Name: Hirevue Webinar: Cheating Mitigation and Candidate Experience in the Era of AI in Hiring
Uploaded: 2026-10-07T17:16:14.805Z
Duration: 58 min 44 s
Description: Hirevue Webinar: Cheating Mitigation and Candidate Experience in the Era of AI in Hiring

Transcript for "Hirevue Webinar: Cheating Mitigation and Candidate Experience in the Era of AI in Hiring": Alright. Welcome, everyone, and thank you so much for joining us today. We are excited to spend the next hour with you talking about the growing concerns around candidate... How to really protect both the integrity in your hiring process as well as your all important candidate experience. Here's the panel that we're gonna have joining us today. My name is Tracy Clemente. I'm a product marketing director over at HireVue, and I'll be moderating the discussion today. With me, I have Marcy Daniel, who's our chief product officer at HireVue. A little later on, we'll hear from Annie Henschel, who's a senior director of product management at HireVue. But also joining our discussion today is Stella Ioanidu, who is a senior resource director from the Josh Bersin Company. Before we get started, I just wanna do a quick introduction of HireVue for anyone who's not familiar. HireVue is AI hiring technology that helps to reveal proven skills and capabilities so that you can make confident talent decisions. And that's why our mantra is up there, which is we don't guess, we validate. And what we mean by that is that we understand that making the right hiring decision is not only of critical importance to your business, but it's also, in the market that we're in today, really hard. And we don't want our customers or talent teams out there guessing based on, you know, unreliable signals like resumes or web scraping and inferred skills. We wanna replace that with science backed, AI powered evidence throughout your entire hiring journey. And we're proud to say that we are trusted, and we are doing that by just over 40% of the Fortune one hundred today. So the first thing I wanna do is a quick poll to get a sense of kind of where everybody is at in the audience. So the question is really, have you encountered suspected candidate fraud or AI misuse in the last twelve months? And so just choose the answer that really kind of best fits your experience, kind of what you and your team have been experiencing. You can find that in that poll, tab. You see a little red dot there if you'd like to answer that for us, and we'll just give it a few seconds for everybody to answer. And then, Chris, if you wanna bring up your... Oh, fantastic. Alright. So it looks like we have just just over a third right now are saying that, like, yes. Absolutely. They're a 100% sure that they've had. And just almost half have said, like, I'm pretty sure, but I haven't 100% been able to prove it. And I would say as well that this definitely matches what we're hearing from our customers and what we have seen in our research as well. So if we can go back to the slides. Thank you. And I think it really reflects what we're seeing in the market today as well. There have been plenty of headlines as late really covering the scale of things that we're seeing, Things like AI generated resume fraud. You know, we're hearing from recruiters that they are just being flooded with with what seems like fraudulent resumes to the point where they really can't sort through all of it, and it's becoming a real systemic and widespread issue, not just something that we're seeing on the edge cases. And we're also seeing a real issue around the signal to noise problem. You have so many candidates are using AI to really make sure their resume is matching that job description and is written just as as well as can be. But what that's creating for hiring teams is a market where a lot of candidates really look equally strong on paper. And so it's getting harder and harder to distinguish, like, who genuinely, is gonna have the skills to do that job or who might be more of, like, on the fraudulent side of things. We're even seeing cases of state sponsored fraud from companies like North Korea, I believe, was the Washington Post that reported about this. But they have assembled a documented network of fraudulent software engineers that are really operating at scale, able to infiltrate banks, insurance companies, and other employers that have these remote hiring processes. And so what that's really doing in the end is creating this trust deficit, between candidates and hiring teams. So you have a, you know, a minority of job seekers that are really trusting AI right now to select the most qualified applicants. You know, nearly 80% of them want transparency about if you're using AI in your hiring process, and if so, how is it being used? And then we have nearly 60% of recruiters that are using AI for sourcing and screening and nurturing. And so what we're now operating in is this, you know, AI mediated environment where fraud can really operate at scale. So with all that said, I think let's let's get into it. So, Stella, I'm gonna start with you. Talked about AI there. How has AI really changed the nature and scale of candidate cheating and fraud, and which development should talent leaders really be paying closest attention to right now? Yes. And I think it's important that we start there and we kind of map out the landscape because there definitely is a spectrum through which you can see, candidates trying to, I don't wanna go into misrepresent yet, but polish how they appear in front of, employers. And, of course, this is not new. Every candidate in the history of, you know, recruitment and, talent acquisition wishes to present the best version of themselves in the best possible way and to be perceived as the ideal candidate and actually progress into the talent acquisition journey. But where does it stop being a goodwill type of, activity, and when does it begin to be, like, a fraudulent, behavior or a bad actor? And we've definitely seen it all. We've seen, for example, from, all sorts of, across the hiring, life cycle in the application intake, in the resume screening, and with AI published, as you also said, in fabricated resumes. We've seen, stolen and synthetic identities being used. We've seen deepfakes, meaning