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The American Academy of Actuaries: Shaping Insurance's Future · Look Forward

• 0:06
  Hello, my name's Andy Critchlow.
• 0:07
  I'm head of news at S&P Global Commodity Insights, and welcome to the
• 0:12
  Look Forward Podcast from S&P Global.
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• 1:10
  Welcome everyone.
• 1:10
  My name's Andy Critchlow.
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  I'm head of news at S&P Global, commodity Insights, and I'm also the
• 1:16
  host of the Look Forward Podcast.
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  And on today's episode, we are tackling the subjective actuary in the US as of
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  2024, the actuarial services market, yes, I can pronounce that correctly, in the US
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  was valued at approximately $19.1 billion and is projected to reach 30 billion.
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  By, 2030.
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  And in terms of employment, there were around 24,000 actuaries,
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  working in the United States.
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  Filling a function in the economy, that's absolutely vital, really for, the,
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  the, functioning of financial services and, and business as a, as a whole.
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  And to discuss this, I'm delighted to welcome into the studio, here in London,
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  Stephen Smith, chief Investment Officer of Insurance Investments at Newberger
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  Berman, responsible for advising.
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  Structuring and managing insurance portfolios across asset classes.
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  In addition, Steven chairs the C-1 subcommittee at the American
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  Academy of Actuaries, and I know that we're gonna get into the Academy's.
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  Work in a little bit more detail.
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  So just to kick us off, what is the academy, Stephen, and it's,
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  what's its relationship specifically with the National Association
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  of Insurance, commissioners and what's your role in that?
• 2:46
  Sure.
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  So the Academy is a nonpartisan, policy group, that, that provides technical
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  actuarial, ser or advisory to, to.
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  You know, real to policy makers.
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  And you know, you mentioned the NAIC, that's the National Association
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  of Insurance Commissioners.
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  So they, that is a, So in, in the United States, insurance is regulated, not
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  federally, mostly, at the state level.
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  And the NAIC is where the different states coordinate on, on, on regulations.
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  So the, you know, among, among other functions.
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  One thing the Academy does is advises the NAIC on on
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  technical and actuarial matters.
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  And that's, you know, so in the scope of, you know, life insurance
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  in particular, and that's where, where I volunteer with the, with the
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  academy, I chair the C-1 Subcommittee.
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  Also, the Life Investment and Capital Adequacy Committees, it's for, those are
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  both within the life insurance, world.
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  So I, you know, with, with the C one subcommittee work in particular,
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  I'm, helping the academy on anything related to life insurance investment
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  capital that comes up at the NAIC.
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  Just to kind of frame life insurance as a subject in the United States,
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  I mean, I is, it is, is life heavily insured in the United States when
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  compared to other developed economies?
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  That's, you know, that's a great question.
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  It's, so certainly the, the, the most heavily insured on life are,
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  are gonna be Japan and Taiwan.
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  And actually I think in reverse order, Taiwan is largest life insurance market
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  as a percent of GDP in the, in the world.
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  Japan is way up there.
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  To be honest, I don't know how the United States compares to say
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  the United Kingdom or other, other European countries, I mean the growth.
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  And this is, this is gonna be important for kind of what we, we were talking
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  about later that a lot of, there's been a lot of growth in the life insurance
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  space, but really that growth has been in, you know, in, in specific types
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  of universal life and also annuities.
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  Of course.
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  So which all falls under the broader, you know, the broader life insurance umbrella.
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  And it's all gets regulated, in the, under that life insurance umbrella.
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  It's, a, a fascinating subject.
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  And it, it occupies a lot of people's conversations at the moment, either
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  at, you know, at dinner parties or at, you know, round tables.
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  I was at a, a function in the city, last week and, this whole subject of
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  the, the changing demographics and more people, you know, hitting that.
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  You know, 50 plus age bracket and of course life insurance, annuities,
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  these are all services in the financial sector that people start
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  to think about when they get older.
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  Right.
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  And in economies like the United States.
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  In Europe here, the UK especially populations are getting, getting older.
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  So it's, an interesting space.
