Every Fact. Every Claim. Every Answer | Global Interview Security Summit 2026 | India Edition

In this keynote, you will explore how candidate fraud has shifted from an artisanal craft into an automated assembly-line threat powered by AI and deepfakes. The session examines how remote hiring has turned recruitment into a dangerous security threat surface, especially within the tech-savvy Indian market. Discover how bad actors leverage AI teleprompters and synthetic faces to manipulate interviews and exploit global organizational infrastructure. Finally, learn about a vital five-step integrity baseline and Talview’s unified dashboard designed to move companies from siloed detection to end-to-end risk management. Tune in to find out how you can close these critical gaps and secure your hiring funnel from application to onboarding. 

Panel details:
Sanjoe Tom Jose (Talview)

Transcript

SPEAKER_00 0:00

Hey everyone. Welcome to another edition of the Interview Security Summit. We've been over the past few quarters having very engaging discussions around what's important for interview security. And in this edition, we are gonna speak about some of the problem statements, some of the solutions which we have been seeing in the India context specifically. India obviously is home to some of the largest industries in IT services, call centers, banking and financial services, and many other industries as well. And we have traditionally found that there are some problems which are very specific to the India market, especially when it comes to uh security and candidate fraud. So in this summit, over the next few hours, we are going to discuss and hear from some of the leading practitioners, some of the leading product um experts and security experts on what they are seeing on the ground when it comes to interview security and candidate fraud, and how they have been tackling what kind of solutions they have been implementing and what has been the impact of some of the solutions. But let's start with some of the key ground truths. When we started the journey as tell you almost a decade back, we were solving for very specific problems within the interviewing space. There were issues around inefficiencies in the interviews process. There were obviously issues around impersonation, some form of candidate cheating, uh, organized fraud. But what we are seeing right now, especially in the last one year, is unprecedented. Lot of new approaches, new tools, new uh organized operators in the space, which is significantly undermining the institution of interviewing and hiring. Today we are at a crossroad where every fact, every claim, and every answer provided by a candidate need to be verified before we can take it at face value. And that's the reality of interviewing for the global context, and that is amplified in many manners in the India context, given the scale of operations, given the tech-Savvy nature of candidate population, and also given the fact that it's such a large country with significant cross-border operations and hiring processes. So that's what we're going to deep dive into in the next few minutes. So if we were to articulate the problem in one single sentence, the fact of the matter today for most large employers or even uh mid-size employers, small employees in the country is that there is no guarantee that the candidate who aced the interview is the one who is showing up for joining. The fact that you probably interviewed somebody, verified them on camera, or even met them in person, and they came across as confident on brief, they had the best answers you could think of, doesn't mean that you're going to onboard that person. It could be a different person, or he could have forged an identity which makes him eligible for the role in uh in a scenario where he might not have been eligible. Or he took significant external help to answer questions, come across as confident that the skill sets you validated for are probably not relevant. So you need to think again about the identity, the claim, the answers, and figure out if each of those can be verified independently. And that's the gap which the industry is trying to mitigate right now. And what makes it even more sinister, even more serious, is the fact that hiring has become a security surface or a threat surface now. For more most of the uh uh history, missing a uh or miss maybe a candidate who attempts fraud in the interview process was probably a talent miss. You probably ended up hiring someone who was not capable of doing the job, and you probably need to rehire them. So there is cost associated with that and all of that. But now, especially in the age of remote hiring, remote work, air-enabled applications, hiring has become a significant security threat. When you're hiring somebody, you're giving them the key to the organization in many forms or shapes. If you are a global capability center, a GCC, or an IT organization or a call center, a new joiner is provisioned a role and access in the global infrastructure from day one. And that significantly enhances the risk or the stakes here because there are a lot of organized operators, and some of you might have already come across them, who are using that as a threat surface, use a combination of fake IDs, AI tools, deep fakes, all of that to get into your organization and either steal the data, hack the company device, steal the data, sell it on the dark web, or worse, even ask for an answer. And this is happening at scale because disruption has really got cheap. Generative AI has collapsed the effort and cost involved in faking a resume. You can you have companies, fake companies which are on LinkedIn with fake social media presence, fake employees. Uh, you have deep fakes, which is helping candidates to uh appear as somebody else, uh some a face and an image or an image which is present only in a fake ID. You have all this AI teleprompting application which is allowing candidates to answer any questions confidently. So they don't need traditionally a lot of this cheating as service providers in the space would have experts who are in the same room trying to help candidates answer questions. They would need to rely on experts to create fake IDs, they would need to uh have elaborate operations to maintain fake uh degree certificates and fake uh uh employment uh records. But now anybody can get this with a subscription. There are AI-driven services which can spin up umpty number of fake companies, fake colleges, fake friends, fake uh recommendations, all of that. So disruption has really got cheap. And as a result of that, for fraud is really industrialized, and there are a lot of bad actors who are taking advantage of it even beyond just uh for the purpose of getting a job when