completely artificially intelligence generated avatars, playing the role of the interviewee. We've seen, proxy interviewees having, like, a friend of mine or someone else taking the test for me. We've seen coast and coordinated references. We've seen misrepresented background files. We've also even seen, cases that people show up on the first day of work, and they're not who appeared to be during the entire recruitment life cycle. So it... I mean, it was never a boring day in talent acquisition, but with candidate fraud, it definitely is a spectrum of what can go in a way that we are not necessarily able to, contain, and it significantly impacts the trust and the... Even at the end of the of the journey, if they're being caught, it still impacts the employer brand. So, definitely, vulnerabilities of organizations and our solutions and our... Of approaches differ by, by stage. We are seeing the candidate fraud market expanding in a sense that the scenarios that we're, now capturing are becoming even, you know, more, let's say, deliberate, more intricate, more intelligent in the way that fraud is being done. At the same time, the talent acquisition life cycle is not yet designed with fraud in mind, which is one of the key, things that we need to be quite mindful. How do we navigate that landscape? Do we go steer into too much of that into that, talent acquisition stages, or do we, hope that bad actors are gonna be in one way or another, cut? Some some stages, benefit from having established controls or from in... Introducing, vendor, solutions, but it all, you know, boils down to how you're orchestrating the talent acquisition life cycle rather than which type of candidate fraud are you going to be, faced with. Because in most cases, probably, we're gonna be faced with multiple multiple of them or even not all of them. Yeah. Great. I'll just. add on add on to that. I think one thing that, Stella talked about is, like, I think really you have to do... What we're hearing from our customers is that, they need, capabilities around understanding, you know, where to... For different roles, what type of fraud or cheating tools that they need in place. So as Stella mentioned, there's, Right. like, everything under the sun of things that are happening And high regulatory type of environments like financial services or insurance or health care, they are the most concerned about. the most acute areas like fraud or having a bad actor. But then other organizations is they really wanna be able to rely on, a validated skill set. And so, like, the concept of an AI, helping, you know, developing cheating, types of methodologies is a key area of concern. Marcy, I wanna stick with you on on this next question. Where do you think... You know, Stella kinda talked about this this wide range of of what can be considered, like, fraud. Correct? So where should organizations really draw the line between what is legitimate AI assistance for candidates to use and, really, what is more like misrepresentation? Yeah. It's a great question. I think, like I mentioned, I think where organizations are thinking about it is, like, what is right, for the role. And there's two two key, personas, if you will, to consider in that dialogue. One is your hiring manager, and then one is your candidate. And, you know, we actually at HireVue did some research on this because I think candidate experience is so critical, for many of the customers that we get to work with is really understanding that perspective is as important as understanding, that hiring manager manager perspective. So, you know, some of the stats, that came out in our research is that really, candidates do want a very fair and honorable process. So, like, having somebody take an assessment, or a questionnaire on your behalf, like, that's, way over the line, for candidates. And you can see some of the other stats here. 71%, you know, reading and generate a response, that's also well over the line. Having AI, there's now tools that you can purchase, as a candidate that will help you in real time during the interview. The majority of candidates think that is over the line. So I think those things, are important aspects as you think about, what and how to combat this type of challenge is starting with the candidate, what their perspective is. And I think that outcome of what came in our research was that it... They want it to be fair. They want it to be, like, a high integrity process because they feel like that's gonna give their... The best them the best opportunity, in the process overall. Hey. Stella, what do you think when employers are looking at kind of how they wanna start responding to candidate fraud, what are they, you know, like, most at risk of of getting wrong per se? Yeah. And, you know, doubling back on something that, Marcy just mentioned about the candidate experience and the, recruiter experience, which, on our latest research on talent acquisition and our definitive guide, we actually found that those two, types of experiences have the biggest outcome if done right on the business and on the financial sanity of organizations getting that experience piece right. So I would say, in all cases, the extremes are not paying too much dividend. What do I mean with extremes? Doing too much about candidate fraud and or doing too little about, candidate fraud. Doing too much would mean something like we're treating all candidates as bad actors. We have rigorous, steps every step of the way. We'll look at, how you, we include at the interview. We include all sorts of, tech enabled checks, AI enabled checks. We look for deep fakes. We ask you to validate your identity even before we get to screen your resume, which is... I mean, if you take a look... If you consider, like, these, as options or as tools, they're all very useful. But if you overdo them or if you include them in ways that are very, let's say, built into the candidate experience, they can really damage the, employer brand. And maintaining a trusted employer brand is actually one of the, practices that has the highest impact on business outcomes that we actually measured on our, latest, research. Now doing too little is also problematic because then you risk, being exposed to the actual bad actors. And