Automated Background Checks

It was a great opportunity to address #HR #leaders representing various Industries in a Round Table discussion, titled - "𝗔𝗜 𝗮𝗻𝗱 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻 𝗶𝗻 𝗕𝗮𝗰𝗸𝗴𝗿𝗼𝘂𝗻𝗱 𝗖𝗵𝗲𝗰𝗸𝘀: 𝗕𝗮𝗹𝗮𝗻𝗰𝗶𝗻𝗴 𝗘𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆 𝗮𝗻𝗱 𝗔𝗰𝗰𝘂𝗿𝗮𝗰𝘆.", which was organized jointly by SpringVerify and HR SUCCESS TALK® in Bangalore As we navigate the complexities of talent acquisition, AI and automation have emerged as game-changers. However, we must balance efficiency and accuracy to ensure reliable results. Let me share the challenge, possible AI driven solutions and use cases. 𝐓𝐡𝐞 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞: Manual background checks are time-consuming (avg. 2-4 weeks), prone to human error (up to 30%), and costly (avg. $50-$100 per check). 𝐓𝐡𝐞 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧: AI-powered #automation can streamline background checks, reducing turnaround times by 50-75% and costs by 20-50%. 𝐒𝐭𝐚𝐭𝐢𝐬𝐭𝐢𝐜𝐬: Following are some interesting data points in background verification 1. 80% of employers conduct background checks 2. 45% of resumes contain discrepancies 3. AI-powered background checks reduce false positives by 90% 4. 95% of employers report that background checks have helped prevent or reduce instances of workplace violence, theft, or other forms of misconduct. 5. The global background check market size was USD 13.83 Billion in 2023 and is likely to reach USD 38.70 Billion by 2032 6. 71% of employers use background checks to verify education credentials, while 64% use them to verify employment history. 7. 85% of job applicants admit to lying or exaggerating on their resumes, highlighting the need for thorough background checks. 𝐔𝐬𝐞 𝐂𝐚𝐬𝐞𝐬: There are several #AI-powered background checks #usecases which can be leveraged to address the various needs of BGV * 𝐈𝐝𝐞𝐧𝐭𝐢𝐭𝐲 𝐕𝐞𝐫𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧: AI-driven ID verification tools, like ID.me and Jumio, ensure accurate identification. * 𝐄𝐦𝐩𝐥𝐨𝐲𝐦𝐞𝐧𝐭 𝐕𝐞𝐫𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧: Automated systems, such as HireRight and EmployeeScreenIQ, validate employment history. * 𝐂𝐫𝐢𝐦𝐢𝐧𝐚𝐥 𝐑𝐞𝐜𝐨𝐫𝐝 𝐂𝐡𝐞𝐜𝐤𝐬: AI-powered search algorithms, like those used by Been Verified and (link unavailable), efficiently scan databases.  𝐀𝐈 𝐚𝐧𝐝 𝐆𝐞𝐧 𝐀𝐈 𝐓𝐨𝐨𝐥𝐬: 1. Natural Language Processing (NLP) for 𝘥𝘰𝘤𝘶𝘮𝘦𝘯𝘵 𝘢𝘯𝘢𝘭𝘺𝘴𝘪𝘴 2. Machine Learning (ML) for 𝘱𝘢𝘵𝘵𝘦𝘳𝘯 𝘳𝘦𝘤𝘰𝘨𝘯𝘪𝘵𝘪𝘰𝘯 3. Optical Character Recognition (OCR) for 𝘥𝘰𝘤𝘶𝘮𝘦𝘯𝘵 𝘴𝘤𝘢𝘯𝘯𝘪𝘯𝘨 4. Robotic Process Automation (RPA) for 𝘸𝘰𝘳𝘬𝘧𝘭𝘰𝘸 𝘰𝘱𝘵𝘪𝘮𝘪𝘻𝘢𝘵𝘪𝘰𝘯 It was insightful, interesting & inspiring round table. Many thanks to my friends - Annie Mathen, Poornima Srinivasan,Tino Thomas, Anbu M, Paramveer Singh Narang, Nandakumar Kuruppath, Priyanka Nikumbha, Maitreyee Bhaduri, Harsha Vatnani, Yashwanth JembigeA, Govind Negi for sharing their expertise and connect. #Leadership #eductaion #AI #BGV #Wednesdaywisdom #digitalsecurity #dataprivacy #GDPR