which they're not qualified for. And I think all of this is significantly amplified in India. India is obviously where, uh at least for the past few decades, the most ambitious hiring has been happening, and the fraud economy has also been built over the years. India was always the fraud economy in India, was always uh ahead of the rest of the world because it is also where hiring is happening at such a large scale. Candidates are tech-savvy, and there's a there's a mix of remote and um in-person work. So, with GCC scaling fast, the kind of growth which you are seeing in the banking and financial service industry and the uh uh the digitization which is also happening in the space, which are all great things, candidates are taking advantage of those limitations or fraud operators, even beyond individual candidates. And using Devon Access and sometimes also using uh the phenomenon of RPOs, the lot of this uh great organizations who have been assisting many of these GCCs or global organizations to scale, they so the fraud operators are at continuously attacking them because if you find a wedge, if you're able to uh uh crack one particular RPO, you're probably having access to n number of uh large enterprise organizations, their data, their uh uh payroll, which significantly changes the equation. And it's already showing in the pipeline. It's uh almost 2.3 times uh surge in AI authored resumes in the in the uh hiring funnel since 2024. These numbers are probably much bigger today in 2026. Well, from the reported data and anecdotal information say it's much more, but from the reported data, almost one in six applications are either a bot or uh uses some sort of automation at some stage in the hiring process. And obviously, the fact that from the time the candidate is onboarded, they have access to all the global system uh makes this a significant risk uh for the employers. And higher when when you think about hiring as a process, you are essentially verifying four fundamental facts or four core uh components. One is the identity of the candidate, who they are. That is being undermined by aspects like synthetic faces, stolen identities, deep fake videos, all of that, which are now as good or even better than a real-world ID or a real world video. Credentials, which is really what's on record, which is your uh degree certificates, experience letters, all of that can be manufactured to look 100% authentic at scale with the help of AI now. Claims, uh, earlier candidates who can only claim about things which they know they need to claim, you know, for together get get shortlisted for a job or answer questions in interview. Now, with AI written tailored resumes, uh every resume would look perfect uh for the role uh you are trying to hire for. And the same thing happens in interviews and exams as well with co-pilots and proxy solvers and all of that. You every candidate is present themselves with 100% perfect answers. And many of us over the years have tried to solve all of this, uh, but we have most often solved this in parts. Uh, we have a resume checker which uh has been used to score candidates and ensure that at least the there is some level of authenticity uh checking is happening happening on resumes even before they are scheduled for interview or a screening conversation. We have ID checks which were traditionally done more downstream. Some of us have moved it more upstream so that you are able to verify the identity of the candidate much ahead of the process before you commit time and effort. There is always proctoring uh which is essentially uh uh being used to ensure that the candidates cannot cheat in an exam, and now many of that is also being um brought into the interview. But what happens is the all of this solutions also exist in silos. You might have uh a genuine resume, but then probably it's not backed by a genuine ID check, or maybe the resume, the person whose resume it is is not the person who is appearing uh for for the day one joining uh when an ID check is happening. Similarly, you might have somebody else taking the exam. So in a proctored exam, they might come come through clean, but then they are not the same person whose identity you're verifying. So these are the issues because the links, each of these independent components might be useful, but the entire chain is not end-to-end uh secure. And hiring fraud traditionally has been largely compared in the background verification straight uh stage, but that cannot be true anymore. It just does not live in the background verification stage, it has to be run through the entire length of the funnel from application to screening to interview, offer, obviously, background verification and the day one joining. And stopping at interview alone or stopping at background verification along is often uh much more difficult because candidates can uh you might not you might miss a lot of signals when you're not paying attention in other steps, and they might genuinely pass one particular step, but then they can still uh uh fake their and their application uh in different ways in different stages in the process. We have seen uh screening and interview are some of the uh areas where AI has been biting the hardest. These are live surfaces where there are a lot of these tools from real-time AI overlays to deep fake videos and hidden hardware, like smart glasses and uh Bluetooth earphones, virtual machines and organized services, all of this is continuously attacking the uh assessment and review process as well. So, what what we are seeing in the industry today from the uh um hiring process doesn't end at the end of the offer. It also happens from offer to day one as well, where many of these things there is manufactured history, there there is somebody else who has been part of the process, and day one, somebody else is being swapped for that person, the laptop farms which are being used to do the work, uh, and the there might not even be a real person behind the uh uh behind the deep fake video. Uh the same person doing multiple jobs and then kind of using a combination of these technologies to manage that. And obviously uh they're being they're claiming to be in one place, but then also being uh uh also but operating from another location. These are also aspects which continues through their employment, even if they are not a threat actor who is probably trying to hack the company's device and steal the data. So these are issues which we need to uh address even during employment. But what we have seen is in these candidates who are not genuine and who are going to commit fraud in employment will also commit fraud during the hiring process. So by ensuring that your hiring process is secure, you are checking for their claims, you