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  So in the, in the scope of the current project on, CLOs collateralized,
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  loan obligations, capital, why is that important to the market?
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  So CLOs have been a growing asset class for, you know, at least for
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  US insurers, we have very good data on US insurance investments.
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  That's the, you know, that's where the most, transparency is out of any other
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  market insurance market in the world.
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  We can see that.
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  I mean, just over the last decade or so, CLOs have gone from.
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  I mean, rounding to zero in terms of, of an investment up to
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  now 4.5% of total assets held.
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  And that's of for life insurers.
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  Right?
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  And that that's four point a half percent of, you know, approaching $5 trillion.
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  So it's a winds up being a large amount of, of, you know, it's a large share.
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  It's a non-trivial share of the, of the US life insurers portfolios.
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  It's also, if you look at it in reverse, roughly speaking, so CLOs have.
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  Multiple tranches, that are issued.
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  If you look at the triple A tranche, so the most senior, lowest credit
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  risk tranche, about 20% of all outstanding CLOs are owned by insurers.
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  If you look at the next three down, the double A, single A and triple B.
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  Roughly half of all outstanding, of those tranches are held by insurers, and
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  then the double B is back to around 20%.
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  So there's, there's a, like insurers make up a very important part of the
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  investor base of CLOs and especially in the investment grade mezzanine tranches
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  from, double A down through triple B.
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  And those mezzanine tranches.
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  I mean, how much.
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  What, what's their share of the total market?
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  'cause that's a big number.
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  You, you know, $5 trillion is huge.
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  Yeah.
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  So the, I mean, so the trip, so, I guess again, there, there's still two ways
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  of looking at it from the perspective of like total CLOs being the universe.
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  We consider the majority of the dollars are in, or the plurality
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  of dollars are in triple A. That's by far the thickest tranche.
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  And so for any given CLO that's issued, the double A, single A
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  Triple B might both be about five, it might be, might be about 5% each.
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  You know, there's a, then there's a residual tranche of, call it around
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  8% at issue, and then all of the rest goes to the triple A. So most
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  of it is, is triple A, but for.
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  Right.
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  But for insurers, you know, their, you know, life insurers anyway are invested.
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  You know, a little bit less than half of their total investments
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  into CLOs or triple A's.
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  And the rest is mostly double A, single A, triple B, you know, they have
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  some double B, some residual tranche.
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  But so, you know, so if you figure four point half percent in total,
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  you know, maybe 2% or so is, is, is invested in those, mezzanine,
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  investment grade tranches.
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  How does the academy's work differ from the SSGs work?
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  So, yeah, so just to, to level set a little bit, there is this, you
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  know, there, there have been a couple of different projects that started
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  somewhat in parallel with NAIC to tackle capital charges for CLOs.
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  So, as CLO, you know, regulars have noticed that CLOs are making up a
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  larger share of investment portfolios.
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  So, and, and as of today, a CLO.
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  Capital requirement is the same as a corporate bond capital requirement
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  of, of the same rating, but the risk characteristics are, are different
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  despite that same capital charge.
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  So as, as CLOs have become more material, so the industry regulators have wanted
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  to look into, updating capital charge.
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  So with that.
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  With that objective, really two parallel projects were started that
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  are somewhat merging together now.
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  But the first project that started was SSG, that is the
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  structured securities group.
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  It's NAIC staff who are working to, set aside ratings.
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  Mm-hmm.
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  So, as I said before, capital charges are based on ratings.
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  Today, the SSG approach is to.
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  Ignore the ratings of each CLO and instead run it through a model that is
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  developed and maintained by the NAIC and reassign it to a different, effectively
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  to a different rating, although it's, it's to a designation technically.
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  So, but it would still map into corporate bond charges.
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  So, for example, they might take a, a triple B CLO, there might be something the
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  model sees in it that, that actually it seems riskier and it might get mapped to a
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  triple C. Bond rating, just as an example.
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  Or it could go the other way too.
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  Like a single egg might turn into a triple A. So that, that's the basic SSG approach.
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  The academy approach is, is a little bit different in that
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  our, our objective is to.
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  Not rely on the corporate bond factors, but to come up with
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  a new set of factors for CLOs.
