Shownotes
In this episode of the Future Proof HR podcast, Jim Kanichirayil, our podcast co-host and executive producer, sits down with Amanda Woodard, Senior Director of HR at Submittable, to unpack what changes when talent acquisition goes hybrid, candidate pools explode, and AI makes it easier than ever for bad actors to slip into your pipeline.
Amanda shares her unconventional path from customer success into TA and HR, and why that revenue-side experience helped her operationalize recruiting like a pipeline, not a reactive process. From there, the conversation zooms into the real-world tension HR teams are facing right now: opening up remote hiring to access better talent, while also tightening controls to prevent fraud, deepfakes, and identity mismatches that can put the business at risk, especially in highly regulated environments.
She breaks down the practical systems her team uses to protect candidate quality without killing candidate flow, including multi-step ID verification, digital footprint checks, geolocation signals, and reference validation that focuses less on “good feedback” and more on authenticity. Along the way, Amanda offers a clear-eyed take on the AI hype cycle, why most “AI” tools are actually automation, and what HR leaders can do today while major ATS and background check providers race to build native solutions.
Topics Discussed:
- The shift from onsite recruiting to hybrid hiring, and why competition intensified
- How revenue-side experience can transform TA into a more operational, pipeline-driven function
- Navigating leadership resistance and trust issues during the move to remote work
- Why candidate fraud is escalating, and what it means for HR and TA teams
- Using automation vs. true AI to reduce application review time
- Filtering and reverse-filtering candidates based on skills and signals
- Multi-layer identity verification: digital footprint checks, photo ID gates, and reference validation
- Balancing candidate experience with security and risk mitigation
- Why transparency in the process reduces candidate drop-off
- What TA leaders should implement now, regardless of industry, to reduce hiring risk
If you are an HR or Talent Acquisition leader trying to keep hiring quality high in a hybrid world where AI-driven fraud is becoming more common, this episode offers a practical look at how to build tighter safeguards without losing trust, speed, or the ability to compete for strong candidates.
Additional Resources:
*Note: Amanda was with Submittable at the time of this recording.
Transcripts
The other thing that I think impacted some of our challenges was trying
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to figure out how to create policies and
expectations around what remote or hybrid
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work looked like and balancing having
a leadership team that was like very
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anti remote, even though they knew that
there was something they had to adapt to.
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Jim: When we're talking about AI
in the world of HR and the world of
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talent acquisition, the debate often
becomes, is this going to be an AI
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on autopilot world, an AI empowered
world, or an AI enabled world?
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And where you fall in those buckets can
depend on your personal experiences.
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In today's conversation with
Amanda Woodard, what we're gonna
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do is actually look at how.
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There are two transformations
that had to be navigated in a
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world where an organization was
moving from a fully onsite to a
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hybrid world in the FinTech space.
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And when you think about FinTech
as a sector, this is a sector
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that moves at a glacial pace.
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So the idea of innovating within AI and
the idea of transforming a culture that
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is dominantly onsite to hybrid or remote.
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Is a tough task in and of itself.
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But what happens when you're trying to
make those transformations and at the same
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time you're seeing advances in technology
go a direction which makes it really easy
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for fake candidates to come in through
the pipeline and potentially expose your
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organization to risk and even compromise.
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Those are some real dangers and
risks that need to be examined,
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which creates the case that you need
to have tight processes that allow
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you to capture the highest quality
candidates while still having a decent
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volume of candidate flow that you can
successfully fill the roles that you have.
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This is a story about how AI.
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Is empowering organizations versus
AI that is coming in to take over and
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run the organization on autopilot.
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And the person leading us through
that story is Amanda Woodard.
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She is the senior director
of HR at Submittable.
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Amanda thrives at the
intersection of strategy and
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sarcasm because someone has to.
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She's a setter taco enthusiast,
devoted dog mom, and avid music lover.
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Often spotted at emo and pop punk shows.
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Amanda's built a career out of channeling
anxiety into proactive planning and
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calling it strategy when it all works out.
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Amanda, excited to have you on.
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Welcome to the show.
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Amanda: Thanks so much for having me, Jim.
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Jim: I'm looking forward
to this conversation.
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It's going to be pretty interesting,
especially for me as a former recruiter.
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I think we're going to
get into a lot of areas.
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That's going to be pretty interesting
when we look at it from a TA perspective.
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But before we dive into that, I think
it's important for you to set the stage
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a little bit and share with us a little
bit about your background overall and
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also what we all know the world of talent
acquisition to be and what you've seen
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over the years in talent acquisition.
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And then we'll go from there.
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Amanda: Yeah, sure.
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So high level, a little about me, my
career, interestingly enough, started in
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customer success and account management.
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So I wasn't even an HR
or TA person by trade.
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I happened into it one time when we were
trying to scale for a really large client
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at a company I was working at and it
worked really well and ended up taking
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talent acquisition over at that part.
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Talent acquisition ended up being
the doorway into HR for me and that
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has just carried my career forward
since probably 2018 to where I am
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today where I am a Head of HR for
software company called Submittable.
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When we think about talent
acquisition and where it was when I
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started versus how it's progressed.
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We have probably a few seasons, right?
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There's pre-pandemic when we're
still bringing people in on site,
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at least in my experience, video
interviews were a lot less common.
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And then we have post-pandemic, where that
was all we did for a really long time.
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We saw a ton of people getting
into talent acquisition and
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we had recruiters everywhere.
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And we saw sometimes the market was
up and it was easy to get a job.