let's face it. The fraud in recruiting and hiring is not new, but the defense market for fraud and, these types of, let's say, bad actor behaviors is only a couple of months or even a couple of years old. So if I would like to, let's say, summarize three things that, we should bear in mind where we're trying to see, okay, where do we draw the line? How much of that, concept are we including in our talent acquisition life cycle? It would be, one, to not over automate, responses to candidate fraud, not layering screen tool... Screening tool over screening tool. And, by the way, latest research I was reading is that even generative AI, based screening tools tend to favor the content generated by the same type of large language model. So you get even... You... You're adding a layer to protect you, and it's actually producing more bias into the equation. The second major thing, and I think it's a very big discussion now because AI adoption and automation or product center and talent acquisition is not to remove human judgment from the high stake moments in the experience. We still need human oversight. We still need hiring decisions to be made by humans. We still need any critical decision point, and critical is defined by each company. What's critical for my company is not critical for another company. So at critical decision points to ensure that the hiring outcomes are consistent, they're defensible, They're transparent. They're aligned with enterprise wide standards. So being very, very deliberate, I don't wanna call it human in the loop, but where human judgment actually helps advance or not advance, a candidate through the, talent acquisition life cycle. And, third is, ignoring the trust dimension. As Amarsie said, and I I loved what she, mentioned previously, still candidates want to feel that they are being reviewed based on their capabilities, based on their skills, based on what they're bringing to the organization, to the role, to the problem, or the challenge at hand or to, the strategy of the organization. So if you treat them fairly and if you give them opportunities to showcase their capability and their skills, they tend to be more, trustworthy in the process themselves, and they appear as their best selves, without the need to overinflate or overindex specific parts of themselves because you can either show it or you don't... You know, if you don't, have it, you can't really show it. So this is the the three things that I would say. Now it's not, a yes or no answer. There's no one way to do this. It really depends on the size of the organization, the industry they're operating in, and where are they in terms of their maturity in talent acquisition. I mean, there are still a lot of organizations who are still trying to, figure out how to standardize talent acquisition to begin with. So if we're at that stage of maturity, let's say candidate fraud is a a whole different animal to tackle. Great. Thank you. Marcy, what... You know, Stella touched about how, like, it doesn't look different for every, you know, every industry, every organization. So when when you're talking to our customers about some of these issues, what does, you know, this idea around kind of, like, the right size of rigor look like? Like, how do we think that verification should differ, you know, by role, you know, by risk level, by industry? How have we been talking to our customers about that? I think it really, comes down to, some different aspects of individual roles. So, you go from all the way from, you know, some... A remote worker, in a financial institution that's going to have access to data, or information, or, you know, abilities to action on something, that's pretty high stakes. And so those types of institutions are absolutely wanting to confirm that the identity of that person, is the person that starts the process, that that identity is continuous through the process. These are some of the key things that not only, do they wanna make sure that there's authenticity to the person and the skills are validated, but that there's not a break in that, continuum, if you will, of the individual that moves through the process. And then other things, you know, that we've heard from customers, and we do a lot of this work at HireVue around skill validation is they, are concerned that people are cheating, if you will, on the assessments. And some of the feedback we've actually done studies on this is that we did a study last year of comparing, you know, was there a lot of cheating happening on assessments in less than 1%? Some of that comes from really well designed assessments, to put in your process, and tools that enable you to make sure there's authenticity and high integrity to that. But I think those are the kind of the two ends of the spectrum. And one of the things that we've thought a lot about at HireVue is how do we, enable our tools to work across that broad spectrum so that at a job or a role level, you can utilize, those tools and layer them in to be appropriate, but not overwhelm the candidate. I think that's the balance that Stella talked about is, like, we're really trying to make sure that we have the superior, experience because it's it's an extension of these brands. We work with Fortune 100, companies, and, they need the experience to be superior, but also, have that approach where they can use identity verification or they can use, some authenticity, skill validation tooling that gives them confidence, in the assessment score coming out, in their process. Great. Thank you. So, you know, we've talked a lot about you know, you even touched on this idea of identity identity... Identity verification and making sure that your candidate is who they say they are. But how can employers really verify not only that a candidate is who they say they are, but, also, you know, we need to make sure that that person can can do the job. So how can they... How can employers kinda work on on both of those? If you can start with that, Marcy. Sure. I think, you know, how, an approach is is to really think about the entire workflow, if you will, of your hiring experience. So, putting ID verification, where, is most important for your particular role. But, you know, you wouldn't wanna maybe think about that