Background Verification Services

Most people get Reference Checks wrong! Here's how to get them right 👉🏻 Throughout my journey, I've had to make 1000s of hires and often struggled with evaluation through the standard interviewing processes. I read somewhere that ~60% senior hires go wrong even after the most meticulous processes so I wondered how to improve the odds. 🤔 What I discovered is that there's no substitute for spending time with the candidates and conducting ‘unnamed’ ref checks through your own network. But what I also learnt is that not every ref check is the same and you can end up with very different outcomes depending on how it’s done. So, through reading and experience, I came with the best practices that I christened with the acronym "PEARL", and here it is for the FIRST time🔥 P - Promise Reciprocity Busy professionals don't dole out intel freely. So, you must offer to return the favor – something as simple as “If ever you need my help for a ref check or otherwise, I'd be happy to help". A senior leader will immediately see its value & perhaps become more ‘available’ on the call. E - Ensure Confidentiality This is critical, especially in India. Candor is not part of our culture, so assure the referrer that you understand the sensitivity of this call and will keep it 100% confidential. Also that you'd expect the same if they ever choose to call you for a reference. If you still sense some hesitancy, maybe throw an ‘offer’ of a good-faith NDA. Don’t worry, nobody ever takes it up but it makes them less guarded. A - Ask questions that force specificity (close-ended & open-ended) Broad questions like – "How was their work ethic?" “Does she work hard?” - are a complete waste of time. You need to ask 2nd order questions that make it comfortable for the referrer to answer without feeling like they're maligning the candidate. For eg - “How do you think we can help the candidate grow?" is better than "Can you tell me about their weaknesses?” R - Retrieve critical insights Actively listen and probe for specifics. Did the candidate consistently meet deadlines? Why or why not? How did they handle pressure? Did they run towards solving problems or look for directions to carry out? These details paint a picture beyond the resume. L - Learn rehire potential And finally, the golden question – "Are you willing to re-hire or work with the candidate again? Why or why not?" Regardless of what the referrer may have said up to this point, most senior folks will have a hard-time giving you a false or misleading response to this one. This is the true gauge of the candidate’s potential and one I put a lot of weight in. To conclude, thank the referrer for their time, assure confidentiality again and commit to a quid pro quo. This leaves the door open for other ref checks you might wish to do in the future 😏 So, there you have it - A PEARL from my collection🙌🏻 Do comment with something that’s worked for you that I may have missed :) #hiring #startups #leadership

I just walked in from a coffee with Kraken Digital Asset Exchange's sanctions lead Crystal Noe and see this! According to an excellent blogpost today, Kraken's security and recruitment teams recently uncovered and thwarted an attempted infiltration by a North Korean state-sponsored hacker—disguised as a job applicant. The incident, which began as a routine interview for an engineering position, quickly escalated into a high-stakes security operation and offers important lessons for the broader crypto and fintech ecosystem. The hacker raised immediate red flags: they joined their interview using a name different from the one listed on their resume and appeared to be coached in real time, switching voices mid-call. Kraken had already received intelligence from industry partners that North Korean actors were actively applying to jobs at crypto firms using networks of false identities. One of the flagged emails matched that of this candidate. Kraken’s red team initiated a deeper investigation, using open-source intelligence (OSINT) tools to identify ties between the applicant and other known aliases across GitHub, breached credential databases, and company systems. The candidate’s technical footprint—use of colocated remote desktops with a VPN and a doctored government-issued ID—added further weight to the suspicion. As the evidence mounted, Kraken advanced the applicant through its hiring funnel—not to recruit, but to study. The final interview, with Kraken’s CSO Nicholas Percoco and others, was a masterclass in subtle operational security. While asking standard technical questions, the team embedded “live” verification challenges—asking the candidate to hold up a government ID, confirm their physical location, and name local landmarks or restaurants. The hacker stumbled on basic geography and could not complete the two-factor authentication steps. By the interview’s end, the team had full confidence this was not just a suspicious candidate but a North Korean agent attempting to gain privileged access through the front door. Key Takeaways? ✔️Don't Trust, Verify—Every Step of the Way ✔️Use OSINT to Investigate Anomalies ✔️Incorporate Real-Time Identity Challenges ✔️Train Your Entire Organization, Not Just Security ✔️Leverage Industry Intel ✔️Recognize State-Sponsored Threats Are a Reality Kraken’s experience is a reminder that modern cybersecurity is no longer just about perimeter defense. Sometimes, attackers try to walk through the front door—wearing a suit and carrying a resume. Resilience begins with awareness, collaboration, and the creativity to think like a threat actor before they reach your systems. Congratulations to Nick, CJ Rinaldi, Crystal Noe, Sarah W., and the excellent team at Kraken working to keep the ecosystem safe. 📄 Read the full post here: https://lnkd.in/eM6r_RNN

