly.

Lily Vittayarukskul:

I think that for traditional caregiving structures in the household, I think a lot of women are still very much going to feel the pressure to have to take care of our in-laws or our own parents and reconcile that with, how am I going to financially be okay as well? That's the tricky problem we have at hand.

Ben Smith:

Lily, I know obviously caregiving is such a big thing. You raise just a really great point that basically, some of the deficiencies in the healthcare system, it just falls to our family members and community members to step up and help out. Somebody has to do these things, and there's people that need care, these people that we love and we want to take care of. We want to help out and we don't want to see them struggle. One thing that, we had an episode way back, it feels like at this point, 60 episodes ago, Dr. Sarah Zeff Geber, we talked about solo aging. There's a growing population of people, they've been married but they don't have any kids, so they've taken care of their parents, but they go, "Who's going to take care of me?"

She really talked about that that was a really big concern for her in solo agers was, to what you just raised as a point of, it falls on people in my network to take care of me as I age, as I'm not able to do so, but I don't have family to then rely on at all. I have to then reinvent my network over time and continue to reinvent in future generations of friends to ask them to help out and advocate for me, because no one else is able to do it. My question is, how would you think about Waterlily here and your software counseling? Again, our roles as advisors using this software to counsel that population to think about their long-term care needs if they don't have family to assist them?

Lily Vittayarukskul:

In terms of immediate family members, we definitely take that into account. In the initial intake form, we ask if you have a spouse or a partner and if you have children. If you respond no to any of those, we actually pull that into our predictions of, what are similar client profiles such as yours where they also did not have a spouse or a partner and they did not have children. What we map out in your family or in your support structure, then, for any family involvement, is that a smaller subset would then just fall on other family members. This could be a younger brother. It could be your niece, your nephew. I don't want to discount the fact that there are sometimes family members that you aren't just your traditional immediate family. We encompass that in other family members.

Then you're right, a large portion of that ends up falling on professional care services, so we show that. We show how much of those care hours get shifted to professional caregiving, which also then automatically is associated with higher cost of care. I think also, I'll share an example. My partner's grandma, which I have a really great relationship with her and I really love her, she is widowed and what she'd done is, I think where I see a lot of single individuals going, which is, she lives in a community, actually, and you're right. She's built out all of her friendships over time where she's in her 80s. She has friends who are 90s or in their 70s and they're all very close-knit with each other. They have book club and they look out for one another. If one of them's really depressed, she's going to go to their door and bake, give her some pastries or cookies and check in on her.

I think that that's such a wonderful form of support, actually, in the communities. You actually all live together. My partner's grandma, she's also actively put together her care plan. I already have, these are my advanced directives and I started looking into independent living or assisted living. That could also cover nursing home and this is what I'm looking for. She actively has those conversations as well and she lets everyone around her know, "These are my wishes and these are my preferences. I want to go to this specific facility." It's that level of direction that not only gets really precise about what the costs are going to be, but also, we get really confident about, what are her supports in place? She's designed that. That's just separate from our predictions. It's just, how do you go about building your care plan after those predictions to just make more educated and informed decisions?

Ben Smith:

That brings up a really important point. I think about our financial planning process and just using this as a parallel to it, to say, as we're going down a road with somebody and we're 20 years in and we can go, "Geez, this is what we spent and this is where we are and this is where we have left to go." I'm just thinking about that of, my father-in-law just had a medical event, ended up in the hospital and got care. He's seen good recovery. Everything's going to be fine, but I'm just thinking about, say we sit down with him as a client and we go, "Okay," we update maybe those events to you. How would that change?

We did the initial onboarding. We go, the client's had a medical event, and they no longer have an organ or whatever happened there. Is that going to change? If we're updating this continually with you and we're going with Waterlily, is that going to then go, okay, then based on this, we had confidence you were going to have 9,000 hours of long-term care, but now based on this knowledge, more than likely, you're going to need 12,000 or 5,000. How does that change over time, in terms of the client journey?

Lily Vittayarukskul:

In a nutshell, it's similar to just what your new snapshot of what your health looks like. We then look at people who look like you that went through those diagnoses and also those events as well, and how did their long-term care event play out? We have so many lives in our data center and it's only growing, that's just building our confidence on, this is how it's going to change what the projected long-term care event's going to look like for you. You're right. It might actually mean 5,000 hours because it looks like you are going through these acute things faster than we expected, which might mean accelerating through having more and more care needs faster or it might actually mean that, hey, we noticed that someone, when they had an initial scare or surgery in their 50s or 60s, all of a sudden, they did certain things to make themselves more stable and healthier.