through the entire thing, but there's other tools that you can deploy that keep that, to a specific set of... In the stage workflow. I think also thinking about developing your assessment or selection process that brings skill validation. And so having a high quality candidate and having the authenticity of the ID verification, if that's important for that role, Some some organizations don't necessarily wanna put that, type of rigor, because it's not critical for, that particular stage that they're working through. So it it very much has to be, I think, a set of, tools that get utilized, and tailored to the volume that you're working with and the type of role. If it's in person, if it's seasonal, if it's remote, risk based, type of measurements is how people, are thinking about it. So what would you add to that from, you know, what you're seeing in the in the market today? Kathy and hers from our team actually did a couple of case studies lately. One was Capgemini. The other one was Foundever. They were both around assessment, skill assessment. How do we, understand, if we have, let's say, great candidates or great fit for the role? And what are some of the elements that candidates appreciated in the whole process? I remember distinctively that in Capgemini, candidates said that they appreciated the fact that, the company wanted to assess their competencies. That added confidence, and gave them some, let's say, empowerment to prove their worth during the process. At Foundever, most candidates said that, you know what? I prefer, and I feel it's a fairer process if I'm being assessed for my skills and their abilities rather than my credentials or how polished my CV, looks. In many organizations, we're also seeing ditching the CV, entirely and only focusing on, assessment. But one part of that equation that I don't see oftentimes being discussed is making sure that we are assessing candidates does not start on the design of the assessment tool. It starts on the design of the role itself. What type of role are we hiring for? What type of skills and capabilities and behaviors we expect from the people in that role? And then if we design that in a very good way that's very reflective and, you know, telling of our culture, of our need, of our strategy, then what type of assessment becomes a much easier, part of the equation? Because we know for a fact, for example, that for this particular role, these three skills or these two behaviors are the make or break skills and behaviors that we focus and emphasize on that. I am beyond, let's say, whereas when I still see organizations trying to focus more on, let's say, language skills or math skills for roles that don't really depend on that or even if they do include that in their everyday reality, that's not the make or break point. So if you want to, let's say, make sure that you're assessing candidates and you're preventing fraud, don't start with how do I prevent fraud. Start with how do I design the role to ensure that I'm prioritizing the make or break trade skills and characteristics of that person and then emphasize that in the candidate experience. And that's a fairer and more transparent and, quite frankly, in many cases, simpler approach to assessing candidates. And so why... You know, when we talk about, you know, finding the candidates with those skills, why do validated skills matter more in kind of this AI enabled hiring environment we're in? And when you look at organizations that are doing really well with skills based hiring, kinda, what are some of the things they have in common? Yeah. I think one of those, insights I'm gonna be sharing, we... I think we started, our discussion with, which is we need to start with, and, let's say, feeling confident that everyone will look great on paper. All the CVs will be very, great, let's say, written, nicely outlined. They will have the right words. They will top the, let's say, word meters or whatever. So let's say that this part that a lot of people spend a lot of time either on the recruiter end or the candidate end, consider that not giving us a big... A lot of signal. It's gonna be more noise in the process. Now it's going to be more about designing for, the role, not just for today, which is what I'm seeing most organizations do when they're hired. They say, okay. We need to hire for another Stella in our team. And what are the capabilities and skills and the behaviors demonstrated by Stella in this role? And this is how we put together the job description. Organizations who are actually more able to be very deliberate and even more successful in their, contaminant containment of fraudulent behavior are those who are not just hiring for today's skill needs, but looking at the skill needs, let's say, two or three years from now. Will that type of skill and that type of profile be still still be relevant for our organization and where we want this, company to go? We're seeing organizations who are completely, ignoring the, insights of the skills market right now. We're seeing very specific type of roles that if you went into a talent intelligence platform, you would see that, okay. There's literally three people on the planet with that exact characteristics. So no wonder candidates will try to inflate and misrepresent their profile to appear, as if they're a good match. So it goes back to that design defining the required skills and competencies and success, indicators, and the evaluation process to be streamlined long before we've had the candidate, fraud, destruction is, discussion. It's not about catching cheaters to improve hiring quality. It's refining the talent ask so that we are accessing the right talent. And if bad actors try to hijack that, we still have tools in place to be aware and stop them when they, are trying to, influence the decision. Yeah. I think Stella's a 100% right. I think one thing that, she stated that I think is worth highlighting is a lot of transparency to the candidate as well, on, the process and really keeping it very human centered, if you will. So that as we're thinking about the success metrics for those roles, aligning those not only qualifications, but also thinking about the skills, for success to that role, and then having a lot of transparency in the