Ben Horowitz, co-founder of a16z, says "knowing what you want" is the most important step in hiring. Most teams skip it. Then they wonder why their job posts attract 200 applications and zero qualified candidates. Here are 5 principles that fix this: 1. Write what they'll ship, not who they are "Strategic thinker" and "detail-oriented" tell candidates nothing. By Day 90, a Senior PM should have launched the first version of the signup experience and improved new user activation by 10-15%, built a 6-month roadmap with engineering and design, and set up the core metrics dashboard. That's outcomes. When hiring managers send you buzzword JDs, send them back with this template and three examples. You're the expert. Own it. 2. Use the action-result template every time "By Day 90, you have [action] [problem area] to deliver [measurable result]." For Enterprise Sales: built a territory plan and outreach system, started 10 qualified conversations, closed one new customer. For Engineering Manager: reduced system downtime to near zero, hired two senior engineers, cut code review time by 25%. When hiring managers push back, ask them what success looks like. They'll figure it out fast. 3. Let the wrong people opt out When outcomes are specific, qualified candidates see themselves in the role immediately. Unqualified candidates see the bar and move on before applying. This is self-selection. This saves your team 20 hours of screening per role. When you deliver better candidates faster, you become indispensable. Clarity is your leverage. 4. Measure what matters: passthrough rate A/B test buzzword post vs outcome post. Track your apply-to-screen passthrough rate by source. If it jumps from 15% to 25%, your targeting improved. If time-to-fill drops by a week, your self-selection worked. 5. Avoid vague outcomes that don't filter "Improve conversion" is not an outcome. "Lift week-1 activation by 10-15%" is. "Build relationships with customers" is not an outcome. "Close one land deal and progress two expansions to commit" is. The difference is measurability. If a candidate can't picture hitting the metric, it's too vague. Push back on hiring managers when outcomes are fuzzy. Your job is to attract the right talent, not process 200 wrong applications. Personally, I always start with first 90 days, and first 12-18 months outcomes. All the standard things you design your loop around (experience, strengths, etc.) are much easier to crystallize once you know what this person needs to do. — Try it now: Replace 3 adjectives in your next job post with 3 day-90 outcomes. Publish it. Measure passthrough. Show your hiring manager the difference. This is how you go from order-taker to strategic partner.

