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Where we share our weekly news debriefs and discussions with industry experts. These are lo-fi recordings aimed at giving our readers more opportunities to engage with our analysis and a view into some of the conversations that shape it.
Sean: Hey, guys.
How are you?
Kevin: Good.
How are you guys doing?
Sean: Doing well.
Doing well.
And you?
Kevin: No complaints.
Excited to dig into the ac-
actuarial infrastructure layer, guys.
Sean: Pretty, pretty, pretty sexy stuff.
Kevin: Would, would be very curious to
hear, uh, you know, the, but the behind
the scenes of developing the thesis.
Um, tell me how you guys
are looking at the space.
What led to the report?
Sure.
Um, key takeaways from your
perspective from the report for
folks who haven't fully dug in yet.
Sean: Yeah, yeah.
And maybe, uh, maybe just
quickly taking a step back.
So Emmet and I, uh, represent, uh, Virtue.
Uh, we are both a stage-focused,
early stage pre-seed, as well as
sector-focused healthcare, uh, uh, firm.
About five years old,
125, uh, under management.
Uh, we're typically first money into,
you know, the vast majority of our teams.
Uh, and currently, uh,
investment of our second fund.
Uh, and so, um, I would say, you know,
we're constantly sort of, you know,
building, uh, internally and pressure
testing, you know, various, uh, investment
theses that we can then go, uh, be able
to invest, uh, behind, uh, in market.
And, uh, we've been doing, uh,
we've been doing that for the
better part of the last five years.
Uh, I think we've done a, a somewhat
subpar job over the last couple of years
in terms of actually, you know, doing
anything in the form- Yeah ... of, you
know, marketing and brand development.
So starting to share, uh, you know,
maybe, um, you know, starting to
share some more views of the, of the
world and where we think, uh, you
know, the healthcare market is moving.
And so, um, one of the more recent
ones was this, um, you know,
underwriting, uh, um, piece.
Uh, new actuarial, actuarial
infrastructure layer is emerging.
Um, where the basic, you know,
simple thesis is that, uh, you know,
most healthcare risk, if not all,
is either, you know, mispriced or
unpriced, uh, just about everywhere.
Uh, and the incumbents themselves,
uh, structurally cannot fix, uh, these
problems, and it's not necessarily at
all because they lack the, the, the
technology, uh, and/or, you know, just
general technical capability, but it's,
um, simply due to the fact that, like,
their, uh, business models depend on
this, um, you know, mispricing or,
or lack, you know, o- o- of pricing.
And so, um, we've been, uh, investing
behind this theme over the better
part of the last couple years.
We're starting to see the need, uh,
for the ability to, uh, underwrite, uh,
uh, for different types of healthcare
risks with a high degree of precision,
uh, increasingly, um, important.
Um, and, um, yeah, so, uh, happy to- Yeah
you know, happy to sort of
unpack that, uh, a bit more so.
But, you know, companies that can
be able to quote a number, bear the
risk, stand behind their math, uh,
you know, that's where we see, um,
uh, real moats, uh, you know, today.
Um, where we see, you know, increasing
margin, um, across the bar- broader
sort of healthcare, uh, you know, sector
and landscape, uh, migrating towards.
Emre: Yeah.
Yeah.
And, and I'd add to, uh, to your
question, Kevin, I think there's Two
fundamental reasons in thinking behind
this that was really instigated by work
with some of our portfolio companies-
Yep ... namely RightWise, which we,
you know, talk about in the pharmacy
space as a whole, um, throughout that.
But yeah, the first is
we talk about risk a ton.
Um, you guys have done a great job
talking about risk adjustment, uh,
in the scheme of Medicare Advantage.
But fundamentally when we're talking
about healthcare, whether that is risk
adjustment, whether that's site of care
arbitrage, whether that's pharmacy, like
we wanna understand risk, predict, predict
that risk and tie it to an outcome.
And so with RightWise, with that
experience, kind of broadened our
view a little bit more, uh, of how we
think about underwriting, how we think
about this actuarial layer, uh, and
what that means, which we'll get into.
The second, which everyone's
talking about is really around
AI and like what's defensible.
So you see in there as well, we kind of go
through the simplified stack that we, we
lay out with underwriting on the bottom.
And so o- o- on the first, that's what I'd
mentioned, Kevin, as we, as we get into it
a little more specifically, like our, our
aperture and view of how we think about
risk is purposely broad as we go through.