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  And then those fact, and once we have a new set of factors, we
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  don't think we need to model each individual CLO going forward.
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  At least that's our, that's our hope is that we can use either a rating
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  or some other, you know, simple.
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  Combination of statistics.
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  So it may be weighted average rating on the underlying collateral
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  or credit support or something like this to, to i to categorize
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  each CLO into, into a risk bucket.
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  So that, that, so that's the main difference.
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  But I, I should, I just wanna make clear, this isn't a competitive process
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  between the academy, SSG, we're actually collaborating with the SSG, the SSG
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  joins us in our weekly meetings, that.
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  On, on, on working through this.
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  And they are helping us with our runs at the same time as, as
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  doing the project that the, NAIC is mandated that they do as well.
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  So I, I think these two projects are, merging over time.
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  Okay.
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  So you're putting a final number on it ultimately.
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  Yeah.
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  Yeah, yeah.
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  Like our output is a number.
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  The SSG output is kinda reassigning a designation.
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  Right, right.
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  Yeah.
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  The, the, as, as a, former Wall Street Journal financial journalist, I think I
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  prefer that outcome 'cause I could see that that would be, be a good story.
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  'cause there's gonna be some big numbers right on, on, on the
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  end of those, those assumptions.
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  The, you mentioned the model that, These instruments run through?
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  I mean, is that a kind of stress test?
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  What's it looking for specifically?
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  So there, so again, I guess there are still these two
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  separate modeling approaches.
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  But you would you, I think.
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  Very roughly speaking, stress test is, is fair, but it's, you
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  know, a, you know, if you think of like when a rating is assigned.
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  Mm-hmm.
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  And obviously there are many people in this building who will know this a
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  lot better than I will, but there's, you know, there is AAA stress test
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  effectively, and if you can pass that, you get to be triple A. There's a
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  double, a stress test that's, you know, a little bit, you know, it's a little
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  bit easier and, and so on and so forth.
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  The academy model.
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  Is, is built a little differently so that we are, rather than trying to meet a
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  specific threshold, we are just trying to quantify the risk at a particular point
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  in the tail of the risk distribution.
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  And right now all of our, like, ultimately the regulars have
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  to decide where in the tail.
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  But for per, for just purposes of coming up with some kind of number, for now,
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  we are using what's called the CTE 90.
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  That's conditional tail expectation.
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  90. It means, you know, we run 10,000 scenarios.
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  We throw away the best 9,000, we're just left the worst 10%.
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  And then we take the average of those and that becomes basically our risk measure.
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  So the, you've heard the, the financial, term for the next year though?
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  The, the, the condi, the CT nine CT 90.
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  Yeah.
• 13:01
  Yeah.
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  CTE 90.
• 13:02
  That's right.
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  We love it.
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  I guess, you know, kind of linked into that another question that I have.
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  You know, I guess modeling these things and understanding that market was
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  simpler before an event like COVID, how did that change your thinking
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  at all, or the academy's work or any of these studies that's going on?
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  Because it was a very sort of, you know, a, a kind of black swan event.
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  No one kind of saw it coming, but it, it definitely did have
• 13:28
  an impact on life expectation.
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  Sure.
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  Yeah.
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  Well, it, it, so it had a, actually, I'll tell you, it, it,
• 13:35
  it did, but let me even dive in.
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  There's a specific impact it had on CLOs that, that we've had to, that, that we've
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  had to work through on this project.
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  So, something that is something true about CLOs and not corporate bonds is a
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  clo, will never really have a default.
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  typically in a typically structured CLO there won't be a default event
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  until the final maturity date when, there is, when there's not enough,
• 14:00
  money available to pay principal.
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  But there are many scenarios where if the underlying pool of loans is under stress.
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  The a CLO might defer interest payments, you know, in particular if it's one
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  of these mezzanine CLO tranches.
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  So for example, if the, there's stress underlying the triple B tranche
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  and the double B tranche might stop paying interest to, to shore up cash
• 14:21
  to make the tranches above it safer.
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  But when they do that, they bill that, that interest capitalizes,
• 14:28
  it's called payment in kind or PIK.