We used to talk about “identity verification” like it was a solved problem. Not anymore. The recent Reality Defender 2025 threat overview shows how synthetic personas are slipping into the very systems we trust to confirm who someone is… from video interviews to onboarding to financial KYC checks. One demonstration in the report is especially telling: a fictional job candidate created in under ten minutes, polished enough to fool a recruiter on a live video call. The voice, the face, and the mannerisms were all engineered. All convincing. All false. We’re also seeing: - AI-generated résumés and work samples appearing across applicant pools; - Deepfake face-swapping during interviews; - Synthetic identities passing automated KYC checks; - Criminal and foreign actors infiltrating remote hiring pipelines to gain systems access. This goes beyond spotting a suspicious résumé. Today, identity itself has become a contested space. Most verification tools were built to answer the question, “Does this person match the documentation?” But now we need to ask a different question: “Is the person on my screen real?” That shift changes everything. It impacts insider threat programs, compliance workflows, fraud detection, and the expectations we place on teams who were never trained to evaluate synthetic humans. For leaders, part of the solution involves better technical tools. But it’s also understanding the new gaps between trust, identity, and authenticity. In this new synthetic era, we must design systems that assume attackers can mimic the visual indicators we used to rely on. And for each of us individually, it reinforces a principle that sits at the heart of Mind Sovereignty™: Critical thinking is now part of identity verification. Not instead of technology. Alongside it. How prepared is your organization for synthetic identity risk in hiring, onboarding, and other core functions? I’d love to hear what changes you’re already making to meet this challenge. #SyntheticIdentity #DeepFakes #DigitalTrust #MindSovereignty

Illinois HR Teams should know that SB 2339 was passed on October 30, 2025, which expands the Right to Privacy in the Workplace Act. The bill is now on Gov. Pritzker's desk and will immediately take effect once signed. The law creates new rules around employment eligibility verification (like E-Verify), privacy, and employer responsibilities. Here is the bill status: https://lnkd.in/etkmnRtR What HR needs to know: E-Verify & Employment Verification Systems ▪ Previously, employers could voluntarily use E-Verify with notice, training attestation, and recordkeeping. ▪ SB 2339: Prohibits employers from imposing checks beyond federal E-Verify rules, protects employees from extra document requests and pre-screening (amended 820 ILCS 55/10). Handling Discrepancies ▪ Previously, adverse action based on agency/third-party discrepancy notices were at employer discretion, with only minor penalties (820 ILCS 55/10, 820 ILCS 55/5-6). ▪ SB 2339: No adverse action solely on third-party mismatch (ex: SSA or IRS) unless from federal immigration authorities; higher penalties and new private right of action (820 ILCS 55/10(b-5)). Notification Requirements ▪ Previously, limited obligations to notify affected employees of adverse verification findings or rights to contest tentative non-confirmations. ▪ SB 2339: Employers must provide detailed written notice to employees (and their representatives) within five business days of any negative finding, informing them of the issue, timeline to contest, upcoming meetings, and representation rights. They must also post official government notices about E-Verify rights in visible workplace location. Local Government Preemption ▪ Previously, individual municipalities and counties could enact tougher employment verification rules. ▪ SB 2339: State law now overrides all local rules—verification now standardized statewide (amended 820 ILCS 55/10(d)) Penalties and Good-Faith Defense ▪ Previously, violations were classified as petty offenses, with limited fines and little civil recourse for affected employees. ▪ SB 2339: Violations are subject to more severe civil penalties, compensatory damages, and attorney’s fees. The law provides legal safe harbor for employers who act in good faith reliance on guidance from the Illinois Department of Labor or DHS, or who make honest administrative errors that do not affect employment or pay. (820 ILCS 55/18) Tips for HR: 1) Update E-Verify practices to only follow federal rules for employment verification—no extra checks or pre-hire document requests. 2) Notify employees of negative findings in writing within 5 days and post E-Verify rights. 3) Train HR teams to recognize the difference between valid federal agency notices and third-party ones not covered by immigration enforcement If you have more info or comments, please share below. Thanks! #EVerify #Immigration #EmploymentLaw #HR