process overall to the candidate themselves so that they know what's happening. They know what they're being evaluated on. And, that really sets them up for the most success, in the opportunity overall, I think is another important piece, especially, one of the things that Stella mentioned in the very beginning is just thinking about the use of AI, in hiring. And I think one of the things that we all have to consider is that we wanna leverage AI, for efficiency, but we have to keep the quality, aspects front and center, and we have to keep the aspects of the final decision maker, as Stella talked about, front and center for our recruiters and hiring managers. And so you can't compromise quality, with... For the sake of efficiency, as you consider this. Right. I love what you just said, Marcy, because it it completely shifts the conversation of candidate fraud. It shifts from a a series of isolated judgments into a system of introducing talent into the organization in a way that continuously learns and improves the entire experience and the entire process. Alright. Well, thank you both of you. We're gonna switch gears for one second and bring Annie up, up here onto our stage. She's just gonna touch base quickly on some of the, advanced fraud offerings that HireVue is gonna be bringing out later this year. So I will turn it over to Annie. Thank you, Tracy. Hi, folks. I'm Annie Henshall, our senior director of product management here at HireVue. And like Tracy said, I'm gonna get into some of the product. So I thought I'd start by anchoring us in, who HireVue is. So if you are not familiar with HireVue, we are along the entire candidate journey from when you were first engaging with your candidates using some of our tools like match and apply, as you're screening and qualifying with our AI interviewer, as you're using our science backed assessments to assess and evaluate, and then, of course, as you're interviewing both live and on demand, and then capturing some of those interview insights. But, of course, today's conversation is really in that trust layer that underpins everything that we do here at HireVue. So I wanna first talk about some of the, thank you, Tracy, the things that we have built into our platform before going into our advanced fraud detection, which is what I'm gonna be demoing in just a moment. So we have talked about how, fraud is on the rise kind of across the entire candidate life cycle. So we have some things built into our platform to help mitigate against cheating and fraud. First, things like image capture, so you know who the candidate is and ensuring that they are the same person who's showing up day one. Disabling copy and paste, which mitigates against copying over from chat GBT into your assessment and, browser focused tracking. So knowing when someone is leaving their assessment, potentially getting some assistance. Now we're building on top of that base platform into more proactive mitigation, and those are our advanced fraud detection offerings. I'll demo some of these, like government ID verification, location signal tracking, being able to have a real time checklist against a candidate, and having a unified fraud support where we're surfacing the signals that we see, relative to fraud and cheating. So before I get into product, I wanna talk about some of the design principles that have anchored us, in everything that we're doing when we're starting to build out our fraud solutions. And a lot of these have already been touched upon. So Marcy had talked about how transparency is so key to candidate experience. So that is the number one principle we are focused on, making sure that we are transparent about what data we're capturing and how it's being leveraged, surfacing that upfront in the candidate experience. It was mentioned by both Marcia and Stella that there is a adverse impact of some fraud and cheating mitigation measures on the candidate experience. In our research, we found that half of the candidates did say that, there was a negative impact by having these fraud detection measures. And, actually, twenty one percent of those candidates said that they would proceed with the, assessment or interview, but they would have a lower perception of the company. And Stella talked about how important it is to brand, to employer brand identity, to try and not impact that as much as possible. So that leads into our second and third design principles. We wanna start with the least intrusive, signals and only when necessary kind of ramp up to those higher signals depending on the role. Marcy talked about how in higher regulated industries, there might be... Need to be more rigor around fraud, mitigation measures. We did find that there are varying degrees of drop off with certain, mitigation measures, and one, the highest we found was a three sixty room scan. We saw thirty nine percent candidate drop off. So you will actually potentially see that adverse candidate impact depending on what measures you have implemented. So, as a part of our design, we're making it so flexible so that you can really cater the needs of your role to the candidate experience that you're looking for, really balancing candidate experience with candidate confidence. And then our fourth signal, fourth principle is really about surfacing those signals. Stella talked about how human in the loop is so critical. We firmly believe that we are not here to make the decision for you, but we are here to give you the information you need to make the best decision you can. So I'll show you how we are surfacing those signals and how you can have input and what signals matter to you. And then our fifth is making sure we're serving that information to the right person at the right time and that this is a continuous experience. Like you saw in the HireVue workflow, we are a continuous workflow for the candidate. We wanna make sure that all of these mitigation measures are following that same path. Okay. Without further ado, I will get us into product. Let me share my screen here while I get set up. I can only imagine I'm hearing just emphatic applause. Okay. Alright. I'm gonna go through three different demos. I know. Three for the price of one. What a webinar. I wanna show you what it looks like from