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And we've seen where the market was
down and it was difficult to get a job.
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And so I think the way that we strategize
how to get around that looks very
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different than it does for me now.
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We had to do a ton of sourcing strategy.
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We had to be really proactive
about reaching out to candidates
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and making sure that we were
aligning with those ideal profiles.
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It took a lot more planning and dining
to get people to bite and be interested
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in the organization and the role.
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And it was just a lot more proactive.
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And then it has started to shift
where we saw fewer companies hiring.
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We started to see a ton of layoffs.
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We saw that impacting our friends in
the talent acquisition and the HR space.
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And it just dipped from there.
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Jim: Really interesting landscape, Amanda.
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There's several things that caught my
attention as you were talking through it.
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And I think one of the things that
I'm most interested in is going
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back to your origin story where you
came from customer success into HR.
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And that's a unique journey.
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What were your observations moving from
a revenue side of the organization into
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more of an admin or cost center of an
organization making that transition from
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customer success to HR that had to be
a pretty significant change of pace.
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So what were your observations
and how did you apply those
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observations to optimize the function?
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Amanda: I love that question.
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Because it touches on something that
I'm super passionate about, which
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is looking at HR and your people
strategy as a revenue generating
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function, as opposed to being a cost
center, which is viewed traditionally.
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I think because I had so much exposure
to what the revenue process looked
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like from a sales perspective and the
customer lifecycle journey and all of
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the pieces that went into acquiring
a new client and then retaining them.
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A lot of it translated really
nicely into talent acquisition.
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So quite frankly, it was a pretty smooth
transition once I realized that I could
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apply almost all of the processes that
I had for what I was doing on a sales
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side to what I was doing from a TA side.
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It helped.
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Were able to apply a ton of
stuff to our charging strategy.
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We were able to apply it to retention.
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We were honestly like just used it to
operationalize our talent acquisition
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and then our HR practice altogether.
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So it is not a common career progression,
but it is one that has served me
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very well, I think, because I had
that revenue experience and also just
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the business acumen operationally.
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Then a lot of times they think HR people
get robbed of getting exposure to.
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Jim: Interesting.
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So the other thing that caught
my attention was that you've,
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been in HR across sort of three
different areas, pre-pandemic, the
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pandemic era and post-pandemic.
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And as somebody that came out of the
agency recruiting world, I've been
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through those three areas as well.
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And I've also been in the
pre-housing crash, housing crash
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and post-housing crash era too.
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So it seems like people of a certain
age are just dealing with economic
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crashes and figuring that stuff out.
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What I am interested in getting
your perspective on is when you look
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at the pandemic and pre-pandemic
era of talent acquisition, what
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was the typical operating rhythm?
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What were the challenges that you
were dealing with in those two spots
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and how did you respond to those
challenges and adapt your organization
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to meet what was required at the time?
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Amanda: Yeah.
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Pre-pandemic, the organization was
still very much on site and there were
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certain areas of the business that were
geographically dispersed or remote, but
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for the most part, we were all in one HQ
area, which really limited my talent pool.
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So the ways that we would go out and try
to find talent for early career people,
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I literally was walking around Nordstrom
with business cards and handing them out
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to people that I thought had potential for
like early career customer service roles.
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And for some of the more technical roles
where they were able to be remote, I was
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doing weird stuff like Googling phone
system repairs and then calling and trying
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to make relationships with people that had
alignment in the work that we were doing.
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At the time LinkedIn was thing, but
the type of technical talent that I was
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recruiting with voice and data engineers
didn't have a ton of presence on LinkedIn.
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So we had to find different ways
to go out and find that talent.
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It was very much network related,
people network related, and who do
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you know and how can you leverage that
to find other people for those roles?
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And then how do we find people to
take roles that we need on site
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because we had no flexibility there.
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Post-pandemic that flipped kind
of everything, which was great in
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terms of having a much wider tool
of talent that we could talk to.
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But I think one of the areas where the
organization I was with at the time
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really struggled with was figuring
out how to adapt to changing employee
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expectations and requirements.
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And so then it became more challenging
because if you weren't competitive
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with work from home or remote flexible
work, if you had really stringent
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requirements on what do you do if your
kid's in daycare and you work from home?
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Those types of things made it really
difficult to be creative and that impacted
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our sourcing recruiting strategy for sure.
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And then this is also where I started
getting more process focused and
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bringing in some of the stuff that
I had done on a sales team in terms
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creating pipeline and looking at
email campaigns and things like that.
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Really just having to figure
out how to apply those kind of
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technical process drops to like
sourcing and talking to candidates
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that I hadn't struggled with before.
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Jim: Got it.
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So think through what you're describing,
and I can relate to kind of everything
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that you're talking about, when
you're dealing with a primarily onsite
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environment, your talent pool is
restricted to maybe a 20 mile radius
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around where your headquarters is.
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And that has an implication
on your employee.
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value proposition and your
employer value proposition.
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How do you sell a particular role or
a company where you have a commute?
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Now in the pandemic and post-pandemic
area, the implication of having wider
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talent pools is that you get better
overall talent and you have access
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to more talent overall as well.
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And should make the job easier, but it
doesn't really work out that way, does it?
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So tell us a little bit about some of the
things that popped up as we transitioned
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from a mainly onsite, geographically bound
hiring strategy to a hybrid or remote,
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and in some cases, international talent
strategy, what did you start seeing?
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Amanda: Competition got so fierce.