Then health is more top of mind for them now. That means they have better behaviors. There's all these subtleties that we try to capture in the intake form. That's why we don't just ask, tell us your health condition. Okay, here's your outcome. It's more about who do we think, who are you? Who are you really, both just externally how you identify things that you've been through, your financial picture, which gives us a sense of your socioeconomic status, and what region to really try our best at understanding the unique predictive variables about you, and try to give you that as insights. I don't know if that was a clear answer.

Ben Smith:

No, I think it is because I think where we're trying to go is, hey, we're on a path. Again, we're strategizing the journey. We're not just strategizing the first step. Hey, we're 88 and here, we're having acute medical issues very routinely. What does it look like for me going forward? Maybe based on where I am, it's just helpful to then understand this in terms of a) affordability, but also my care plan and who's available to me, because what if my spouse has predeceased me at this stage, and now I was planning on that role, that caregiver giving me those hours and now that's not there, and I have to readjust the whole thing. Maybe people aren't as you said before, maybe people can't do those roles. It's just re-strategizing continually is what I'm hearing you say.

Lily Vittayarukskul:

Exactly. I think we're actively getting more information on this right now where we have upcoming pilots next quarter where it's actually focused on populations that are going through care right now and how could they potentially use our software to re-strategize how they're leveraging their financial resources? How are they leveraging their current upfront family caregiving resources versus how can we spread that over time, or how can we recognize, wait, if the daughter's going to spend 5,000 hours on my care, that seems like too much for her, and she's also verbally saying, "This is too much for me," then we can use our caregiver assessment of just saying, objectively, who else in the family should we identify as potential caregivers? Let's go through the assessments and figure out whether or not they'd even be a good fit to then have a conversation about spreading those family caregiving hours amongst more individuals.

We're in a really interesting time in which, if we tell someone their projections, how is that going to illuminate back to us what someone's preferences are, what someone's motivations are and their psychological profile? I think that'll further help us better guide more precise projections of, we think you want to actually go in this direction versus this other direction. Is that true? Things like that.

Austin Minor:

That makes a lot of sense. I wanted to zoom back out a little bit. Obviously, there's a huge, I love this software, by the way. I think it's such a useful tool for so many different age ranges. Obviously, the focus turns towards long-term care as you're 50, 60, 70, aging, but I think as we saw with Ben's example, it's a really valuable thing for younger people to be utilizing as well. With that being said, we're looking at the future of long-term care specifically in the US. How do you see the future of long-term care evolving, and are other countries models influencing how the US is caring for its citizens?

Lily Vittayarukskul:

That's a really fascinating question. I will share. The aging innovation landscape is drastically changing right now. For what it's worth, I think government is stepping in more now than it ever has been before into making sure that the population is prepared for long-term care. For example, there's a lot of state mandates that are slowly unrolling with Washington starting first and requiring either you pay a payroll tax or you purchase a form of long-term care coverage. There's some caveats on implementation, of course, but California's [inaudible 00:38:22] that and there's a few other states where it's going to be a mandate to actually have some level of coverage to ensure that financially, we're somehow getting prepared for that. I don't have an opinion on if it's going to be beneficial or not. I think it's always based off of execution.

There's also, across each state, we know we have our Medicaid programs as well and our Medicare Advantage programs where there is now this stronger emphasis on LTSS, which is the long-term care support systems. They're actually coming up with the program you just talked, that was just shared about, in our particular state, family caregivers are actually getting compensated by Maine to take care of aging family members. I think innovative measures like those are only going to increase today from the state. They're actively looking for ways to better manage the aging population.

From a private industry standpoint, I speak to a lot of founders like myself who are in the elder care space or in the elder care financial services space. We recently had a fascinating conversation that was organized by one of my investors. He asked, outside of what you're doing, just if you had unlimited time and money in the world, what would you work on for this space? The most interesting answers were people that said, I want to build communities that mimic Blue Zones across the world.

More specifically, really focusing on a sense of community, reducing loneliness, eating better, factors that we've seen across the world where people are living a lot longer than our average life expectancy, up to what we call the centenarians. I might be pronouncing that wrong, but people who live above 100, what are they doing across the world that allows them to live to 100? A lot of us entrepreneurs are really fascinated by that, and we're trying to see how can we build, mimic that Blue Zone as a way of promoting not just extending up to 100, but also creating higher quality of life at the same time. I see all sorts of ideas more in spirit of a Blue Zone.

