sapiens.com Open in urlscan Pro
65.21.62.103  Public Scan

Form analysis
2 forms found in the DOM

GET https://sapiens.com/

<form role="search" class="searchform fusion-search-form  fusion-live-search fusion-search-form-clean" method="get" action="https://sapiens.com/">
  <div class="fusion-search-form-content">
    <div class="fusion-search-field search-field">
      <label><span class="screen-reader-text">Search for:</span>
        <input type="search" class="s fusion-live-search-input" name="s" id="fusion-live-search-input-0" autocomplete="off" placeholder="Search..." required="" aria-required="true" aria-label="Search...">
      </label>
    </div>
    <div class="fusion-search-button search-button">
      <input type="submit" class="fusion-search-submit searchsubmit" aria-label="Search" value="Search" data-color="rgb(158, 160, 164)">
      <div class="fusion-slider-loading"></div>
    </div>
  </div>
  <div class="fusion-search-results-wrapper">
    <div class="fusion-search-results"></div>
  </div>
</form>

GET https://sapiens.com/

<form role="search" class="searchform fusion-search-form  fusion-live-search fusion-search-form-clean" method="get" action="https://sapiens.com/">
  <div class="fusion-search-form-content">
    <div class="fusion-search-field search-field">
      <label><span class="screen-reader-text">Search for:</span>
        <input type="search" class="s fusion-live-search-input" name="s" id="fusion-live-search-input-1" autocomplete="off" placeholder="Search..." required="" aria-required="true" aria-label="Search...">
      </label>
    </div>
    <div class="fusion-search-button search-button">
      <input type="submit" class="fusion-search-submit searchsubmit" aria-label="Search" value="Search" data-color="rgb(158, 160, 164)">
      <div class="fusion-slider-loading"></div>
    </div>
  </div>
  <div class="fusion-search-results-wrapper">
    <div class="fusion-search-results"></div>
  </div>
</form>

Text Content

Skip to content
 * Modernize
   * Transform your core with next generation, digital-led solutions designed to
     deliver enhanced, frictionless experiences, and increase efficiency,
     revenue and success.
     * Property and Casualty:
       Commercial Lines
     * Life & Pensions
     * Reinsurance
     * Property and Casualty:
       Personal Lines
 * Differentiate
   * Tap into the digital era and reimagine your engagement with customers, the
     visibility you provide to agents and brokers, and the agility and
     flexibility with which you manage your business.
     * Digital
     * Data
     * Decision
 * Rearchitect
   * Evolving software architectures go beyond the monolithic systems of the
     past, to enable more flexibility, more scalability and faster time to
     market.
     * Cloud
     * Next Gen Architectures
     * Partners Ecosystem
 * Resources
   * Blog
   * Case Studies
   * Whitepapers & eBooks
   * Insights
   * Events & Webinars
   * Videos
   * Podcast
 * About
   * Our Story
   * Newsroom
   * Corporate Responsibility
   * Investors
   * Leadership
   * Contact Us
   * People & Culture
   * Join us
 * Search for:
   
   
 *  * North America (English)
    * EMEA & APAC (English)

 * Request a Demo

 * North America (English)
 * EMEA and APAC (English)




Search for:



 * Modernize
   * Transform your core with next generation, digital-led solutions designed to
     deliver enhanced, frictionless experiences, and increase efficiency,
     revenue and success.
     * Property and Casualty:
       Commercial Lines
     * Life & Pensions
     * Reinsurance
     * Property and Casualty:
       Personal Lines
 * Differentiate
   * Tap into the digital era and reimagine your engagement with customers, the
     visibility you provide to agents and brokers, and the agility and
     flexibility with which you manage your business.
     * Digital
     * Data
     * Decision
 * Rearchitect
   * Evolving software architectures go beyond the monolithic systems of the
     past, to enable more flexibility, more scalability and faster time to
     market.
     * Cloud
     * Next Gen Architectures
     * Partners Ecosystem
 * Resources
   * Blog
   * Case Studies
   * Whitepapers & eBooks
   * Insights
   * Events & Webinars
   * Videos
   * Podcast
 * About
   * Our Story
   * Newsroom
   * Corporate Responsibility
   * Investors
   * Leadership
   * Contact Us
   * People & Culture
   * Join us
 * 
 * Request a Demo



 * Sapiens
   >
 * Podcast
   >
 * Bridging the Insurance Talent Gap with AI
 * Bridging the Insurance Ta...