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Which did surprise me because
now everybody has access
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to a wider talent pool.
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And so you would think that there would
be great talent to go around for everyone.
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But as is with the case we've now,
people want to work for great companies
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and benefits and total compensation
packages and all of those things are
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contributing factors to what that looks
like for an employee when they take a job.
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And so if you are not a fang company
and you're in the tech space and maybe
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you're a small voice and data provider
and you're not Accenture, like you can't
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compete with some of the things like from
a compensation or benefit standpoint that
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those other organizations can't either.
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The other thing that I think impacted
some of our challenges was trying to
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figure out how to create policies and
expectations around what remote or hybrid
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work looked like and balancing having
a leadership team that was like very
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anti remote, even though they knew that
there was something they had to adapt to.
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And so there was very much the sense
of like control that was perceived
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as we don't trust our employees.
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And that made it really difficult for us
to be competitive in the talent landscape
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as well, because people would have
questions about flexible work and just
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work life balance and all of those things.
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And that was another area where we
really struggled to compete at first
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because it was very much like, okay,
yes, you can work from home, but you are
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expected to be in your chair from 7 a.m.
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to 4 p.m.
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and your little green dot has to be
on and if we can't ping you, then it's
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probably because you're mowing the lawn.
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And so that was something that also
ended up working against us where we
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were trying to influence something
that was happening to the business
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operationally, but was directly impacting
our ability to attract top talent.
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Jim: So it's interesting that you're
navigating both a talent strategy
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transformation, and it sounds
like you had to navigate sort of
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a cultural transformation as well.
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Because oftentimes what I've found in
talking with other HR leaders is that
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those organizations that have senior
and executive leadership that pushes
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back against remote or hybrid structures
usually have some gaps in terms of overall
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leadership style and competency and
management style and competency as well.
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Looking back at that time,
is that what you observed?
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And if it is what you observed,
how did you actually triage that
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aspect of organizational challenge
while at the same time dealing
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with the talent sourcing strategy
transformation that you're dealing with?
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Amanda: Yeah, I think
there's a few things there.
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One of the things that I did not
connect back then that I wish I
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would have was honestly generational
differences in work styles.
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I definitely uncovered some
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new leadership gaps in some areas
where needed to tighten up and
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we'll talk about that in a second.
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But I don't know that it's always
fair to put everyone in that bucket
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when a lot of it sometimes is simply
perception because of a generation.
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And so at the time all of
our C-suite were Boomers.
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Our senior leadership was Gen X and
then we didn't have the millennials
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in the workforce quite yet.
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So the rest of us were Millennials and
we were still super entitled and we had
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these like preconceived notions of that.
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And so I think a lot of
it was generational and I
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still run into that today.
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But one of the other things that
we did uncover is just how much
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micromanagement was happening.
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And as a result of that, was just
like surprising how much we realized
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our productivity was being impacted.
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And it really was like
a top-down trust issue.
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And
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one of the challenges that created for me
was when we would go to open a new role,
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getting approval to have it be on site
versus remote, if it had traditionally
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been on site, is really where we
started to untangle all of those things.
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And so that's where we started having
the, like the conversations of,
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but why does it have to be on site?
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What are you worried about that
it isn't going to be successful.
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Doing some pros and cons and at
the time I was also responsible
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for learning and development.
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So that also was like, okay, we need to
do some work on our middle management,
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leadership foundations and building trust.
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And then I needed to be able to
leverage my influence to say, okay,
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just let me try this a couple of times.
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And if it's successful.
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Then we can reevaluate
how we make that decision.
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And if it's not, then we'll just go
back to doing it the way you want it.
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And we were able to make it
successful for the most part.
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Jim: So it's interesting that you're
describing this and I'm hearing a
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little bit of risk that you're taking
because you're sticking your neck
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out and trying to fight the dominant
culture within the organization that's
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resistant to this sort of change.
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And you finally get momentum
in the right direction.
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But the thing that I think about
is even before you're dealing with
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heavy remote staff, was running a
agency recruiting firm for a metro
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market and all of our candidates were
generally within the metro market area.
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But there would be people
that had 40 minutes commutes
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into where we were located.
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So we would just take a remote interview
that way instead of having them come in.
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But even in those instances, we ran
into issues where people were having
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stunt doubles in those environments
and you would get a different person
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showing up in the interview process,
even in those local environments.
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So you've gotten momentum and stuck
your neck out and you've gotten some
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buy-in to move people in the direction
of opening up the candidate pool,
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being more open to remote candidates.
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But even in an environment where you
were interviewing more locally, you
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still had to have strong processes
in there that you could vet out
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candidates on a real basis and validate
that their skills met the role.
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How did you navigate that challenge in
a more remote recruiting environment
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where that becomes a lot tougher?
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What did you encounter and
what did you do to combat that?
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Amanda: We learned a lot of lessons
along the way, I can tell you that.
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We learned quickly that leveraging
video over phone calls whenever possible
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was something that was important.
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00:19:05,338 --> 00:19:11,898
I learned that candidates didn't
really know immediately how to
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be part of a remote
interview at the beginning.
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So in some ways I felt like we
were also training candidates on
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how to show up for an interview.
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And then we also had to just really adjust
the way that we looked at structural
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interviews and get really smart about the
behavioral questions that we were asking.