Ben Smith:

Lily, that's really fascinating because MIT AgeLab, I know they have their own research that they're having. We had a gentleman come on from Hartford Funds and they have a good partnership with MIT AgeLab. That's what we were talking about was not necessarily Blue Zones, but they're saying how, really, a lot of successful folks as they age, that they were really being successful around college campuses, because you get multi-generational populations there. It's not just, here's my gated retirement community and we're all the same age and we all age together and we reinvest in other people that are of similar ilks.

No, when there's activity, usually, there's things like sports or academic things or theater or there's things to do and there's free access to healthcare, typically, or there's access to healthcare, typically. There's access to athleticism and gyms and things like that, and I can go on walking trails and tracks and things. That was a takeaway that we thought was pretty fascinating. It was like, hey, that actually was attracting more. You think it was attracting college students. It was attracting retirees as a fascinating thing.

Lily, I want to ask another question here. I know it's a little impromptu, but we talk a lot about the journey. I know for us as advisors, I know we're interacting with your software here. The question I think that then is being asked of us, I thought I'd just ask you a similar question then is, okay, the question's being asked of us from our clients. Okay, then if I know how many hours and I know what the investment on my family is going to be, how should I pay for these services is a question, right? You talked about Medicare Advantage. You talked about Medicaid. Obviously, there's long-term care insurance. We joked about you're not selling and neither are we, but there's lots of different ways for either out of pocket to all these different avenues here. I just want to get your take on that. Not going into anything specific, but just generally, how you'd want the advisor community like us to interact with your software to then make those recommendations.

Lily Vittayarukskul:

We're actually in the midst of developing this internally, which is more the financial planning aspects of the software. I'm really glad that you all find the current software useful. We're massively improving it right now to solve for a lot of the advisors' key pain points where the first one is, okay, if I know the cost and the client's just like, what are we going to do about that? The main pain point is, the client does not, they're having trouble. They oftentimes have trouble understanding, what is the difference between self-funding, partially insuring or fully insuring, just as three fundamental concepts, and get them to make a decision on one concept to go with. The way we solve for that is, we've actually built out this financial calculator that, once you know what that cost is going to be, we then have these basic, basic fields, and I'd love to get your feedback on it, probably at another time.

Basic, basic fields around self-funding of just, how much have you set aside for long-term care today? The advisor gets to decide, what is that ARR on self-funding vehicles, whatever you want to put in here. Then we tell you. We just calculate, what is the expected monthly contribution over the period of time up until their care age, that they're going to need to put in to cover their cost of care at the age in which they're going to start needing care? We then calculate, what is that total principal investment that you're going to be making? That's a dollar amount to focus on, which is, how much are you going to invest today? Then if you added a policy of any sort, I don't care if it's life with a rider or hybrid or traditional, we just ask basically, what is that total benefit amount, and what is that monthly contribution rate?

Then we understand, okay, if the coverage is $350 and your long-term care is going to cost $700K, we just automatically cover the rest through the self-funding, and we show you the new principal total investment. All a client needs to understand is, how does your principal change as you consider different methods? The advisor could potentially talk to them about, outside of the quantitative number, what is the qualitative differences of going with one versus the other, which I can't speak to, but someone might prefer to be more liquid today than later on or things that you could talk to them about, but we focus on one single number to simplify that financial story so that they could decide, I'd prefer to be more liquid today. I think a partial insuring route generally makes most sense. That, I think, will take an advisor so much farther than they are today, which immediately, the only solutions are, here are these policies. Here's the illustration for them, which are very hard to understand.

Where we're going past from there is okay, we helped an advisor potentially help a client make a decision today on what method, but a client might still say, "Okay, great, I'm going to partial insure, but I'm going to wait five years. I'm going to wait ten years. We're on the same page. I just want to focus on this later." We actually have a toggle for the time value of money where we said, "Okay, if you want to start five years from now or ten years from now, how does that change the total principal you need to invest if you start it at ten?" It's drastically higher, and people don't recognize that. We're just building the visualizations of calculators that already exist so that the advisor can solve for, the client wants to make a financial decision now and they know the type of financial decision. Now it's just on the advisor on what specific individual [inaudible 00:46:29] do you now pick to align with that strategy?