Um, and then we lay out that
simple kind of three layer stack.
The first piece of that
stack being dashboards.
Think all the BI and business
intelligence, uh, that we are used to
seeing that now can be done easier,
uh, with tools like Texas SQL.
And we talk about workflow,
things that are actually
touching providers and patients.
Think prior auth, formula
design, step edits again in
that pharmacy, pharmacy world.
And then underwriting is a kind of
chassis, uh, underneath fueling all those.
So I think we, we see the success,
um, early success of companies in the
portfolio and then try and take that-
lens and never perfect pattern matching
with any of these companies in, in
new markets or, uh, within healthcare.
Um, but just taking those
lessons and drilling down deeper.
Martin: Yeah.
I'd love to start a little bit on
what's inside, uh, inside your, your
aperture or your frame of reference now.
You...
The nice table in the piece, which
we link to in the comments, um,
but who, who's doing interesting
work on this infrastructure layer
today, and are there any spaces
that you're seeing where you're...
it feels like there's some, some
ripeness for, for someone to
come in and, and be disruptive?
Sean: Yeah.
Um, I mean, we, we...
Like, the, the company...
So we, we see there, um, as being,
you know, plenty of opportunities
to better, uh, you know, reprice g-
you know, certain types of risk and
be able to take, you know, uh, and
then be able to, uh, you know, take
balance sheet risk off the back of.
Uh, you know, certainly, you know, from
our sake, having worked closely with
the team over at Brightwise over, you
know, these last couple years, we think
they're a sort of a shining example
of, uh, you know, of this thesis and,
you know, really, uh, you never wanna
project too much, uh, from one company,
uh, against the entire future market.
But we think, you know, uh, lays a
certain blueprint for a model and
framework, uh, that we can, uh, you
know, apply on a go-forward basis.
So Brightwise, check them out,
uh, really, really cool company.
Uh, so what they do, they're basically
repricing pharmacy claims at the, you
know, individual drug level, um, you know,
selling into employers, um, namely, you
know, self, uh, self-insured SMBs, uh,
and guaranteeing them a, you know, a, a,
a fixed, uh, a fixed, uh, you know, PMPM.
So what they can do is be able to
aggregate claims data across, you know,
many different, uh, sources, um, not
necessarily, uh, uh, data sources and
access that a single, uh, uh, PBM has.
Also, you know, these PBMs, uh,
typically, uh, don't have, uh, you
know, much of an incentive to be
able to, you know, share this data,
you know, with, uh, with each other.
Um, Brightwise is able to, you know,
use that data to be able to, uh, price
that pharmacy spend at the individual
drug level versus the, the group level,
uh, which makes their, uh, makes their
predictions, you know, far more precise
than, say, those legacy benchmarks, and
then, you know, thereafter able to, um,
you know, has the sort of operational
prowess, if you will, to then be able to
actively route those, uh, those patients,
those, um, um, employees to the, you know,
towards the, you know, clinically, uh,
equivalent lower net cost alternative,
which can keep that, you know, actual, you
know, spend, uh, uh, below what they were,
uh, uh, below the price they were quoting.
And so, um, we've- We've seen this
model work quite, quite well with
respect to, uh, you know, with respect
to RightWise early on sort of building
up the, you know, the data access and
aggregation, having a very sort of,
uh, you know, specific go-to-market
focus initially on this, um, you know,
SMB employer side where, you know,
the costs, uh, are really, you know,
becoming out of hand for these employers.
Um, how do we sort of rein in
the, uh, the both the medical
and drug benefits, uh, uh, costs?
They're mostly...
They are focused on pharmacy, as well
as, um, at least introducing the levers
to, uh, you know, have predictability
on, you know, uh, go-forward costs
over a, uh, twelve, twenty-four,
thirty-six month, uh, profile.
And so just firsthand, we've seen
the RightWise team, you know,
run this model very, very well.
Um, we think there is the ability
to sort of repeat this, whether
that's in, you know, um, areas like,
uh, you know, in ACO land, med mal.
I think the, the list of, you
know, potential opportunities is,
um, you know, uh, uh, aplenty.
Emre: Yeah.
And w- we keep emphasizing RightWise
and, and pharmacy here for good reason.
I would say there are...
You know, pharmacy is a market
where people aren't fundamentally
taking risk today, today.
Yeah.
Sorry.
There are other markets where people are
looking at risk and data that might be not
the right resolution or time, like we see
with ACOs and the, the lag of data there.