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And that is also about the time when
we started implementing like online
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00:19:48,598 --> 00:19:52,828
technical assessments or any sort of
like testing that we would have for
287
00:19:53,358 --> 00:20:00,268
technical roles to give us a good
indication of skill proficiency, which
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00:20:00,278 --> 00:20:04,628
at the end of the day, honestly, gave
us a better indication of whether or
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00:20:04,628 --> 00:20:07,814
not someone was going to be successful
in the role prior to what we were doing
290
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when it was in person and more intuitive.
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00:20:12,728 --> 00:20:17,528
Jim: So you put more process in, but I
want to wind back just a little bit into
292
00:20:17,528 --> 00:20:19,878
what led to those processes being put in.
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00:20:20,248 --> 00:20:24,798
Because one of the things that I
encountered at the beginning of the
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00:20:24,798 --> 00:20:29,548
pandemic and even before that is that
when we would have virtual interviews with
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00:20:29,548 --> 00:20:34,228
candidates that weren't geographically
limited to our area, you would often
296
00:20:34,228 --> 00:20:39,258
have one person on camera and somebody
else like feeding answers or acting as
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a stunt double or something like that.
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So to the point where we had
instances where people who showed
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00:20:45,118 --> 00:20:47,868
up at the work site were different
than the ones that we interviewed.
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00:20:48,488 --> 00:20:53,868
So when you expand that out from a virtual
interview setting, did you experience
301
00:20:53,868 --> 00:20:57,758
that and what sort of controls did you
put in as a result to mitigate the risk
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00:20:57,758 --> 00:21:00,978
of somebody showing up that wasn't the
actual person that you interviewed?
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00:21:02,168 --> 00:21:07,018
Amanda: It's funny that you ask
that because I think for whatever
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00:21:07,018 --> 00:21:12,218
reason, we were extremely lucky that
in my entire career, we never had
305
00:21:12,218 --> 00:21:20,618
that happen, either with on-site or
remote people or even across multiple
306
00:21:20,748 --> 00:21:22,298
organizations that I've worked for.
307
00:21:22,638 --> 00:21:30,843
And you saying that just really reinforces
that I was way too trusting for a
308
00:21:30,843 --> 00:21:34,413
long time because I wasn't even aware
that was something that was happening.
309
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Until very recently, when we started
hiring quite a bit again, and we were
310
00:21:41,083 --> 00:21:45,413
just completely overwhelmed and inundated
with the number of candidates that we
311
00:21:45,413 --> 00:21:48,023
were receiving for some of our open roles.
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00:21:48,783 --> 00:21:53,183
And at that point we were like, okay,
we have to pivot our strategy again.
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We're a small team.
314
00:21:54,443 --> 00:21:57,433
We don't know how to get through
all of these applications.
315
00:21:57,433 --> 00:22:02,023
I started kind of asking around in some
different forums that I am a part of like,
316
00:22:02,633 --> 00:22:04,453
what are some things that you guys can do?
317
00:22:04,453 --> 00:22:06,793
Like, how are you leveraging
AI to get through this?
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00:22:07,273 --> 00:22:12,833
And while we did figure that out, one
of the other things that came up was
319
00:22:12,843 --> 00:22:18,903
someone shared an FBI article with me
about just bad actors that were posing
320
00:22:18,923 --> 00:22:25,103
as candidates and then turning laptops
or company access over to North Korea.
321
00:22:25,453 --> 00:22:29,603
There's recently a Forbes article
talking about this as well.
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00:22:29,903 --> 00:22:34,393
There's tons of just different
aspects of fraudulent activity that
323
00:22:34,393 --> 00:22:39,673
is occurring today above and beyond
just the typical 25 % of people
324
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lay on their resume type of thing.
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And it's scary.
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Thomas Kunjappu: This has been
a fantastic conversation so far.
327
00:22:46,847 --> 00:22:49,637
If you haven't already done so,
make sure to join our community.
328
00:22:49,877 --> 00:22:52,547
We are building a network of the
most forward-thinking, HR and
329
00:22:52,547 --> 00:22:55,727
people, operational professionals
who are defining the future.
330
00:22:56,207 --> 00:22:58,817
I will personally be sharing
news and ideas around how we
331
00:22:58,817 --> 00:23:00,827
can all thrive in the age of ai.
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00:23:01,187 --> 00:23:04,172
You can find it at go cleary.com/cleary
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00:23:04,602 --> 00:23:05,212
community.
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00:23:05,837 --> 00:23:06,677
Now back to the show.
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Jim: So when you have a couple of these
things that are popping up at a national
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level, where you're talking about foreign
bad actors, potentially compromising
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00:23:17,294 --> 00:23:22,664
internal systems with fake candidates
and whatnot, but you referenced there,
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there are ways that you can leverage
AI as a countermeasure against that.
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So what are some of the things
that you've learned or done
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to combat the risk of that?
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Amanda: Yes.
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00:23:35,214 --> 00:23:36,954
So first I'm going to
start with a hot take.
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Everybody has been completely
inundated with everyone in their
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00:23:41,644 --> 00:23:45,684
leaked in messaging, getting blown
up about, we have AI to do this.
345
00:23:45,684 --> 00:23:46,624
We have AI to do that.
346
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And let's be real, most of the time
it's not AI, it's just automation.
347
00:23:50,444 --> 00:23:54,424
And I'm not knocking automation
because that has saved my
348
00:23:54,424 --> 00:23:55,884
biscuits like a ton of time.
349
00:23:55,884 --> 00:23:59,454
But let's be clear automation
and AI are not the same thing.