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  So the, it's effectively the principle that is owed to the investors into
• 14:33
  those tranches grows over time.
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  Mm-hmm.
• 14:36
  Now.
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  Normally you would think if that's growing, that's probably a bad sign
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  and, and we should expect that some kind of loss will be experienced
• 14:42
  by those investors at some point.
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  However, COVID provides this really interesting counter example where during
• 14:48
  COVID, there was this immediate stress.
• 14:51
  In, in the, in, in the system, there were, you know, loans were were being
• 14:55
  downgraded to triple C or were is it, so this was triggering just through
• 15:00
  the automatic structure of a CLO.
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  It was triggering PIKs.
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  It was triggering, triggering deferral of interest on mezzanine tranches.
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  Largely speaking, as we worked through COVID, those
• 15:11
  tranches wound up being money.
• 15:12
  Good.
• 15:13
  They, they had to pay out more than they would've because of that deferred
• 15:15
  interest that, you know, there's interest on interest, but they were.
• 15:18
  Basically able to, able to make those payments in the end.
• 15:21
  And, you know, our initially and our, our thought in modeling was to say, was
• 15:26
  to treat, the, deferral of interest.
• 15:28
  Like if you failed to make an interest payment, that should tell us something.
• 15:31
  It should tell us you are probably about to, experience losses.
• 15:35
  But COVID provides a counter example to that.
• 15:36
  It's more complicated there.
• 15:38
  If you have a severe stress followed by a quick recovery, tranches may
• 15:43
  defer interest and then recover.
• 15:45
  That's really fascinating because.
• 15:47
  You know, when, when COVID happened, I think all our fears were that, that
• 15:51
  this is the mother of all financial crises and, and you know, you saw
• 15:56
  it in different asset classes.
• 15:58
  I know here on the commodity side at S&P, you know, WTI crude going into,
• 16:04
  into negative territory, something that had never been seen before.
• 16:07
  But actually from what you're saying, if I'm understanding it right, actually
• 16:10
  the insurance market, that it reacted in a way completely differently to what.
• 16:14
  The big fear was right.
• 16:15
  It was, and in many ways that probably proves all the, that all the stress
• 16:20
  test measures, all the guardrails that put in place worked really well.
• 16:25
  Yeah.
• 16:25
  And, and even in the financial crisis, CLOs came out largely unscathed.
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  And, and, and frankly, the, the structures got more conservative, less levered
• 16:34
  after the financial crisis anyway, even though even during the financial
• 16:38
  crisis they actually performed well.
• 16:40
  So there is a lot of history and, and that, and that kind of, I think
• 16:43
  that leads to a tension in the, you know, the work that we're doing
• 16:47
  and also just in the debate that is happening in the broader insurance
• 16:51
  regulatory community between those who.
• 16:54
  You know, on the one hand there, there are people who will point
• 16:56
  to the actual empirical history, which shows CLOs don't like.
• 17:01
  Historically, it's just especially investment grade CLOs, it is just
• 17:05
  very rare to experience a default ever, even through some very
• 17:07
  severe stresses On the other hand.
• 17:11
  The underlying all of the assets that actually underlie those
• 17:14
  CLOs, they're, they're almost entirely below investment grade.
• 17:17
  Like we know there is risk.
• 17:18
  We also know that over time the recoveries after default on the
• 17:22
  underlying, these underlying loans have been getting worse and worse.
• 17:26
  So there is this tension between, well, historically CLOs have
• 17:30
  not experienced credit losses.
• 17:31
  However, you can come up with reasons why.
• 17:34
  They might in the future, right?
• 17:35
  They would, especially recoveries, getting, getting worse and
• 17:39
  interest rates rising, right?
• 17:40
  Which means all of the companies, you know, these loans are all floating rate.
• 17:43
  The companies are borrowing at floating rate, which means it's getting harder
• 17:47
  for them to make, to make their loan payments with, with higher rates now.
• 17:53
  What sort of connection is there to, you know, broader money markets in the US
• 17:57
  with, with, with how these loans perform?