the candidate experience, what it looks like from the evaluator experience, and then what it looks like to actually configure this as the admin on the back end. So we'll go in that order. Alright. So you are Amy. We have applied to a sales manager role, a regional sales manager, and we're going through the same HireVue experience that we know and love already. We receive information about what we're going to experience, expected lengths. None of this has changed. We are, transparent from the start even without the fraud mitigations. We're telling the candidates what they are to expect. Now here's where we have new capabilities. We're telling you exactly what we're monitoring. So we're saying, hey. We are doing a location check. We are checking your... If you're using any VPNs, and there's a little tool helper. You could turn off your VPN if you don't want that to be flagged. Maybe you're working from a coffee shop, and that's why you have a VPN on. It's not actually the sign of anything nefarious. And then we're also letting you know that we will be doing identity verification checks. You can also see what happens with this information, who's seeing it, how it's being used, some things you should know before getting started, and what we don't collect. Next up, we start with our identity verification. This will require that the candidate, apologies, will pop out to our identity verification provider. It will require either a second device, or if they're on mobile, it will link to them so that they can, use a camera to, verify their identity. So we are consenting that we're collecting information. Here, we're gonna scan a driver's license, and it will automatically, you know, go through the the flow in your phone, take a picture of the front of a driver's license, process it, good to go, backup driver's license, say that we're processing, and then let them know that we have completely, finished this ID verification. Next, we go into our, setup as they normally would where you're setting up your microphone, your camera, and you're ready to begin your interview. Now let's look at this on the backside where... If you are an evaluator. So, Amy, sail through very clear. We're gonna look at a slightly different job here. We have an office manager, and, we had some flags come through for Meredith Palmer. So you can see this is our, candidate evaluation dashboard, and we have a new section for fraud detection. We can also see here a section where we're identifying the risk level associated with Meredith. She was tagged as a medium risk. In a moment, I'll talk about how to, set up this on the admin configuration. We can dive into these signals and learn more exactly where they came from and why. So we see that she has some flags under identity verification, and you can see exactly where those are coming from. Her image doesn't appear, to be a photograph, and there are some inconsistencies across some security elements. You can also see that her name didn't match. Perhaps we're using a different name than what was on record. Also failed a liveness check, and the liveness didn't match the photo ID. We can also see we flagged some, location signals. She was not... The candidate location where she was taking the assessment or interview does not match her job country, and there was an IP address flagged. You can also see where... What she did pass. Alright. I'm gonna stop into the admin experience and talk about how these things are set up on the back end. Because like we said, this is configurable to meet the needs of the role, while protecting, you know, brand identity and candidate experience. So here in fraud settings, you can see any signals that are available, you can turn on or off. And within them, when you turn them on, we're simply just going to collect the information. If you'd like to flag them, they get summarized into those flags that you saw, so you'll actually get that extra, added flag. So you can see for the ones that are not flagged, we are logging them for the evaluator. And for those that we do have flagged, we can see, that they're gonna, have that additional level of visibility. And same for any of these. This is our kind of simple, setup. And then down here, you can configure your risk levels. So those were where we saw that, there was moderate risk. I might update this to say low risk, is, you know, zero to two flags, moderate risk. We will put in the middle, and I'll add a a level to say high risk review. As a red. And those will be the flags that show on that evaluation page. Now we do have, advanced settings if you do want to have greater level of control over the flags. Instead of a binary flag, you're now able to set a severity. So now I wanna know if the candidate location doesn't match the job country and to what degree that is important to me. If it's set to zero, it will be the same kind of logged for the evaluator, but set with any... You know, a VPN detected is, you know, low to moderate risk for me. It will be captured as a flag, and it will tell me, to what degree that matters. And you have the same, level of configuration for all of these. And then you can here see, we're verifying the candidate's ID at what stage. You can do it at the first job stage, or, really, you need to know, at every single interaction you're having with the candidate that they are who they say they are. So you might want it at every job stage, or you can customize. Same all the way through. And, again, you can also, you know, create custom tags for the flags that are shown on the evaluator page. Alright. I see some questions coming in. I can work in the background to answer those, but I'm gonna hand it back over to Tracy for some final questions. Great. Thank you, Annie. Appreciate that. Yeah. Let's just go into some practical takeaways before we get into the q and a. So I'll ask both Stella and Marcy the same question. But if a talent leader wants to strengthen their hiring integrity, like, this year, where should they begin, and what questions should they be asking their technology partners? So still a lot of you answer first, and then we'll turn it over to Marcy. Okay. Great. I would say definitely start by defining what good looks like. What are those skills? What are the success criteria