Um, so Sean touched on this, but one of
the emp- uh, one of the points about this
is when we walk through is when we...
how we think about data, right?
In, in RightWise's case, um, I
mean, if you think about this, it's
everything from kind of the social
data and things you might be able
to collect to the hardcore pharmacy
claims and, and underwriting there.
So y- you need to be operating in a space
where you think you can get unique access
to data, whether that's a function of
your relationships or go-to-market, or
other ways to actually deploy within a c-
in a customer, maybe using a workflow as
a dashboard as a way to go collect data.
And so some other areas that
Sean, uh, touched on, ACOs,
we're seeing some work there.
Um, you can even think about
maybe more specific specialties
or intervention, interventions.
You can even think about
a center of excellence for
surgery- Mm ... as an example.
If you are, right, you're, you're
doing site of care arbitrage
on, in ASC versus what it costs
in a, in a hospital outpatient
department or inpatient, for example.
If you are confident that you can use
tools like- Voice AI, for example, to
actually impact the patient workflow,
you can better understand how you price
and, uh, think about these 30, 60,
90-day bundles for that surgery episode.
So there's kind-- like, there's
this cycle as we think through those
layers where they, they compound.
There's a view on how we think
about what's differentiated, where
we invest, what the long-term value
creation of the company looks like.
Um, but there are, of course,
opportunities throughout.
So ACOs, med mal is an interesting one.
Again, that's more of the cherry-picking,
um, example where you can get into
individuals, you can get into states,
you can get to demographics and
specialties and really understand.
Um, and then other examples, um,
like centers of excellence around
surgery, where that's, again, a
very similar set of care arbitrage.
And then even just to emphasize for
the whole discussion here, like for,
for RightRise, R-RightRise today, we're
really talking about the pharmacy benefit.
Um, there's a whole another
unlock o-on the medical benefit
as we think through that.
Yeah.
Again, different data flows, different
incentives, different entities that you're
working with in the space, um, and then
different entities on the back end that
you need to understand and work with
to actually backstop that risk as well.
Yeah.
Kevin: I'd be curious, guys, Sean, I've
heard this a little bit from you in this
conversation about, um, go-to-market path,
uh, and small and medium sized SMBs as
the kind of customer base of these orgs.
Sean, going back to beginning of
conversation when you're like, you know,
the, the traditional entities can't
structurally move into this market,
I would imagine the, the, the sale
of these new actuarial capabilities
isn't to the BUCA plans, the large
institutions in the industry and the
SMBs how go-to-market would, um, would
take hold here, similar to how we've
seen it play out in AI tooling be adopted
by private practices cross-country.
I'd be curious how you guys think
about that go-to-market strategy as
part of the investment thesis here.
Are you looking at that SMB adoption
of new a-actuarial tools as a key
part of it, or how do you think about
Sean: it?
Hey, uh, we're still in healthcare, right?
So, you know, uh, go-to-market and
distribution oftentimes is, uh, you know,
just as important as the actual, uh, you
know, uh, product innovation, uh, itself.
So 100%, you know, this is something,
you know, we, we think about quite a bit
and what specifically like gives you,
uh, you know, your, um, edge, right?
So we focus on, you know, uh, seed
stage, that first 12, 24 months,
uh, be able to get the product
market fit effectively is everything
and, um- Hey, like, you're right.
Like, there is, um, there is certainly
an element of a effectively what is,
like, a cold start problem, you know,
here, uh, that you also ne-need to be
able to solve for and account for, uh,
in, you know, in order to get, you know,
any sort of, you know, initial market
share that you can build out the back of.
Um, you know, uh, so, uh, you know, I
think about, uh, RightWise, you know,
in this example, first and foremost,
uh, it didn't hurt that you had a,
you know, CEO sort of in place who,
um, has been, you know, building
companies at this intersection of,
you know, employer, broker, uh, you
know, a carrier for some point in time.
So really understand sort of like
this, uh, the nuances of this corner
of the market sort of in and out.
But I think, you know, from a, um,
go-to-market focus was very, you know,
specific and intentional early on, right?
So they, um, whether it is sort of
like picking, you know, one segment
of the market, um, there's being
that sort of like, you know, that
SMB, you know, self-insured employer,
self-insured versus fully, you know,
insured, so you just have more, um, uh,
information, demographic information
on those employees at your disposable,
uh, at, at, at, on, at your disposal.