In our new form of our client profile, we're actually opening up the dynamic expense graph and we're allowing you to put in individual vehicles so that if you put in a policy, it might have a max benefit amount of $250 a day. We could tell you through the expense graph that, hey, it's going to cover up to these four years out of these six years and then you have this extra gap of, we're maxed out at this max daily coverage and we've taken into account your overall max benefit. You haven't hit it yet. The rest of that, how does that get covered through some self-funding vehicles?

Curtis Worcester:

I'm going to go ahead and just pull up my calendar so we can book another episode of this show when that calculator's out and we can go through it with everyone. I think speaking for Ben and Austin, that just sounds incredible and I think, something that's would be incredibly useful. Lily, I want to just take a second. We've reached the end of our conversation, so I first just want to thank you again for coming on our show, sharing your expertise, sharing your software with us, letting us dive into it and really show people what's out there. I do have one final question for you. I hope you've got your crystal ball out, if you will. The name of our show, the Retirement Success in Maine podcast, we like to ask all of our guests, how are you personally going to find or define your personal retirement success?

Lily Vittayarukskul:

How am I going to define or find?

Curtis Worcester:

Either one, right? What do you see as being a successful retirement for yourself?

Lily Vittayarukskul:

I honestly think it's an active learning journey to define what my personal retirement success is going to look like. I think I'm learning it's going to change as I learn so much from talking to advisors like yourself, following your podcasts where there's just all these new concepts of setting up your goals for retirement or what are some important financial strategies that you should be aware of? I think we're now in this era of technology and access to information where I think I just want to use that to better consult with financial professionals about, what should I do next? It shouldn't just be them telling me what to do, but I think we're now in an era of, how can I get empowered with the topics to then want to bring up with any financial professionals or for me to do myself?

I think that's how I would find personal retirement success is actively learning and finding the right influencers in this space that know what they're talking about, are always trying to learn themselves. I think that's a really nice way to stay on top of our method. In defining it, I think that's just, I love that you have conversations with your clients, because I think it really is all about just having a really good sense of who I am, what are my values and recalibrating financially. Do I have enough for my goals, actually, in retirement? I think that's going to change. I should have them today so that I could know how to invest appropriately but then ten years from now, it's probably going to change. As I mentioned, it's better to make financial decisions today to the best of your ability versus waiting five or ten years out, because that could be so much more expensive to do and way less affordable, actually.

Curtis Worcester:

Absolutely.

Ben Smith:

Lily, thank you so much for coming on our show. This is a lot of fun. I know you're well on your journey in terms of, you're shaping the financial services industry. We thank you for that. You're shaping not only us, but our careers and our clients, so keep going. We're cheering for you. We want your company be a success. Keep us in the loop, but thank you so much for coming on our show.

Lily Vittayarukskul:

Yeah, of course. This has been a pleasure. Ben, Austin, Curtis, it was a pleasure to meet you all and wonderful questions as well. I think that if I was a new person listening and I was just like, wow, these are really insightful to just get that precursor into the space. Also, I love, it also shows me just how much you all care about being on top of your financial planning game. It's been amazing.

Curtis Worcester:

Appreciate it. Thank you.

Ben Smith:

Yeah, thank you. Appreciate it, Lily.

Austin Minor:

Thank you.

Ben Smith:

Be well. I can say we had a lot of fun talking to Lily Vittayarukskul today. Just talking about her background, you can tell just the intelligence coming through obviously, in what she knows about the space. Basically, you're just a NASA scientist as a teenager, right? I can't put that on my resume.

Curtis Worcester:

Yeah. I wanted to dive in on that for a minute, too, by the way. We might have to have her back because she quickly threw in that she interned for NASA as a teenager.

Ben Smith:

Yeah. I was just working for NASA just in my teens.

Austin Minor:

No big deal.

Ben Smith:

I can say I wasn't a NASA scientist as a teenager.

Austin Minor:

I was not. Exactly. Nope.

Ben Smith:

Yeah, just very impressive of a background, impressive what she's working on today. You can just tell she has a lot of momentum behind her in making an impact in this long-term care space. I know that's just an area that, it's going to impact all of us. As we talked in our intro, it's just a large percentage of us are going to be in that position. Here's somebody that's coming up with a really great way to plan for those events and helping our advisory committee on trying to create solutions. We are going to have, actually, some more information about Lily and her company, Waterlily, on our website, so you can go to blog.guidancepointllc.com/95 for episode 95, find some more information there, have our transcript and some links to the show. We really appreciate everybody tuning in. I know we went a little technical here and there, but thanks to you all for tuning in and staying with us, and we'll see you on episode 96.

Topics: Pre-Retirement, In Retirement, Podcast