for the candidates before going into sourcing or even selecting a tool or having the candidate for a discussion to begin with? And organizations need to understand not only what they're aiming for, what they want to achieve, but also what is their level of tolerance when it comes to automation in the talent acquisition, life cycle? Where is the human contribution necessary? What can be, let's say, easily automated or can be AI empowered without a significant impact on either the candidate's trust or the recruiter experience or both? The third thing I would definitely say, and I know it's saying where to begin, but it actually boils down to three different dimensions, is to, further, support hiring managers, not just the TA teams. It's, hiring and recruiting, at large has a lot of stakeholders, a lot of players. Even if we have the best technology and the best, let's say, streamlined processes, if we don't include that level of sophistication into the approaches of our, hiring managers, we will not be able to actually ensure that we're not gonna be hiring based on the usual suspect bias type of, approaches. One of, the clients that, we've run case studies on, which is a consumer bank, Citizens, actually got 80% of their hiring managers certified in behavioral inter... In behavioral, analytics, in evidence based interviewing before introducing them to AI in any of the tools. So definitely summarize it, define what good looks like, understand the automation boundaries and who does what, and train and support the hiring managers to ensure that they are supporting as the backbone of the whole process. Thank you. Marcy, what would you... How would you answer that question? Oh, and you are still you're still muted. Darn. Thank you. We only got through the whole webinar. I only had to have them once. So, I think things that, I would highlight are... Is to really think about it in a very holistic way. I think, you know, organizations are doing a lot of hiring and talent acquisition and having, you know, one off, one off processes or one off, approaches doesn't really serve the organization for the more long term strategy. AI is is here. AI and being in the hands of candidates is here. And so really thinking through their strategic approach, of how they want to manage cheating and fraud, for their town acquisition, acquisition, is, I guess, the main thing that I would encourage folks to think about. In addition to, many of the things that, Annie highlighted of transparency, right rigor for right role. These are some of the fundamentals that go into that holistic approach and strategy. Great. All right. Thank you, Marcy and Stella. And, we're going to keep Annie up here too. We're going to get into some of the questions that have been coming in. Please feel free to keep submitting questions in those, Q and a box. We wanted to leave a good amount of time. So I'll dive right in. I think this first question is for Stella, and this comes from Marcel. He asked, if applications are becoming easier to adapt to the requirements of the job description, how does designing the role help reduce risk of fraud or misrepresentation when now every resume kind of perfectly matches that job description? I love... I absolutely love that we're starting q and a with that because we touched upon that briefly, previously as well, but I do want us to make sure that that part is is grounded. When every resume can be perfectly tailored to a job description, as you say, Marcel, the role design itself must shift the verification burden from, do we have the stated credentials to, can we demonstrate capability? This means completely anchoring job requirements to, work outputs that you can observe that are specific and testing candidates against those outputs directly rather than against keywords and how you structure your resume and things that are trivial and easy to to replicate. A well designed role narrows what fraud can actually accomplish because if the hiring process is built around live situational judgment test and and work samples and real time problem solving tied to the precise outcomes that the role must deliver, then a fabricated resume becomes irrelevant because it's never that type of evidence that matters. It's can you do the job? Can you demonstrate those make or break key, skill and behavioral characteristics? This is why I feel it's it's so structural to design the requisition and the job role, with, what are the make or break characteristics and then upscale for the rest. Right. Thank you. Next question is for Marcy, also from Marcel. But he is wondering if HireVue is exploring technology that will monitor systems, processes, or browsers, to detect AI usage. Yeah. So we, we have, as Annie highlighted, we have, a handful of features that, are already part of our base platform, things like understanding if browser focus is lost, if copy and paste is done. Some of, what you'll see coming out in the advanced fraud solution will expand on that with a number of additional features of identifying questions that, are AI generated, and some of those type of feature sets. So definitely things that are available today, and then more to come, in that advanced fraud, tool set. Great. Next question, I think, Annie, you can take this one. Wondering about, you know, any privacy policy, like, stated or information on how or how long, say, like, a candidate's driver's license is stored, who it's shared with, some of those kind of pieces of information. Yes. We do have stated privacy policies. They are linked right in the candidate experience for them to view. And in the case that we are using a a third party, if they're going to a third party system, they also have, privacy policies, stated, linkable, viewable by the candidate. Okay. And if there are any flags, is the candidate made aware of that at all? Or, is that strictly on the side of the hiring team? Right now, it is on the side of the hiring team. We do not want the flags to be a gating function, nor do we want them to cause any bias on the the side of the evaluators or entering into a conversation with the candidate. Great. Another question. Could you talk about kind of the different candidate save... Stage options, how company could verify the I... The ID from application