350
00:23:59,909 --> 00:24:06,419
One of the things that we have done,
we was filtering and reverse filtering,
351
00:24:06,429 --> 00:24:09,099
which isn't really an AI thing.
352
00:24:09,109 --> 00:24:14,389
But being able to then score the
candidates based off of skills and
353
00:24:14,399 --> 00:24:17,689
things that are on their resume or
not on their resume is one thing
354
00:24:17,689 --> 00:24:19,459
that we were able to leverage AI for.
355
00:24:19,709 --> 00:24:23,359
And that significantly reduced the
amount of time that we had to spend
356
00:24:23,359 --> 00:24:25,359
just in the application review part.
357
00:24:25,769 --> 00:24:30,199
There are some other more tactical
old school things that we actually
358
00:24:30,199 --> 00:24:34,689
implemented to help encourage people
not to apply if they were fake.
359
00:24:34,689 --> 00:24:38,559
Like having, taking away easy apply
on LinkedIn, for example, and making
360
00:24:38,559 --> 00:24:42,329
people actually fill out an application
and having the application have drop
361
00:24:42,329 --> 00:24:45,569
downs and check boxes and long texts
and short texts so that it would be
362
00:24:45,619 --> 00:24:47,499
more difficult for a bot to fill it out.
363
00:24:48,619 --> 00:24:51,549
And then keyword search, like I mentioned.
364
00:24:51,609 --> 00:24:54,379
One of the other things that we
would do is reverse keyword search.
365
00:24:54,379 --> 00:24:55,499
So if there were.
366
00:24:55,914 --> 00:25:01,084
specific skills or specific parts of a
tech stack or something that we wanted
367
00:25:01,084 --> 00:25:04,594
to look for that maybe wasn't included
in the job description, we would search
368
00:25:04,594 --> 00:25:09,694
for those and then aggregate that versus
what we had done from our original filter
369
00:25:10,084 --> 00:25:13,884
to try to get down to viable candidates.
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00:25:14,454 --> 00:25:16,744
Jim: So that's at the application stage.
371
00:25:16,854 --> 00:25:21,954
What changes or processes did you
implement at the interview stage to make
372
00:25:21,954 --> 00:25:24,124
sure that candidate quality remained high?
373
00:25:24,854 --> 00:25:29,199
Amanda: Yeah, so now we have
multiple levels of ID verification
374
00:25:29,684 --> 00:25:33,729
and you think of it as multiple
gates as you go through the process.
375
00:25:33,764 --> 00:25:39,049
The first gate is a digital
ID footprint verification.
376
00:25:39,449 --> 00:25:43,139
And so that's just taking basic
information, name, phone number,
377
00:25:43,159 --> 00:25:48,799
email address, and cross-referencing
against your digital profile
378
00:25:48,799 --> 00:25:50,609
experience, if you will.
379
00:25:50,949 --> 00:25:54,219
Checking for things like
what is your phone carrier?
380
00:25:54,299 --> 00:25:59,559
Is your email actually an email that is
connected to something else that you would
381
00:25:59,559 --> 00:26:01,869
use on an application in the internet?
382
00:26:01,869 --> 00:26:07,689
Do you have consistent activity
that you would expect to see with a
383
00:26:07,889 --> 00:26:11,449
real human on things like LinkedIn?
384
00:26:11,849 --> 00:26:13,279
And then looking at geolocation.
385
00:26:13,299 --> 00:26:15,079
So you told me you were in Ohio.
386
00:26:15,099 --> 00:26:17,899
Does your IP address actually
reflect that you're in Ohio?
387
00:26:18,479 --> 00:26:25,519
Now, we don't get the readout on all of
who your cell phone carrier is or what
388
00:26:25,979 --> 00:26:28,009
apps or accounts you have or any of that.
389
00:26:28,009 --> 00:26:31,969
That's not important, but really what
we're looking for is like a authenticity
390
00:26:31,969 --> 00:26:36,199
score that says based off of everything
we see and can scrape from the internet,
391
00:26:36,639 --> 00:26:38,099
it looks like you are who you say you are.
392
00:26:39,479 --> 00:26:44,839
The second gate is where we do
like a photo ID verification.
393
00:26:45,319 --> 00:26:48,949
And that comes across as a link
before you do a video interview.
394
00:26:48,949 --> 00:26:51,826
So at this point, a candidate would
have gone through application and your
395
00:26:51,889 --> 00:26:55,389
recruiter screen, and now they're probably
going to talk to a hiring manager.
396
00:26:55,649 --> 00:26:56,939
They're somewhere in the interview loop.
397
00:26:57,439 --> 00:27:00,699
And it's just a link before they
join a Google Meet, and then they're
398
00:27:00,699 --> 00:27:05,259
asked to show a picture of a photo
ID, any sort of government issued ID.
399
00:27:05,609 --> 00:27:10,319
And then we have a third party system
that will run that through and check
400
00:27:10,319 --> 00:27:12,489
to make sure that it's not fake.
401
00:27:13,149 --> 00:27:17,019
That the person in the photo ID is also
the person being represented on the video.
402
00:27:17,589 --> 00:27:21,969
That has, I think, helped us
get away from having to do some
403
00:27:21,969 --> 00:27:24,969
of the awkward deep fake tests.
404
00:27:25,099 --> 00:27:28,489
Like I call it the John Cena when
you're trying to make sure that
405
00:27:28,489 --> 00:27:32,129
you don't see someone having a
face overlay that's not theirs.
406
00:27:32,849 --> 00:27:35,169
The third check is a reference check.