How to Navigate AI-Optimized Resumes: Balancing Technology with Human Judgment in Hiring 🛠️ In the era of AI-generated resumes, hiring managers face several unique challenges that require them to adapt their evaluation processes. One of these challenges includes over-polished resumes which can make it harder for them to differentiate between genuinely qualified candidates and those whose resumes are simply optimized for algorithms. It is no surprise that candidates are turning to AI-powered resume tools: it increases their chances of catching the attention of employers. For example, if a job posting emphasizes "data analysis" and "team leadership," the AI might suggest adding these keywords to the resume if relevant to the candidate's experience. This optimization aims to improve the chances of a resume passing the initial automated screening and impressing human reviewers. 👉 While this technology helps candidates present themselves effectively, it also means employers must look beyond the polished surface to assess authenticity and find the best candidate for the role. So, how can companies effectively evaluate candidates with AI-optimized resumes? Here are a few strategies to consider: 1️⃣ Focus on Behavioral Interviews Behavioral interviews help reveal how candidates apply their skills and experience in real situations. To uncover their problem-solving abilities, for example, ask questions like, “Can you share a time when you faced a major challenge at work and how you resolved it?” 2️⃣ Skill-Based Assessments Practical assessments ensure candidates can indeed perform the tasks required for the role. For example, you might ask a developer to complete a coding exercise or a marketing professional to draft a quick campaign strategy. 3️⃣ Check for Authenticity in the Resume Use the interview to verify the claims on a candidate’s resume. Ask, ”You mentioned leading a successful project on your resume—can you walk us through your approach and the outcomes?” to ensure their achievements are authentic. 4️⃣Most Importantly! Remember that Human Judgement is Vital While AI may help you streamline resume screening, you must apply a human lens to evaluate nuances. For instance, after a screening tool identifies top candidates, ask them questions like, "What attracted you to this role and how do you see yourself contributing?" By implementing these strategies, your hiring process becomes thorough and equitable, allowing you to evaluate candidates beyond superficial qualifications and identify the most suitable individuals to enhance your team’s success. #FutureOfHiring #AIInRecruitment #HumanCenteredHiring #SkillBasedHiring #EquitableRecruitment __________________ 👋 Hi! I am Luiza Dreasher, DEI+ Strategist and Facilitator. I help leaders create workplaces where all individuals feel valued and want to stay. Would you like more DEI+ insights? 🔔 Ring the bell on my profile and follow me.

How to cut your interview-to-hire ratio in half: Most hiring processes waste enormous time interviewing candidates who were never right for the role. Here's how to fix that: 🎯 Create a structured pre-screening process that tests for actual job requirements, not just resume keywords 🎯 Have candidates complete a small, paid sample project that mirrors actual work 🎯 Involve team members in early screening calls to assess cultural fit The standard approach is fundamentally flawed - reviewing dozens of resumes, conducting multiple rounds of interviews, only to start over when no one fits. Instead, focus on quality of assessment over quantity of candidates. A well-designed 60-minute technical assessment will tell you more than five generic interviews. We've seen companies reduce their time-to-hire by 40% simply by reimagining their screening process to focus on demonstrated skills rather than claimed experience. Quality at speed isn't a contradiction. It's a methodology that transforms expectations in technical recruiting. #RightfitAdvantage #HiringEfficiency #TechRecruitment #TalentAcquisition #InterviewStrategy