• 17:59
  I mean, you know,, say what the Fed does, et cetera.
• 18:02
  So, yeah.
• 18:03
  So they are, so they are all floating rates.
• 18:04
  So they, they, they always say all, they are almost all floating rates, right?
• 18:08
  So they pay, you know, they pay SOFR plus a contractual spread.
• 18:12
  So, as you know, I mean, now the Fed is, is cutting again, so that, you know that,
• 18:15
  SOFR will, you know, quickly follows what the, what the Fed does, which means
• 18:19
  the interest payments are coming down.
• 18:21
  It's also, but, you know, fortunately there is.
• 18:23
  There is asset liability matching inside of a CLO.
• 18:26
  So all of the assets of a CLO, these bank loans or, or middle
• 18:29
  market loans are floating rate.
• 18:31
  All of the debt t tranches on MO most, for most CLOs, the debt tranches, that
• 18:36
  are issued are also floating rate.
• 18:39
  So mostly that, you know, that's SOFR just passes through.
• 18:44
  Of course, the difference is the, you know, there are more assets
• 18:47
  than liabilities in a CLO and so you might issue, you might raise.
• 18:52
  You know, let's say you raise $500 million for a CLO, you'll buy.
• 18:56
  You know, something like $460 million of loans, there's an extra 40.
• 19:00
  So it is slightly beneficial for the CLO structure if rates rise.
• 19:04
  And in that sense, assuming that rates rising doesn't also cause the,
• 19:08
  bank loans to be more likely to.
• 19:09
  So that excess is like a buffer within the clo, is it?
• 19:11
  Yeah.
• 19:12
  And that is all effectively owned by what's called the residual tranche.
• 19:14
  So they're whoever owns the equity in the CLO, if there's money left over at
• 19:18
  the end, like they keep all of it, but they're also the first to lose money when
• 19:21
  there's, losses on, on the pool of loans.
• 19:24
  Got it.
• 19:24
  Got it.
• 19:25
  Got it.
• 19:26
  What resources is the Academy using to undertake this study?
• 19:29
  So it, so the academy is, you know, the, the work is all done by volunteers.
• 19:34
  So we are
• 19:35
  Wow.
• 19:35
  Like, like, like myself.
• 19:36
  Yeah.
• 19:36
  So we're, you know, we we're, you know, no one's for better or worse,
• 19:40
  no one's paying us to do the work.
• 19:41
  Right.
• 19:41
  So it's, it's mostly actuary.
• 19:43
  It's all actuaries.
• 19:44
  And you know, those who work at a combination of asset managers like
• 19:47
  I do, or who work at life insurers or who work at consultants or in,
• 19:51
  actually in some cases who are retired.
• 19:53
  And this is a, a way to stay connected to the profession, keep, keep active so that.
• 19:57
  There's, so that those are the, the people doing the work.
• 20:00
  But in addition to that, we've been very fortunate to get really,
• 20:04
  really great support from the broader community, including S&P.
• 20:07
  You know, S&P has been hugely helpful to us.
• 20:11
  They, they've made available, they're, they're structured finance team, but
• 20:13
  we've been able to, to spend a lot of time with, actually the ACLI that's, a trade
• 20:17
  group representing, US life insurers has,
• 20:20
  also been helpful.
• 20:21
  They've, they've allowed, they owned the model, for corporate bonds.
• 20:24
  They've allowed us to, to, to use that to model the underlying loans so that, Yeah.
• 20:30
  And, and just in, in, I mean, just in general, I mean the, the whole industry,
• 20:33
  I mean the CLO portfolio managers, risk teams, across life insurers and asset
• 20:38
  managers have all, made themselves available to us to, I mean, to help
• 20:42
  train up, you know, not, not every actuary on this group is necessarily,
• 20:47
  you know, came into this project having spent decades working on CLOs.
• 20:50
  Right.
• 20:50
  I mean, there, there's a. Diverse range of backgrounds and experiences.
• 20:54
  So, you know, I think especially the, the broader community was really helpful
• 20:58
  in, in helping, helping people on the, on this volunteer group get up to speed.
• 21:02
  So it's really sort of taken a village to, to pull this thing together.