Employers are using AI to investigate job applicants. What will they find about you? I just ran an AI background check—the good, bad, and ugly. The results were surprising! It found details I'd forgotten I'd ever shared. 📄 Old forum posts from 2015. 👨💻 My comments on news articles. 🖼️ Even photos I was tagged in by colleagues at conferences. The AI created a comprehensive behavioral profile that went far beyond anything a traditional Google search would reveal. This isn't some future scenario. It's happening right now: 1️⃣ 80% of employers already screen social media profiles 2️⃣ AI screening tools scan 10,000+ online sources instantly 3️⃣ Websites tag you with 32+ tracking scripts 4️⃣ Even "deleted" content can resurface through archives The most shocking part? Most of us have no idea what's actually out there. 💻 AI remembers everything. AI can analyze your behavioral patterns, flag concerning content, and predict workplace fit—all before you even submit your application. But here's the opportunity: You can run this check on yourself first. ✍ I've written the exact prompt to audit your own digital footprint and specific strategies to protect your reputation. Because in 2025, your digital footprint isn't just part of your professional brand. Your AI profile IS your professional brand. 🙋♀️ Are you ready to discover what AI knows about you?

When we recently ran the numbers on our own applicant pipeline, the result stunned us: 780 out of 1000 engineering applicants were fraudulent. Not just sloppy resumes. Full-blown, coordinated fraud campaigns on great American companies. And we're not alone. Heads of Talent across the industry tell me the same thing. The FBI has even warned that many of these schemes are backed by North Korea, with IT worker infiltration as a state strategy. But here's the worst part: the scams are getting really good. One customer shared a story about a candidate who breezed through screening with an impeccable resume. Great pedigree, flawless answers, even passed the technical interview. But when the background check came back … total fraud. Someone else's career was completely stolen. Another recruiter told us about a "dream candidate" who turned out to be a literal deepfake. On video. Polished, articulate, believable… until they asked him to move his hands. The image glitched. Then they ran a liveness test: "Cover your left eye, now hold up 3 fingers." Frozen screen. Scam exposed. And others still are seeing LinkedIn profiles and résumés copied verbatim, with nothing changed but the email, redirecting callbacks straight into a scammer's inbox. The impact is massive: - Tens of thousands of dollars wasted in interview hours - Real candidates overlooked while your team is tied up chasing ghosts - A real risk of one slipping through and poisoning your trust with customers and investors Why is this happening now? Because fraudsters are using AI to generate resumes, invent social proof, even lip-sync answers on video. This isn't a one-off. It's AI on offense. The only way forward? AI on defense. That's why we built Covey's anti-fraud detection as a first-class capability. We flag risk signals that humans would miss (strange social footprints, resume inconsistencies, patterns of coordinated applications) and share detection intel across our customer network. What used to cost 95 wasted interview hours now gets shut down in minutes. Because the real question isn't if you'll encounter your own "deepfake candidate." It's whether you're equipped to catch all 780 of them … BEFORE they drain your time, money, and pipeline. After many months of testing, plugging a new hole every time a scam profile got through, we've perfected the best in class spam mitigation system. Excited to get it in all your hands to fight the good fight!!

I was telling a CEO about the rise in fake applicants trying to penetrate corporations. He said, "Thank God we do background checks." He was missing the point. Clearly hadn't spoken to his recruiters lately. In one recent Socure example, a role that usually gets 90 applicants suddenly had 3,000+ submissions. Our internal recruiters were drowning, asking to hire consultants just to get through the first screen. Then we added automated identity checks at the top of the funnel. Overnight, the noise disappeared and the real applicant pool dropped back to the normal 90. Had we simply said to the HR team, "You have background checks, use them earlier," that never would have worked. The cost and time per check should be summarily prohibitive. Having automated checks for "real identities" earlier in the funnel is the only way that companies are going to solve this and have HR teams still be able to do their jobs.