I just automated HR Talent Aquisition. Are you spending countless hours sifting through resumes? HR professionals spend an average of 𝟮𝟯 𝗵𝗼𝘂𝗿𝘀 screening resumes for a single hire. I built an AI-powered HR assistant that reduces screening time from 𝟮𝟯+ 𝗵𝗼𝘂𝗿𝘀 𝘁𝗼 𝘂𝗻𝗱𝗲𝗿 𝟲𝟬 𝘀𝗲𝗰𝗼𝗻𝗱𝘀, while enhancing the quality of candidate evaluations through consistent, evidence-based insights. 𝗜𝗻 𝗺𝘆 𝗹𝗮𝘁𝗲𝘀𝘁 𝗮𝗿𝘁𝗶𝗰𝗹𝗲, 𝗜 𝗰𝗼𝘃𝗲𝗿: 1️⃣ 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗮𝗻 𝗶𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝘁 𝗿𝗲𝘀𝘂𝗺𝗲 𝗮𝗻𝗮𝗹𝘆𝘇𝗲𝗿 using Azure OpenAI Assistants & Semantic Kernel. 2️⃣ 𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴 𝗼𝘃𝗲𝗿 𝟭,𝟬𝟬𝟬 𝗿𝗲𝘀𝘂𝗺𝗲𝘀 𝗺𝗼𝗻𝘁𝗵𝗹𝘆 𝗳𝗼𝗿 𝗹𝗲𝘀𝘀 𝘁𝗵𝗮𝗻 $𝟭 in API costs. 3️⃣ 𝗣𝗿𝗼𝘃𝗶𝗱𝗶𝗻𝗴 𝗲𝘃𝗶𝗱𝗲𝗻𝗰𝗲-𝗯𝗮𝘀𝗲𝗱 𝗿𝗲𝗰𝗼𝗺𝗺𝗲𝗻𝗱𝗮𝘁𝗶𝗼𝗻𝘀 with automatic skills assessment. 𝗞𝗲𝘆 𝗙𝗲𝗮𝘁𝘂𝗿𝗲𝘀: 📄 Supports multiple resume formats (PDF, DOCX, TXT) 📊 Generates automated competency matrices 🤖 Offers smart candidate comparisons 📈 Tracks quantifiable achievements #AzureOpenAI #AI #HR #Recruitment #AzureAI #MSFTAdvocate #Azure #HRTech #FutureOfWork #TalentAcquisition #Agents

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

Fraudulent Candidates Are Everywhere—Here’s What We’re Doing About It Over the last few months, we’ve seen a huge rise in fraudulent applicants here at Tailscale. In some cases, as many as half of applicants on a job are not who they say they are. Yes, really. The good news: we’ve gotten very good at spotting it, and I wanted to share what I have learned. 🎯 Who’s a Target? -remote-first tech companies -companies with fully remote interview processes ❓ Why? Fraudsters are hoping they can: -impersonate someone else -use deepfake video or audio -bypass less-rigorous screening steps -eventually steal data or paychecks Basically, anywhere the hiring process happens behind a laptop, fraud is rising. 🛑 The Most Telltale Signs: -no profile photo (or a cartoon avatar- as much as we love them!) on LinkedIn -no connections or a brand-new LinkedIn account -application language suspiciously close to the exact verbiage in your job description -different name on the resume vs email vs LinkedIn (not just a nickname… literally different identities) -repeated applications even after being rejected -listing n/a in job posting questions to bypass or writing nonsensical answers ⚠️ Important: One flag alone does not mean fraud—but multiple flags together should absolutely make you pause and verify. Some Tips 👉 Message them on LinkedIn before the interview If the LinkedIn looks legit but something else feels off, send a message and ask them to confirm the interview time. If it’s a fraudulent applicant, 1 of 2 things might happen: 1) the real person responds (“um…who??”) 2) the scammer disappears Either way, you get clarity without wasting time. 👉 Email before the interview. You can literally say: “We’ve been seeing a lot of fraudulent applications—would you mind confirming X?” Most legitimate candidates won’t mind at all. 👉 For Engineers, ask for a GitHub link in your application questions & have them to add you to a private repo (takes 30 seconds). 👉 Use verification tools. We use tofu, and it’s been excellent. It can tell you: -if their email address or LinkedIn was created yesterday -whether the email matches the LinkedIn signup -if the phone number is tied to prior scams -whether the same resume shows up under multiple names at your company or the countless others in their network It’s worth the investment—especially if you’re remote and high-volume. 💡 Remember: Behind every scam attempt, there’s sometimes a real person whose identity is being abused. If you confirm something is fraudulent, be kind and send a quick InMail to the person. Most have no idea someone applied on their behalf. TL;DR Fraudulent applicants are here, they’re getting more sophisticated, and we’re not tolerating it. At Tailscale, we’re actively verifying identity, tightening processes, and investing in tools. If you’re a hiring manager or recruiter dealing with the same, I hope this helps. And if you’re a scammer thinking of applying here… please don’t. We’re onto you. 😉