• 21:05
  It's interesting though that, that you, you've managed to pull together
• 21:09
  such a broad spectrum of, you know, expertise from, from, from the industry.
• 21:13
  People must really see a benefit in this study then to commit that time.
• 21:17
  Either benefit in a study or a fear of it being done wrong.
• 21:20
  Right, right.
• 21:20
  Okay.
• 21:21
  Yeah.
• 21:21
  Yeah.
• 21:22
  I mean, on, on that, that question then what, I mean, you
• 21:25
  know, what, what could go wrong?
• 21:27
  Yeah.
• 21:27
  Well, I mean, if you get the capital charges wrong, I mean, it's
• 21:31
  bad in either direction, right?
• 21:32
  So if the capital charges are too high, you, you.
• 21:36
  Pulling, choking off this source of capital for CLOs, which in
• 21:40
  turn chokes off a source of capital for the underlying loans.
• 21:42
  And these are, you know, these are generally small, smaller companies.
• 21:45
  You know, they like it, it, we don't, and again, I'm not, I am not
• 21:48
  an expert on the, on the finance side of, of these companies, but
• 21:51
  I would imagine having capital available is probably good for them.
• 21:55
  So that's, yeah.
• 21:56
  So we don't want them too high.
• 21:58
  We also don't want them too low because then you, you may see insurers take on
• 22:03
  excess risk by buying more of these than is appropriate for their portfolios.
• 22:07
  And, and then, you know, then regulators will, will not have the advanced warning
• 22:11
  of, of potential issues, solvency issues that RBC is meant to give them.
• 22:16
  It's a seat at the table that you want to have then, to have a
• 22:19
  stake in what those outcomes are.
• 22:21
  Yeah.
• 22:22
  Can you give us some details?
• 22:24
  What's in the study?
• 22:25
  Yeah, absolutely.
• 22:26
  So we are, this is, you know, really important, that we want because
• 22:31
  internal consistency is important.
• 22:33
  We do not want, and, and there's, there's this con, there's this phrase that's
• 22:36
  been, bandied about a lot recently called Equal capital for equal risk.
• 22:40
  That is a directive from the NAIC at this point.
• 22:43
  So we want to find a way to model CLOs such that the whole
• 22:47
  framework is internally consistent.
• 22:49
  You know, when we include, especially corporate bonds, right?
• 22:52
  So we don't want CLOs to look cheap or expensive in capital terms versus bonds.
• 22:56
  So the way, the way we do that, we are using that corporate bond model
• 23:00
  that, you know, that the, that acl that the A CLI has, has given us
• 23:04
  access to that was, and developed, I mean they paid Moody's to develop it.
• 23:08
  And we're, we've got that, we've got that model.
• 23:10
  We are using it.
• 23:12
  To run, these 10,000 economic scenarios I mentioned earlier
• 23:16
  on the entire underlying pool of loans that sits inside of the CLOs.
• 23:21
  We then identify, so there's 10,000 scenarios.
• 23:24
  We have a, a statistical technique to identify 17 key scenarios that
• 23:28
  are all fairly deep in the tail.
• 23:30
  These are all bad outcome kind of scenarios, and we, we run each of those.
• 23:35
  Give us an idea of some of these bad scenarios then.
• 23:37
  What?
• 23:39
  Well, so I mean, there's,
• 23:39
  are we talking plague and, and
• 23:41
  well, well, so the model doesn't work exactly that way.
• 23:44
  There's no narrative to the model.
• 23:45
  It's just a quantitative one.
• 23:47
  The, the numbers are enough defaults that, you know, the defaults
• 23:50
  like have never happened before.
• 23:51
  Right, right.
• 23:51
  And that's important.
• 23:52
  The worst case scenario is not the worst case in the history.
• 23:54
  It's a forward looking model where something much worse could happen and
• 23:58
  we have to assign some probability to something much worse happening.
• 24:02
  I mean, and if we otherwise, well historically.
• 24:05
  Investment grade CLOs basically don't default.
• 24:07
  It would be very easy if we weren't assigning that.
• 24:09
  That's a really interesting concept.
