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

Can we save inference cost by routing easier questions to cheaper LLMs? 🤔 📝 New research from Carnegie Mellon University, Google DeepMind, Indian Institute of Technology, Delhi and University of Southern California proposes AutoMix - an approach that strategically routes queries to larger LLMs based on the approximate correctness of outputs from a smaller LLM. 🔎 How it works: 1️⃣ First, generate an answer with a small, efficient model. 2️⃣ Then automatically verify the answer using few-shot learning. 3️⃣ Use a meta-verifier to evaluate reliability of answer. 4️⃣ Only if uncertain, invoke a larger, more accurate (but costly) model. 💡 Key benefits: • Enhances the incremental benefit per cost by up to 89% • Builds on and outperforms prior methods like FrugalGPT • Works with open source and black-box LLMs alike I'm excited by the potential for novel methods like this to make LLM solutions more cost effective, and therefore usable at scale 💰 🧵Read the paper for all the details! 👉 https://lnkd.in/eW7Nf2rf

The dark side of employee monitoring: trust, value, and agency 🕵🏻♂️🚫 🤔 A study found that 80 percent of top US employers use tech to track workers' productivity, often in real-time. Does our company monitor our fellow workers and us with high-tech software? Do we even know? ➡️ The missed side of value Employee monitoring encourages the mentality that the only valuable hours are those we spend in front of our computers; instead, we need to reframe what productivity is. ➡️ A trust issue "If we can't see our people, how do we know what they're doing?" Digital monitoring is an extreme form of micromanagement, a need for control resulting from a lack of trust that when people are not in the office, they are not "productive." ➡️ Monitoring can backfire Research suggests that employee monitoring can backfire, making people feel like they have no agency and increasing the prevalence of the behaviors these systems want to deter. ➡️ Rethinking knowledge work and value People may work hard to prove they are working instead of doing valuable work, constantly demonstrating their hard work. 🌱 So, how can we create cultures where people are trusted to manage their time and produce quality work? ➡️ The potential of people analytics If we can solve the trust and transparency issues, people analytics could help employees use their data to better understand and improve their work patterns. Illustration by me 😊 Extract from an article by Rachel Botsman. Link to the complete source in the first comment 👇 #productivity #trust #management

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

The Joshua Schulte Case: A Masterclass in Insider Threat Failures When CIA software engineer Joshua Schulte decided to leak some of the agency’s most classified hacking tools to WikiLeaks, it wasn’t just one of the biggest intelligence breaches in U.S. history—it was a glaring failure in insider threat management. Schulte didn’t just wake up one day and betray his country. There were red flags all along his employee lifecycle—from hiring to his eventual arrest. Had there been stronger human risk management practices, the damage might have been prevented or contained before it spiraled into a full-blown national security disaster. What Went Wrong? 📌 Hiring & Vetting Gaps – Schulte was brilliant, but also volatile and disgruntled. Background checks don’t end at hiring—continuous behavioral monitoring is critical. 📌 Toxic Workplace Culture – He had conflicts with coworkers, was written up for behavioral issues, and had access to sensitive CIA cyber tools despite being under scrutiny. A zero-trust access model could have prevented him from walking out the door with state secrets. 📌 Poor Privilege & Access Controls – Despite concerns, Schulte still had access to some of the most sensitive digital tools in existence. Just because someone has clearance doesn’t mean they should have access to everything. 📌 Failure to Detect Early Warning Signs – Reports say Schulte felt resentful, isolated, and underappreciated—classic insider threat indicators. Human risk management isn’t just about cybersecurity—it’s about understanding people and their motivations. How Enterprises Can Prevent Their Own ‘Schulte Moment’ 🔹 Implement a Robust Employee Lifecycle Management Program – Insider risk doesn’t start when someone leaks data—it starts when they’re hired. Screen, monitor, and reassess risk continuously. 🔹 Apply Zero-Trust Security – No one should have unlimited access just because they have clearance. Use role-based access controls, behavior analytics, and real-time monitoring to flag unusual activity. 🔹 Build a Culture That Reduces Insider Risk – Employees who feel unheard, undervalued, or mistreated are more likely to become threats. Security isn’t just about firewalls—it’s about people. 🔹 Monitor for Behavioral & Digital Red Flags – Disgruntlement, unusual file access, sudden changes in work habits—all of these should be triggers for closer scrutiny. Joshua Schulte was a brilliant hacker—but he was also a human risk hiding in plain sight. Insider threats don’t happen in a vacuum. They are built over time—and can be prevented with the right security mindset. #Insiderthreat #HumanRiskManagement #Cybersecurity #Zerotrust #Employeelifecyclemanagement