BRIDGING THE INSURANCE TALENT GAP WITH AI | EPISODE 10


FEATURING

Today’s insurance industry is thriving with innovative technologies,
next-generation products, and novel methods of customer engagement. But a
shrinking headcount due to retiring baby boomers and a shortage of younger
workers could jeopardize its bright future. Listen as host Caryn Warner,
Sapiens’ Director of Marketing, North America, explores how AI can help carriers
bridge the insurance talent gap with guest Jeffrey M. Snider, General Manager of
P&C at Gradient AI.



Host: Caryn Warner
Director of Marketing, North America
Sapiens
Guest: Jeffrey M. Snider
General Manager of P&C
Gradient AI
Bridging the Insurance Talent Gap with AI
Episode 10
0:00 13:50 100 1x
Subscribe

SUBSCRIBE :


Bridging the Insurance Talent Gap with AI

Caryn Warner: Hello! Welcome to the Sapiens Insurance 360 podcast. I’m your
host, Caryn Warner, and I’m so excited that you’re out there listening. This is
where we discuss the latest news, trends, and issues from across the insurance
solutions and technology spectrum. Today we have a very special guest, Jeffrey
M. Snider. With nearly 25 years of successfully leading teams in cutting-edge
technology companies, Jeff is General Manager of P&C at Gradient AI. He
leverages his experience managing insurance programs and handling claims as a
lawyer, in-house counsel, and risk manager to help Gradient AI grow its solution
set to include all major property and casualty insurance lines. On today’s
program, we’ll be discussing bridging the insurance talent gap with AI. Jeff,
welcome to the show.

Jeffrey M. Snider: Thanks, Caryn.

Caryn Warner: I’m sure that we can all agree that today’s insurance industry is
incredibly dynamic. The innovative technology that’s coming out of startups and
established firms these days is astounding — in-depth data analytics, advanced
API infrastructure, and intuitive and seamless user experience, just to name a
few. But a glaring downside is that the industry’s headcount is on a serious
decline. According to insurance industry consultancy, the Jacobson Group, the
talent shortage is getting worse with the 10-year average unemployment rate in
insurance only slightly above the current 2.5%. There are a variety of reasons
for the tight insurance labor market, but the more immediate pressing question
is what to do about it. One oft-proposed solution has been AI, especially for
such key areas as technology, claims, an underwriting, where the retirement of
so many baby boomers has been driving a host of vacancies. So Jeff, to start us
off, how does AI help insurers who are facing a shrinking workforce and
challenge to find experienced replacements?

Jeffrey M. Snider: It’s a great question. I think the answer is to hang on to
that institutional knowledge by mining it from the results that those people
have achieved, and using it to guide newer underwriters and adjusters and AI
allows you to do just that.

Caryn Warner: Okay. So can you talk then about how AI captures critical
institutional knowledge? What does that mean and how does it work?

Jeffrey M. Snider: So, if you think about it, we use an analogy that it’s a lot
like the oil industry was a hundred and something years ago. They know there’s a
tremendous amount of value that they’re sitting on, but it’s just beneath the
surface. And the trick is how to access it. And I think if you look at the
insurance industry today, it’s the same thing, and it’s being brought to a head
as trained industry professionals are retiring and moving out of the industry,
and it’s a real challenge for the industry to find people to replace them and to
train those people if they can find them. The way we tie that analogy back is
all that oil under the ground is all the experience that those adjusters and
underwriters have. And the question is, how do you tap that? The way you tap it
is you look at everything that they’ve done, all the decisions that they’ve
made, and what the outcomes that resulted from those decisions are, and you
glean from that what is likely to happen in a similar situation next time. And
so by looking at those decisions, what was decided, what was done, and what
happened, what the outcome was, and drawing a mathematical correlation between
the two, we can make a very accurate prediction about what’s going to happen
when we see that same situation again. Actuarial tables allow underwriters to
make underwriting decisions, claims managers to make reserve decisions, and
ultimately settlement decisions in the aggregate, right? Actuarial tables have
been around for hundreds of years, and what they say is that if you have a large
enough number of samples, everything deviates to the mean. And so reverts to the
mean. And so you know that on average, something like this is going to result in
the following. But the problem is, no situation is average, right? The average
is made up of things that are better than average, worse than average, riskier
than average, less risky than average. But actuarial tables don’t allow you to
dig into that. AI and specifically machine learning allows you to evaluate
things at the individual level. So at a very high level, the way it works is we
train a model the same way an adjuster or an underwriter is trained. We show it
lots of inputs. Here’s a policy application, here’s what we knew about it at the
time an application was being submitted, and here’s what happened. This is all
historical, so we know what happens. And then we train the model to learn and
then we test the model by showing it inputs it’s never seen and asking it to
predict the outcomes. And then we measure how well it did, and that’s what
proves that the model can make those individual decisions.