• 24:10
  'cause I think that most people's misunderstanding of risk is that
• 24:13
  it's based on the last major risk event that the market saw.
• 24:16
  And it's not is it's, as you said, it's
• 24:19
  Daily
• 24:19
  Yeah.
• 24:19
  It's the worst, worst, worst right.
• 24:22
  Possible computation from what we would see in the data.
• 24:25
  That's right.
• 24:26
  Yeah.
• 24:26
  So we take those 17 varying degrees of kind of worse that we could see scenarios.
• 24:32
  We run each of them through, a, a, we run each of them through the waterfall
• 24:38
  structure, which is what we call just this idea that losses get distributed
• 24:41
  from the bottom of the CLO up to the top.
• 24:43
  So we identify where the losses are in each tranche of each CLO,
• 24:48
  and then finally, once we've identified those losses, we convert
• 24:51
  them into capital charges by applying a few other adjustments.
• 24:55
  You know, most importantly.
• 24:57
  Taking out the amount of risk that is already incorporated in the reserves
• 25:01
  that insurance companies hold.
• 25:02
  And then, you know, seeing how much risk is left over for the, you
• 25:05
  know, for, for the capital charge.
• 25:09
  This is a task to me that would seem like, would, you know, potentially
• 25:14
  AI could have a big impact in how.
• 25:17
  Maybe not this study, but future studies are, conducted or the, the, the outcomes.
• 25:22
  Are you starting to see any of that?
• 25:24
  Does that play a part?
• 25:25
  I mean, I mean I, I, this is a more mundane version of ai, but I mean, already
• 25:29
  some of the code that we have written has been AI assisted, for this project.
• 25:33
  So it has, it has found its way in, but in the, I think the more
• 25:37
  It made it quicker.
• 25:38
  Right.
• 25:38
  To do, do you think?
• 25:39
  Yeah.
• 25:39
  Oh, absolutely.
• 25:40
  Absolutely.
• 25:41
  Yeah.
• 25:42
  It, it, but, you know, in the sense of what we haven't done, which I think is
• 25:46
  kind of the, you know, the more sexy version of AI would be to have AI just
• 25:49
  kind of give AI the broad parameters and say, solve the math problem.
• 25:52
  We have, we haven't done that.
• 25:53
  Right.
• 25:53
  The, and, and you know, the truth is we're trying, like our, I think we're, we're
• 25:57
  much more heavily constrained than, then.
• 25:59
  Something like a machine learning type of a, an approach would lead to, 'cause we.
• 26:04
  We want to be consistent with what has already been done and
• 26:08
  what's already in the system, and that that heavily constrain us.
• 26:10
  So we're not exact, we're not really playing in a sandbox where we're
• 26:13
  just trying to get the best, most precise measure of the risk purely.
• 26:17
  I mean, we want to be as, as precise and, and accurate as we can be with the risk,
• 26:21
  but subject to the constraint that we are taking an approach that is, that is
• 26:25
  consistent with other areas within RBC.
• 26:29
  So what you've just described, this document, this study to me.
• 26:34
  This sounds like the most important document in the.
• 26:38
  Financial services that's about to come out.
• 26:40
  I think that everyone needs to see this.
• 26:41
  So what will the public be able to, will it be made public so that
• 26:47
  people can, can read this openly?
• 26:49
  It will be, yeah.
• 26:50
  I'm not, I'm not sure if it's the most important.
• 26:51
  Appreciate you saying that.
• 26:53
  It's.
• 26:54
  Drum roll
• 26:54
  To some there, there are surely someone in the world for whom
• 26:58
  this is the most important.
• 26:59
  I don't know about the broader world, but it, yeah, it so well
• 27:02
  But everyone's insured.
• 27:03
  I mean, this is the, the, I mean, this is where I find it a fascinating subject.
• 27:06
  You know, it's, it's insurance is, is, is probably after your home loan, the second
• 27:11
  most important decision you're gonna make.
• 27:13
  Financially, anyone's gonna make.
• 27:14
  Okay, so it's wood.
• 27:16
  I would say this, if you're gonna read anything, read this.