Uh, you can focus on, like, a single
drug class or, you know, a select group
of, you know, drug class, a, a, a, a, a
single geography or, you know, small, uh,
short list and just dominate that very,
very specific, uh, you know, go-to-market
focus early on and then be able to expand.
Um, and then, you know, I think there
are also ways, uh, we think about sort of
like your ability to sort of like produce
and think about almost like a kind of
like a creative aggregation early on.
So, um, you know, building, uh,
RightWise, for instance, like building
data assets like the PBMs, um, either--
I don't, I wouldn't say couldn't, but
like again, from a structural, uh, you
know, business perspective, a models
perspective, uh, weren't, uh, they
weren't going to be able to share, you
know, with, with, with one another.
And so, um, you know, we saw that,
um, uh, you know, RightWise had a very
specific, you know, go-to-market focus,
um, on these, you know, SMB employers.
They were seeing, you know, their
costs like skyrocket year over year.
I mean, the same cost trends
that we've been seeing over the
last, you know, fifteen years are
certainly affecting that SMB market.
Um, you're starting to see the, uh, the
rise of, you know, things like GLPs, uh,
you know, affect, you know, thirty, forty
plus, you know, percent of these employee
populations where these, uh, you know,
these groups have, um, little to no sort
of like tooling or defense, uh, against.
And, you know, they're, they're
thinking about, uh, how do they, uh,
reduce costs as much from a, you know,
economics perspective as they are just
from a, a marketing re- uh, retention
to these, uh, to these employees.
And so, uh, they're looking for, you
know, this style of tooling, um, and,
um, have now a, you know, certain
economic need to be able to do so.
And so, um, I think go-to-market early
on- I mean, as I think, I mean, it is,
uh, you know, uh, crucial to, to be able
to, uh, you know, get right early on.
And I think that just requires a sort of
outsized focus versus this, you know, boil
the ocean, you know, style approach where
maybe you're trying to go from, you know,
SMBs all the way to, you know, jumbos.
I don't, I, I don't think that would make
a ton of sense or to do, uh, not just, you
know, pharmacy, but pharmacy and medical.
Uh, there are, you know, uh, reasons
why, you know, pharmacy we think is
a little bit cleaner, um, a little
bit more straightforward from a, uh,
predictability of sort of expected
utilization to spend off of these, uh, you
know, uh, off of, uh, these drug classes.
So, um, yeah, that, uh, early go-to-market
is, uh, absolutely crucial to have a sort
of honed in, you know, focus and, uh,
ability to execute, uh, execute off of.
Martin: If...
So we are at time.
If we are, if, if I'm an actuary with a,
a dream of a new, uh, uh, infrastructure
layer play, what's the best way for
me to get in contact with Virtu?
Sean: Uh, we're pretty easy.
I mean, you got the entire, uh, you know,
investment team on the line right now.
So whether it's, uh, ek@virtuvc.com
or sd@virtuvc.com,
um, you know, we take just about every
single pitch, uh, almost to a fault.
So we're more than
happy to jump on a call.
Um, I mean, we, we wanna, uh, we
wanna meet with some like creative
founders who are thinking about,
you know, these problems under-
underwrite off the back of.
Um, I mean, we could spend another
hour on this, which we won't do.
But I think also just, you know,
given where, uh, how AI is effectively
commoditizing, uh, sort of competing
away a lot of sort of, uh, prior
moats, uh, and, you know, uh, company
advantages and, you know, uh, forms of
defensibility, um, you know, we think
that sort of ac- actuar- actuarial, uh,
layer, uh, is one that, uh, at least
not in the sort of immediate or, you
know, medium term, is going to be, um,
you know, uh, sort of abstracted away.
And so, um, yeah, we wanna talk with,
uh, you know, uh, with smart folks
who are thinking about, um, you know,
underwriting certain types of risks
that we're probably not even thinking
about in a very creative manner and,
uh, we will take that call all day long.
Emre: All day.
Yeah, I'd love to see
more of those, Martin.
Uh- Yeah.
That would be a pleasant surprise
and a great start to the week.
So, uh- Yeah.
Definitely keep them coming.
And yeah, thanks, guys.
We'd love to continue, uh,
the conversation on, on
this and many more fronts.
And thanks for all you're doing here.
Martin: Yeah.
Sean: Yeah.
Really appreciate
Martin: the time, guys.
Great work
Sean: you guys are doing at HM.
See you
Martin: guys.
Thanks, guys.
See ya.