Caryn Warner: Yeah, it sounds so powerful. So talk to me about how the newer,
less experienced and underwriters, claims adjusters, how do they use it,
specifically? It captures so much information, how do they access it and how do
they apply it?

Jeffrey M. Snider: Great questions. In terms of how it’s accessed, that really
depends on the organization. And so the goal, I think, always when you’re trying
to do something like this decision support is to integrate it into the
decision-making process. And so they can access it in a very simple way, like a
dashboard view, but it can also be implemented to drive rules-based decisions.
So it may be that a particularly risky application or an application that the AI
determines to be particularly risky is automatically directed to a very
experienced underwriter or a claim that is determined to be very likely to be
high cost is automatically directed to an experienced adjuster. I think the idea
is that it should function to supplement or conceivably even replace the
experienced adjuster who has moved on or the experienced underwriter who has
moved on by providing kind of a virtual tap on the shoulder. In the old days, if
you talk to experienced professionals with 20 or 30 years under their belts,
they’ll tell you that they received real-life taps on the shoulders from the
adjusters or the underwriters who were sitting at the desk next to them. That
experienced person would overhear a phone call and say, hey, did you think about
doing this? Or when I see that fact pattern, I always do this or that. So for an
example, if an expensive surgery has been scheduled, an adjuster may want to
have an independent medical exam — IME — to confirm the diagnosis before it’s
authorized. An experienced adjuster would know to do that, but a new one might
not. And with the power of AI, the new adjuster can be prompted to consider it.
Over time, that person will learn to recognize those patterns in the same way
they would have before, but now they can sort of do it without a physical person
next to them, which in a virtual world is happening less and less.

Caryn Warner: Yeah, that’s fascinating. Does it take a lot of time for
underwriters and adjusters, particularly the ones with more experience, to gain
an understanding of and trust in AI? And what about other innovative
technologies such as predictive analytics? How do insurers help ease what may
be, I guess, a pretty steep learning curve?

Jeffrey M. Snider: Yeah, it’s not really as steep as it sounds. And the reason
is that we’re not looking to replace industry professionals. We’re looking to
augment their capabilities. We say we’re looking to give them power tools. In
the 19th century, lumberjacks cut down trees with an ax. That’s all they had, so
that’s what they used. It worked, but when somebody came along with a chainsaw
and showed them how it worked, they were pretty quick to adopt it. And so it’s
really that kind of a process. And what we see is the experienced adjusters or
underwriters are the ones who are asking for this the most. The ones at the most
innovative companies recognize that this isn’t some sort of magic, it’s math.
And it’s math that they’ve been trying to do all along. And again, at the
aggregate level, they do very well. But the ability to do that at the level of
the individual risk is really new. AI, it doesn’t provide a crystal ball, right?
We’re never going to be able to let you see the future. What this is, is
essentially card counting on an industrial scale, and it allows an underwriter
or an adjuster to see the most mathematically probable outcome and to consider
that in his or her decision-making. It can also be used as a sanity check, what
we like to call an intelligent audit. Traditional audits are done by first
identifying a representative sample of claims or policies, which when you think
about it, is kind of a silly way to go about it, because in a representative
sample, there’s nothing wrong with almost all of the things that you’re looking
at. So you’re looking at a needle in a haystack, looking for a needle in a
haystack, by taking a small piece of the haystack. What AI allows you to do is
instead say, okay, here’s what your folks think. Here’s what the AI-driven model
thinks. Let’s take a look at where they agree and where they disagree, and where
they disagree by the most is really where you should spend your time. I use an
example often when I’m talking to people to illustrate this, pick the
hypothetical 20-year industry veteran. Let’s stick with underwriting. How many
policy applications has she seen in her 20-year career? 20,000, let’s say? How
many of those does she remember? And I’ll be charitable, and I’ll say 200. I say
charitable, because if you ask me to sit down and describe 200 of anything, I
might get the first 10 or 20, but I’m not going to remember much after that. So
how many of the 20,000 policy applications that she seemed to, she remembered
very, very few. And why does she remember those? More often than not, she
remembers those because they’re the outliers. They’re the ones where what she
expected to happen didn’t happen. Maybe she got burned. And so as a result,
human underwriters carry and adjusters carry that bias with them, whereas AI
driven models don’t. They look at everything as just a mathematical probability.
And so once people understand that it’s not threatening to them, it’s not there
to replace them, it’s a power tool. And why wouldn’t they use a power tool,
particularly where we can show them that mathematical probability, the thing
that they now have to largely guess, we can tell them with that much greater
certainty.