407
00:27:35,659 --> 00:27:39,699
Obviously, like we do care about like
past performance, but also everyone knows
408
00:27:39,719 --> 00:27:40,869
that no one's going to give a reference.
409
00:27:40,879 --> 00:27:41,659
So it's a bad reference.
410
00:27:41,669 --> 00:27:46,759
So what we're really looking for in that
situation is that the contact information
411
00:27:46,759 --> 00:27:53,949
that we've been given matches the
organizations that are on the candidate's
412
00:27:53,949 --> 00:27:55,339
resume where they said they worked.
413
00:27:55,879 --> 00:27:59,809
And then we're also doing a side-by-side
comparison of geolocation like that.
414
00:28:00,329 --> 00:28:07,239
For example, maybe we would run into
someone who has multiple email addresses
415
00:28:07,249 --> 00:28:14,529
and they are their own reference and to
try to get around it, they talk to us
416
00:28:14,529 --> 00:28:20,489
on iPhone and they email us from a PC.
417
00:28:20,499 --> 00:28:24,579
But their IP address is all similar
or the same so we know that they're
418
00:28:24,579 --> 00:28:26,839
in the same like geolocation.
419
00:28:26,839 --> 00:28:31,639
Or maybe one or all of them are
not in the geolocation at all.
420
00:28:31,639 --> 00:28:36,199
Maybe they said that they were in Utah
and they are in fact in Bangladesh.
421
00:28:36,434 --> 00:28:40,819
And so those are some other areas
that we get some insight into.
422
00:28:41,089 --> 00:28:42,889
And then the last step
is a background track.
423
00:28:44,619 --> 00:28:51,989
Jim: So when I hear all of this, some of
this sounds like pre-hire, some of this
424
00:28:51,989 --> 00:28:58,349
sounds like it might be conditional to
hire, but I'm listening to the steps and
425
00:28:58,349 --> 00:29:00,039
I get it from the employer side of it.
426
00:29:00,059 --> 00:29:04,109
I'm thinking about it from the
candidate side and I can't take my
427
00:29:04,109 --> 00:29:06,029
recruiter agency recruiter hat off.
428
00:29:06,554 --> 00:29:07,749
I'm thinking about two things.
429
00:29:08,209 --> 00:29:10,389
Candidate experience has got to be rough.
430
00:29:11,129 --> 00:29:14,599
There's it's triggering
my creep factor alert.
431
00:29:14,609 --> 00:29:18,169
Hey, this is really intrusive and I
don't even know if I have a job yet.
432
00:29:18,179 --> 00:29:22,329
You're giving me a full
out like NSA check.
433
00:29:22,749 --> 00:29:28,449
And then the third part of it is all
of the benefits that you get from being
434
00:29:28,449 --> 00:29:33,609
a remote or hybrid organization, being
able to recruit from bigger talent pools.
435
00:29:34,209 --> 00:29:38,649
That shrinks it back down because
a lot of people are, even if they
436
00:29:38,649 --> 00:29:41,589
are viable candidates, which there's
going to be a good chunk of viable
437
00:29:41,589 --> 00:29:44,599
candidates are going to be like,
I'm not going through all of that.
438
00:29:44,609 --> 00:29:45,589
Screw this place.
439
00:29:46,039 --> 00:29:57,089
So how did you balance the need for proper
process while still maintaining a decent
440
00:29:57,089 --> 00:29:59,059
enough candidate flow to justify that?
441
00:29:59,059 --> 00:30:01,669
Hey, one of the big reasons why
we want to go remote is have a
442
00:30:01,679 --> 00:30:03,299
bigger access to a candidate pool.
443
00:30:04,629 --> 00:30:04,959
Amanda: Yeah.
444
00:30:05,429 --> 00:30:07,579
It seems so creepy, right?
445
00:30:07,719 --> 00:30:12,719
I think honestly like that's still
something that I am still struggling
446
00:30:12,719 --> 00:30:16,974
with a little bit because I put myself,
if I were a candidate, are those
447
00:30:16,974 --> 00:30:19,064
steps that I would want to go through.
448
00:30:19,519 --> 00:30:22,484
It doesn't feel great to be going
through an interview process and
449
00:30:22,484 --> 00:30:27,954
to feel like I'm already like
not trusted or like illegitimate.
450
00:30:27,954 --> 00:30:34,854
For us, honestly, what we do is we
talk candidates through it upfront and
451
00:30:34,854 --> 00:30:36,704
we're just very transparent about it.
452
00:30:37,154 --> 00:30:43,154
So we have information on our careers
page and in the job application process
453
00:30:43,164 --> 00:30:46,124
that like, this is our stance on AI.
454
00:30:46,124 --> 00:30:47,144
These are our guidelines.
455
00:30:47,144 --> 00:30:48,734
This is when it's okay to use it.
456
00:30:48,734 --> 00:30:50,464
This is when it's not,
this is how we use it.
457
00:30:50,954 --> 00:30:55,554
And then similarly, because of the
nature of our business and because
458
00:30:55,554 --> 00:30:59,634
we want to protect our clients and
our employees and because of the
459
00:30:59,844 --> 00:31:06,634
landscape today, we're gonna have
multiple layers of ID verification.
460
00:31:07,124 --> 00:31:11,804
And so far, I haven't had
anyone tell me to pound sand.
461
00:31:12,074 --> 00:31:14,284
I'm sure it's coming,
but so far it hasn't.