are checking for their identity, you are checking for their answer, you are also significantly reducing your risk even during the employment phase. And another key aspect, especially in the India context, is the fact that while the decision on whom to hire is often local, you many of you have processes where probably there's a global counterpart who is also an interviewer, or there's an approval process which requires a global counterpart to be involved. But the decision is largely local, the process is mostly local, but the risk is global because these candidates are getting access to systems which are uh exposing global data of the organization to these threat actors. So, what is really a good solution? In our experience, in the especially in the last uh one year, working with many of the leading employees in the space, is that what you need is one single signal across the funnel. You need to have a comprehensive end-to-end solution without disconnected checks, which are composite, which is uh basically taking individual proof, whether it's identity, whether it's claims, whether it's uh um uh your credentials, whether it's the answers. While each of those are being independently checked, they are also being uh brought together to correlate and make sense out of and look for additional signals. You need these signals to be presented in an explainable manner, especially when it comes to compliance and some of the other reasons as well. And this entire process has to be continuous. So, for example, you should have an identity check, uh at least a face match across different stages in the hiding process. So the person who is applying or whose ID verification you have done at the top of the funnel, you should verify that the same person who is taking the exams, if you have a skill exam, same person who is joining the interviews, and most importantly, the same person who is coming for day one joining. And that would require you to perform those face match checks across the funnel. And obviously, you want to you you also need to ensure that the end-de verification process is fair and it doesn't become uh surveillance. So you also need to ensure that the processes which you're doing, those are compliant with the uh uh local regulations. You uh the uh solutions which you're using, those are tried and tested. There are not a lot of false positives or false negatives, which distorts the level playing field, and then wherever possible, there is a human in the loop, uh, but without putting significant uh honors on the if that human in the loop is the recruiter, without putting significant honors on the recruiter, uh, to ensure that there is verification by them uh at specific stages of the process. And all of this comes with significant experience, uh, which I'm I'm sure you will also hear from some of the practitioners today, but also many of the Talvut team members, if you're already in touch with them, are very familiar with. So, in in our experience, the India Hiring Integrity baseline is this five-step process. Verify the identity right at the beginning and then also continuously throughout the process. Always treat the test and interview as monitored surfaces, never do an exam without proper security, never do an interview without proper security. Try and reconcile claims against evidence. So if they are claiming something in the interview or in the resume, uh especially when it comes to uh their employment records, their credentials, verify those and as much as possible as uh as early in the process rather than uh doing everything in the background verification stage, and there are simple checks which uh platforms like Talview today can provide for that purpose. Reverify everything at offer stage. You already have your preferred background verification vendor, I'm assuming, but uh re-verify everything at the offer stage, but also ensure that uh you're also doing the uh uh checks at the onboarding stage. This the there's a many of our customers have a face match mandatory at the onboarding day so that you can ensure that the person who is joining is the same person who was part of the process beforehand, and then you obviously need to keep the entire process compliant and explainable and have some form of human in the loop so that you're not exposing yourself to additional risk. And Talvi has been at it for many years, as you know, and uh we've recently launched. I did speak about this in the last submit, but we've really taken our AIOP platform, our assessment intelligent operations platform, to create what we are calling a candidate trust dashboard, which is helping you to verify the facts, the claims, and the answers, and also give provision for you to hook up to your preferred background uh verification providers to also verify credentials and bring all of those signals into one single trust dashboard where you can be in control of your hiring process and manage your risk end-to-end. So, the way we are thinking about this, the market or most of the uh practices in the market today, some of the providers in the market today is largely focused on detection, but in silos. Talvus focus has been to not just do one pinpoint solution when it comes to security, but bring the best of breed in a single unified solution, which is end-to-end and is a single end-to-end risk management dashboard for you. But we are not just coping at that. We have been working with some of the thought leaders in the industry with uh AI AGIS, our latest initiative, where we believe we can standardize some of this best practices across industry and work with industry, especially the India community, to create a portable standard for candidate trust. And that's something which we we're gonna talk more and more about later today and also in the course of this year. So, we would welcome each of you whoever believe they can contribute to this initiative of AIGS to reach out to your Talview account manager or customer success manager and uh discuss about how you can partner with us in this initiative. To summarize, trust is not a feature which you can add as an afterthought. It is the precondition for hiring for global organizations for large enterprises. You need to ensure that trust is being taken care of end to end. And Talvi is excited to partner with every one of you to do that. And later today, in the subsequent sessions, you will hear from real practitioners who have been facing the challenges on the ground, have been trying to solve those challenges and share their experience on what worked and what did not work and what are some of the best practices. So enjoy the rest of the sessions and look forward to uh having more conversations around security and trust with each of you sometime in the future. Thank you.