Caryn Warner: That is a great explanation, and Jeffrey, you’ve made this really
understandable and consumable, so thank you for unpacking such a timely and
important topic. To everyone listening, thank you so much for spending the time
with us here today. We love hearing from you, so if you have comments or would
like to follow us on social media, please reach out to us on our channels. And
don’t forget to subscribe to the podcast and thank you everybody for listening!
We’ve got more coming, so be sure to tune in next time to Sapiens Insurance 360.

Read more

MODERNIZE

 * Property & Casualty: Personal Lines
 * Property & Casualty: Commercial Lines
 * Life & Pensions
 * Reinsurance
 * Request a Demo

DIFFERENTIATE

 * Digital
 * Decision
 * Data
 * Request a Demo

REARCHITECT

 * Cloud
 * Partners Ecosystem
 * Next Gen Architectures
 * Request a Demo

RESOURCES

 * Blog
 * Case Studies
 * Whitepapers & eBooks
 * Insights
 * Events & Webinars
 * Videos
 * Podcast
 * Request a Demo

ABOUT

 * Our Story
 * Corporate Responsibility
 * Leadership
 * People & Culture
 * Newsroom
 * Investors
 * Contact Us
 * Request a Demo



Copyright © 2024 Sapiens International. All Rights Reserved.

Legal Notice Privacy Policy
TwitterFacebookYouTubeInstagramLinkedIn




Page load link


Go to Top


ARE YOU IN THE RIGHT PLACE?

It looks like you’re visiting our page from Germany.

We recommend using our Sapiens Germany Website for the best experience.

Go to Sapiens Germany Stay here
×
×


WE VALUE YOUR PRIVACY!

We use cookies on our website to give you the most relevant experience by
remembering your preferences and repeat visits. By clicking “Accept”, you
consent to the use of ALL the cookies. However you may visit Cookie Settings to
provide a controlled consent.
Reject All Accept All Cookies
Cookies Settings



PRIVACY PREFERENCE CENTER

When you visit any website, it may store or retrieve information on your
browser, mostly in the form of cookies. This information might be about you,
your preferences or your device and is mostly used to make the site work as you
expect it to. The information does not usually directly identify you, but it can
give you a more personalized web experience. Because we respect your right to
privacy, you can choose not to allow some types of cookies. Click on the
different category headings to find out more and change our default settings.
However, blocking some types of cookies may impact your experience of the site
and the services we are able to offer.
More information
Allow All


MANAGE CONSENT PREFERENCES

STRICTLY NECESSARY COOKIES

Always Active

These cookies are necessary for the website to function and cannot be switched
off in our systems. They are usually only set in response to actions made by you
which amount to a request for services, such as setting your privacy
preferences, logging in or filling in forms. You can set your browser to block
or alert you about these cookies, but some parts of the site will not then work.
These cookies do not store any personally identifiable information.

PERFORMANCE COOKIES

Performance Cookies

These cookies allow us to count visits and traffic sources so we can measure and
improve the performance of our site. They help us to know which pages are the
most and least popular and see how visitors move around the site. All
information these cookies collect is aggregated and therefore anonymous. If you
do not allow these cookies we will not know when you have visited our site, and
will not be able to monitor its performance.

FUNCTIONAL COOKIES

Functional Cookies

These cookies enable the website to provide enhanced functionality and
personalisation. They may be set by us or by third party providers whose
services we have added to our pages. If you do not allow these cookies then some
or all of these services may not function properly.

TARGETING COOKIES

Targeting Cookies

These cookies may be set through our site by our advertising partners. They may
be used by those companies to build a profile of your interests and show you
relevant adverts on other sites. They do not store directly personal
information, but are based on uniquely identifying your browser and internet
device. If you do not allow these cookies, you will experience less targeted
advertising.

SOCIAL MEDIA COOKIES

Social Media Cookies

These cookies are set by a range of social media services that we have added to
the site to enable you to share our content with your friends and networks. They
are capable of tracking your browser across other sites and building up a
profile of your interests. This may impact the content and messages you see on
other websites you visit. If you do not allow these cookies you may not be able
to use or see these sharing tools.

Back Button


COOKIE LIST



Search Icon
Filter Icon

Clear
checkbox label label
Apply Cancel
Consent Leg.Interest
checkbox label label
checkbox label label
checkbox label label

Reject All Confirm My Choices