462
00:31:14,284 --> 00:31:18,094
So we talk about it, it's there in the
application process for you to review.
463
00:31:18,354 --> 00:31:20,644
We also talk about it quite a
bit in the phone screen process.
464
00:31:20,919 --> 00:31:23,784
And I think one of the things
that's been able to help us
465
00:31:25,824 --> 00:31:32,334
lessen the intensity feeling of it is by
connecting why we are doing this process
466
00:31:32,364 --> 00:31:36,564
back to how it could impact the business.
467
00:31:37,019 --> 00:31:43,514
And so for example, my company is
shuffling billions of dollars around on an
468
00:31:43,524 --> 00:31:46,734
annual basis through government funding.
469
00:31:47,204 --> 00:31:51,384
When candidates hear really big
numbers like that and they are able
470
00:31:51,384 --> 00:31:56,114
to understand like, yeah, the type of
information that I could potentially
471
00:31:56,114 --> 00:32:00,084
have access to could be detrimental
if it were in the hands of a bad guy.
472
00:32:00,684 --> 00:32:03,404
I think it doesn't make it any
less intense, but it's okay.
473
00:32:03,404 --> 00:32:06,664
Yeah, I can get my head wrapped
around that, and this is like a
474
00:32:06,664 --> 00:32:08,234
standard protocol that makes sense.
475
00:32:08,254 --> 00:32:12,684
And if I were applying for any fintech
company, I should probably expect
476
00:32:12,694 --> 00:32:14,054
to see something along those lines.
477
00:32:15,314 --> 00:32:16,989
Jim: So I want you to
zoom out a little bit.
478
00:32:17,769 --> 00:32:23,669
So we've been really heavy in sort of the
specific use case that you've been talking
479
00:32:23,669 --> 00:32:29,319
about your company within that sector
in the age of post-pandemic hybrid and
480
00:32:29,319 --> 00:32:33,469
remote work and how you actually navigate
that environment where there is a lot
481
00:32:33,469 --> 00:32:36,679
of candidate side potential for fraud.
482
00:32:37,569 --> 00:32:42,109
So when you look at all of the things
that you can do from a candidate
483
00:32:42,109 --> 00:32:48,179
perspective to game the system and you're
advising other TA leaders and other
484
00:32:48,559 --> 00:32:52,789
HR leaders about systems of control
that you want to put in place in the
485
00:32:52,789 --> 00:32:54,799
age of AI and the age of deep fakes.
486
00:32:55,339 --> 00:33:00,899
What are the key action items that you
would recommend for those folks to have
487
00:33:00,899 --> 00:33:08,099
in place, regardless of sector, to make
sure that they are getting who appears to
488
00:33:08,109 --> 00:33:13,319
be, they're getting the same person that
they're looking at on paper in person.
489
00:33:13,549 --> 00:33:14,359
Amanda: That's a great question.
490
00:33:14,359 --> 00:33:19,724
I think the good news here is a lot
of the main, like the biggest ATSs
491
00:33:19,774 --> 00:33:23,364
are like already reacting to this.
492
00:33:23,694 --> 00:33:31,534
There is already going to be opportunities
to help combat this innately, likely
493
00:33:31,544 --> 00:33:33,664
in tech techs that we're already using.
494
00:33:34,184 --> 00:33:38,784
So if you are running background
checks, we use Checker and they are
495
00:33:38,824 --> 00:33:43,184
getting ready to launch something that
does a lot of what I just described as
496
00:33:43,184 --> 00:33:45,544
part of the background check process.
497
00:33:45,994 --> 00:33:48,374
Greenhouse announced a
partnership with Clear.
498
00:33:48,554 --> 00:33:53,734
There's a few others that are in
the works and higher might be one.
499
00:33:54,224 --> 00:34:00,414
And I think a lot of that will include
some sort of biometric scan during
500
00:34:00,414 --> 00:34:03,284
part of the video interview process.
501
00:34:03,294 --> 00:34:08,884
So I think the good news is that the
tools that we use on a day-to-day basis
502
00:34:09,514 --> 00:34:16,714
to help us hire top talent is reacting
quickly and trying to get tools out there
503
00:34:16,714 --> 00:34:18,184
that we can use that help combat this.
504
00:34:18,184 --> 00:34:21,914
So you don't have to do
quite so many manual steps.
505
00:34:22,504 --> 00:34:27,494
In the meantime, I do think that anything
that you can do to try to qualify or
506
00:34:27,494 --> 00:34:33,679
disqualify talent through the application
process, leveraging filters and skills.
507
00:34:33,679 --> 00:34:36,688
And if you can do candidate
scoring, I think that's a great
508
00:34:36,688 --> 00:34:38,978
way to help optimize the process.
509
00:34:39,474 --> 00:34:44,264
And you will find very quickly if you're
not already doing this to how much
510
00:34:44,603 --> 00:34:46,074
just fake stuff is already out there.
511
00:34:46,074 --> 00:34:50,204
For example, I've never seen so
many resumes from folks that have
512
00:34:50,254 --> 00:34:54,974
PhDs in petroleum engineering
from the University of Cameroon.
513
00:34:55,353 --> 00:34:56,974
They must have a really strong program.
514
00:34:57,123 --> 00:34:59,344
I don't know why they want to be
software engineers, but there you go.
515
00:34:59,824 --> 00:35:01,794
So that's early on in the process.
516
00:35:02,124 --> 00:35:06,394
And then I think some sort of
ID verification is important.