Stop Asking References Easy Questions. Get the Real Answers! Have you ever seen a hire go wrong because HR didn’t dig deep enough during reference checks? It’s not just about ticking boxes—it’s about safeguarding your company’s future. Leaders need to step up and guide HR on how to ask the questions that really matter. Remember, it’s your company’s reputation on the line. Here’s how to avoid fluff and get the insights that count: 1. What is your name, title, and current role? 2. What was your relationship with the candidate? When did you last work together? 3. What are the candidate's top three strengths for this role? 4. Describe their leadership and management style. 5. How do they make decisions? 6. Can you share a time they managed extreme pressure? 7. What areas needed more development? 8. Would you work with them again? 9. What’s something unique about working with them that an interview wouldn't reveal? 10. Anything else we should know? Start with these better questions and watch your hiring decisions improve dramatically, we all know that bad hires can be expensive. According to recent studies, a single bad hire can cost a company up to five times the individual’s annual salary. It’s not just about the financial hit—it’s about the impact on team morale, productivity, and company culture. By investing the time to ask more meaningful questions, you’re not only protecting your investment but also ensuring a stronger, more cohesive team. The right hire can drive your company forward, innovate, and inspire those around them. Make reference checks count. Make every hire a strategic advantage. Ready to transform your hiring process? #hiring #jobs #jobseekers #interviews #managers #leaders #hr #humanresources #people #business #strategy #reference #checks #image #linkedin #linkedinconnections #talentnexa #aach

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?

In some workplaces, especially in China, companies are turning to advanced AI and computer vision technologies to monitor employees. The aim? To ensure productivity and minimize downtime. While the potential for optimizing efficiency is clear, the approach raises critical questions about privacy, trust, and ethics. 𝐖𝐡𝐚𝐭 𝐈𝐬 𝐂𝐨𝐦𝐩𝐮𝐭𝐞𝐫 𝐕𝐢𝐬𝐢𝐨𝐧? For those unfamiliar, computer vision is a field of artificial intelligence that enables computers to process and interpret visual data - essentially teaching machines to "see" like humans. In workplace settings, AI-powered cameras analyze behaviors and patterns to differentiate between work-related activities and distractions. 𝐎𝐫𝐠𝐚𝐧𝐢𝐳𝐚𝐭𝐢𝐨𝐧𝐬 𝐢𝐦𝐩𝐥𝐞𝐦𝐞𝐧𝐭𝐢𝐧𝐠 𝐬𝐮𝐜𝐡 𝐬𝐲𝐬𝐭𝐞𝐦𝐬 𝐨𝐟𝐭𝐞𝐧 𝐡𝐨𝐩𝐞 𝐭𝐨: - Identify inefficiencies: Pinpoint areas where workflows can improve. - Increase focus: Minimize distractions and ensure tasks are completed on time. - Enhance performance tracking: Gain data-driven insights into employee habits. 𝐁𝐮𝐭 𝐈𝐭’𝐬 𝐍𝐨𝐭 𝐖𝐢𝐭𝐡𝐨𝐮𝐭 𝐂𝐨𝐧𝐜𝐞𝐫𝐧𝐬 While the tech has its advantages, here are a few critical considerations: Privacy and Stress: Being constantly monitored can make employees feel uneasy, potentially leading to stress or resentment. - Trust Issues: Over-surveillance may imply a lack of confidence in employees, impacting morale and workplace relationships. - Legal and Ethical Challenges: The acceptability of surveillance varies by country and culture, making this a gray area in many regions. What’s your take on this? Is AI surveillance in the workplace a necessary evolution or a step too far? #innovation #technology #future #management #startups

Can you spot fake resumes? I've been seeing a lot of resumes lately with fabricated experiences or credentials. For example, here's a software engineering application we received this week. This resume seems promising, with a stint at Amazon AWS and wide experience with modern technologies. However, there are a few things that don't pass the smell test and some dead giveaways: • Experience at a leading tech company (Amazon) is followed by much less prestigious companies (offshore consultancies). This sort of career trajectory is very rare. • There's a lot of keyword stuffing in the resume, but there's very little description of the specific product or business impact. In this case, over 40 different technologies are mentioned. It's hard to be an expert on that many things. • The job titles are incorrect. At Amazon, the title would be SDE I, not Junior Software Engineer. • Finally, the resume lists experience with technologies before they existed. During their stint at Amazon (2014-2016), they worked with FastAPI (released 2018) and Python 3.8 (released 2019). So unless they have a time machine, this is almost certainly fake. At Fonzi AI Recruiting, we're building AI agents to automatically detect fake resumes, so recruiters can focus on real candidates instead.

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