to onboarding while protecting the candidate experience? I think probably Annie or Marcy could take that one. start. Comforted. Yeah. From a from a tactical perspective, the ID verification, the, like, highest form of, candidate confidence and ID will be available at each stage if you would like to have that in each stage of their, interview process. And we will also be offering candidate kind of continuity. So checking is the candidate the same candidate from previous stages by checking, the ID and the candidate snapshots as image captures that we, are generating at the... As a part of the platform. So that's a less invasive way, but the ID verification is available at each stage. Great. Excuse me. For Marcy, do you have any advice on kind of creating assessments that test reliability? I think I think that I just wanna restate the question because of, like, reliability for, like, assuming the candidate maybe on the job type of reliability. We actually do. We have a lot of, assessments that, that support, that, sort of stability and capability for candidates. I totally encourage you to talk to your CST or reach out to us. We can reach out to you. We have those types of assessment, tools, in place that can provide that type of information, for you. Right. So I think this next question's, can be good for you. We hear a lot about candidates using AI to kind of game the process. From the other side, how can a qualified candidate make sure an automated screen doesn't filter them out unfairly? Are fast rejections usually from knockout questions, keyword matching, or something else? I love the use of the phrase game the process because there really is a structural asymmetry here in terms of how the initial stages of, candidate application could be structured and how each technology, solution is approaching that. If I were to start from, let's say, what can candidates do, it's... I would say, yes. There is a job description. Yes. There is a vocabulary being used in that job description, but that's not necessarily a requirements list. And using that vocabulary in your CV doesn't necessarily mean that you're gaming a process. It's speaking to the system's language, which is okay if you're doing that than if it's genuine and legitimate at the first stage. What most candidates often don't include in their subsequent conversations or in how they present themselves is making skills explicit rather than implied. For example, we hear a lot of, organizations and even, technology solution providers moving beyond the keyword matching, trying to develop a deeper understanding of, candidates' capabilities, but only where platforms surface enough signals for them to do so. So for candidates, that means that you should not be assuming that the technology solution provider or the company will infer your capabilities or your skills. So be very explicit about them at any stage of the, process. Of course, in conversational AI driven, screening, speed matters more than candidates realize. So actually applying early, responding promptly, actually helps, move candidates faster into the, next stages, and we've, and we've, seen that with, one of our clients I've written a case study for, which is Great Wolf Resort, which they were able to move candidates for application to interviews in days, not weeks. And add... Candidates who delayed responses to, those messages actually found that the pipeline had already moved on. So it's not about, penalizing the vocabulary and the language and feeling like we're gaming a system. It's yes. Make sure that you are using the vocabulary, but... And at the same time, do not expect that there's gonna be, like, a... An inference done for you. Be very explicit about the profile of what you're, offering because, yes, if, an average job requisition has a thousand candidates for some, specific, occupations that I'm, studying and I'm crunching the numbers on, you can't expect to be given a second chance to talk about your, credential... Your, skills or your capability. So be very specific very early on about them. Okay. Great. And, one more question, I think, for you as well, Stella. What do you think about... What is about AI features that can kind of miss the genuine and authentic candidates during the early selection process? And if you've, you know, come across any of these, you know, you know, like, what what would you suggest they do or, like, what would be your advice? You mean, in terms of candidates, Yeah. having having that type of experience? Well, remember. in the in the, first part of the conversation, we said that candidate experience and, recruiter experience, but candidate experience is a make or break in the impact of the talent acquisition, process. Well, if we're not designing with that in mind, if we are just putting too much technology in front of, candidates and too much automation without actually having the grounded truth of, you know, who is this person, what can they really, support, how can they really support the role of the organization, then we're completely missing the point of what it is we're doing. This is not a numbers game, talent acquisition and recruitment. It's a, can we help our organization solve one of our biggest business challenges by bringing into our organization the right type of talent with the right skills and put them in the right place at the right timing in our organization to make sure that we are succeeding and we're achieving what we're set out to achieve. If you over gamify that, if you over automate that, and if you completely let go of the candidate experience, trust me, with Gen z being very active in, entering the workforce, they're not gonna be candidates, to begin with entering, those types of, experience. So definitely being very deliberate about how we're, designing the experience and at the same time, how much technology because there is such a problem as too much technology in, the talent acquisition life cycle. Absolutely. Alright. With that, we are gonna wrap up for today. First, I wanna thank Marcy and Stella and Annie for your time and your insights. Thank you everyone for attending today and all of your great questions and engagement. We really appreciate it. And thank you again so much and enjoy the rest of your day.