517
00:35:06,584 --> 00:35:11,304
Whether you re-implement reference
checks of some kind or background
518
00:35:11,304 --> 00:35:12,864
checks if that's part of your process.
519
00:35:13,144 --> 00:35:19,104
I think something along those lines
needs to be part of the process now.
520
00:35:19,524 --> 00:35:24,264
Even if you don't have access to check
like geolocation and IP addresses and
521
00:35:24,264 --> 00:35:31,124
things like that, there is some kind of
fishy behavior that these folks typically
522
00:35:31,124 --> 00:35:33,504
will let on throughout the process.
523
00:35:33,894 --> 00:35:38,194
And so I think just knowing that they're
going to have to go through those steps
524
00:35:38,474 --> 00:35:43,964
is going to help deter the ones that maybe
aren't super proficient professionals
525
00:35:43,984 --> 00:35:47,034
in the fraud space quite yet.
526
00:35:48,444 --> 00:35:49,919
Jim: Yeah, that's great advice.
527
00:35:49,919 --> 00:35:53,449
And then think the one thing that I would
throw out there, that's more of an analog
528
00:35:53,459 --> 00:35:56,209
process is to go really old school.
529
00:35:56,779 --> 00:36:00,589
And when you're interviewing
people, interview using the
530
00:36:01,059 --> 00:36:07,099
outcome based recruiting questions
that Lou Adler is famous for.
531
00:36:07,169 --> 00:36:11,119
And that helped me catch a lot of
people that were trying to like
532
00:36:11,369 --> 00:36:13,979
fluff their resume with stuff
that they didn't actually do.
533
00:36:14,459 --> 00:36:16,679
This has been a great
conversation and I appreciate
534
00:36:16,679 --> 00:36:17,839
you hanging out with us, Amanda.
535
00:36:17,849 --> 00:36:20,299
If people want to continue the
conversation, which I'm pretty
536
00:36:20,299 --> 00:36:23,389
sure they will, what's the best way
for them to get in touch with you?
537
00:36:24,359 --> 00:36:25,299
Amanda: I am on LinkedIn.
538
00:36:25,919 --> 00:36:26,829
Come find me there.
539
00:36:26,849 --> 00:36:31,419
And I would be more than happy to
continue to nerd out on this stuff.
540
00:36:32,459 --> 00:36:32,989
Jim: Awesome stuff.
541
00:36:33,039 --> 00:36:36,609
It's been a great conversation and
I could probably talk about this
542
00:36:36,609 --> 00:36:39,479
stuff for two hours because you never
really stopped being a recruiter.
543
00:36:39,889 --> 00:36:45,999
When I think back, over the course of
this conversation, the key question that
544
00:36:46,019 --> 00:36:51,669
we are thinking about is what does, what
do TA organizations, talent acquisition
545
00:36:51,669 --> 00:36:54,439
organizations need to do in the age of AI?
546
00:36:54,839 --> 00:36:59,989
Because the ability to fake a candidate
to get access to your environment
547
00:36:59,989 --> 00:37:01,129
is only going to get better.
548
00:37:01,699 --> 00:37:06,319
And I think the biggest thing that
stands out from this conversation is
549
00:37:06,319 --> 00:37:13,039
that you need to get over the ickiness
of being of treading the line of being
550
00:37:13,039 --> 00:37:16,549
creepy, because you have to understand
what your business objectives are.
551
00:37:16,559 --> 00:37:21,039
And you also have to keep an eye on
the customers that you serve and the
552
00:37:21,079 --> 00:37:26,099
impact of a breach on those customers
because you have a loose process.
553
00:37:26,649 --> 00:37:31,689
So when you frame it in that perspective,
I think the important things that come
554
00:37:31,689 --> 00:37:35,919
out of the conversation is that if you
want to bridge the gap between candidate
555
00:37:35,919 --> 00:37:38,859
experience and having a tight process.
556
00:37:39,499 --> 00:37:45,139
Being upfront and transparent is going
to go a long way in people being able to
557
00:37:45,139 --> 00:37:49,579
swallow the steps that they have to take
to get in position to have a role there.
558
00:37:50,049 --> 00:37:53,699
Connecting the why of the business
to the what and the how that you're
559
00:37:53,709 --> 00:37:55,199
doing and the process that's there.
560
00:37:55,199 --> 00:37:56,309
That's going to be important to you.
561
00:37:56,309 --> 00:37:59,589
And I don't make a habit of
sounding like Simon Sinek.
562
00:37:59,669 --> 00:38:01,199
This is an HR conversation.
563
00:38:02,139 --> 00:38:03,259
He goes with the territory.
564
00:38:04,079 --> 00:38:07,089
So when you're striking that balance
between candidate flow and candidate
565
00:38:07,089 --> 00:38:11,879
quality, it's always makes sense to err on
the side of candidate quality, because if
566
00:38:11,879 --> 00:38:16,129
you're just focusing on the quantity side,
you open yourself up to a lot of risk.
567
00:38:16,419 --> 00:38:20,279
So learned a lot in this conversation
or appreciate you sharing that with us.
568
00:38:20,529 --> 00:38:23,759
For those of you who have hung out with
us and listened to this conversation,
569
00:38:23,759 --> 00:38:27,649
make sure you leave us a review on your
favorite podcast player, and then tune
570
00:38:27,649 --> 00:38:32,229
in next time where we'll have another
HR leader sharing with us how they
571
00:38:32,229 --> 00:38:35,759
plan on responding and transforming
the HR function in the age of AI.