• 27:18
  I appreciate that.
• 27:19
  Thanks.
• 27:20
  Yeah, so, so it is all, yeah, it's all, it's all public.
• 27:23
  Actually most recently on September 8th, I think it was Monday the eighth, we
• 27:28
  presented an update on this study to the NAIC, and that is the, the, the, the.
• 27:34
  Entire presentation is public on, on the NAIC website.
• 27:38
  And we will, and on the American Academy of Actuaries website and will, you
• 27:42
  know, but that was a status update.
• 27:44
  Ultimately, we will have a full report that, again, will be made public.
• 27:48
  I mean it, and it will be as transparent as we're allowed to.
• 27:51
  I mean,
• 27:51
  there are a couple of vendors that, that we're using where we're not necessarily
• 27:53
  allowed to disclose like their, the underlying assumptions that came for their
• 27:56
  data, but outside of that, like every part that we legally can make transparent will
• 27:59
  be, will be transparent to the public.
• 28:01
  So it's gonna be made, publicly available.
• 28:04
  What else will the NAIC do with it?
• 28:07
  So, that's a great question.
• 28:08
  The Academy is, is advising, but we have no authority to implement.
• 28:14
  Mm-hmm.
• 28:14
  That is all up to the NAIC and to the states.
• 28:17
  So we will, we will present our, our, our recommendations and then
• 28:22
  it's the NAIC, they, they might.
• 28:24
  I just say thank you.
• 28:26
  You all are brilliant.
• 28:27
  We're just adopting it just like this.
• 28:29
  You, they might adopt it with some adjustments or they could
• 28:34
  completely discard it, right?
• 28:35
  They, they, I mean it's, you know, it's plausible that, you know, the
• 28:38
  SSG has this alternative approach that I mentioned of while we're
• 28:40
  collaborating together on, on this approach, it's possible regulators say.
• 28:44
  You know what, the SSG approach is just a better way of doing
• 28:47
  it than, than the academy.
• 28:48
  I mean, they will, you know, that will either way.
• 28:50
  I, I would expect 2026 to be kind of a key year for seeing
• 28:54
  how that, how that turns out.
• 28:55
  The, the SSG approach is being, was gonna be implemented 2025 year end, it looks
• 29:01
  like that's getting delayed to 2026.
• 29:03
  Just to give time, I think, to give regulators the choice between the two.
• 29:06
  Is there a scenario where they would ask you to make revisions or give you,
• 29:10
  Yeah, they certainly could.
• 29:12
  And we're, we're trying to build that into the, into the timeline.
• 29:15
  I mean, the, in order for 2026 year-end implementation to happen, we need to
• 29:19
  have the numbers finalized by April 30th.
• 29:23
  So we are, you know, our goal is to have the, our next.
• 29:26
  A big report ready by January.
• 29:29
  So that gives time for, or, you know, for a round of, of feedback
• 29:33
  and, and, and doing the work again.
• 29:35
  And of course, like you, there's, there's no, there's no law at the
• 29:38
  universe that says the whole thing couldn't be delayed till 2027.
• 29:41
  I think there's a lot of, but I, I think there's a lot of, you
• 29:44
  know, a lot of desire on, on the part of basically everybody to
• 29:47
  put this to bed in 26 if possible.
• 29:49
  Early 26.
• 29:50
  Then that's the, the, the kind of key date there.
• 29:52
  Great.
• 29:53
  Well, Stephen, thank you so much for coming into the, studio here in
• 29:58
  London, and thank you so much for, you know, giving me such a comprehensive
• 30:01
  view of the work of the academy, the NAIC, but also the importance
• 30:06
  of actuary globally and insurance.
• 30:09
  Everyone has it.
• 30:10
  Everyone needs it.
• 30:11
  We should all, understand it more.
• 30:14
  Thanks very much to our listeners, for downloading, this episode
• 30:17
  of the Look Forward, podcast.
• 30:20
  You can find us on, Apple Podcast store, Spotify, YouTube, if you so choose,
• 30:27
  and also the S&P global.com website.
• 30:30
  Thanks very much.
• 30:31
  Bye-bye.