Rohit Laila has spent decades at the intersection of freight operations and technology, and he’s seen fraud morph from clumsy fakes into polished impersonations that slip through busy workflows. In this conversation with Alexandre Faurestain, he unpacks how identity verification must anchor every engagement, why AI-driven spoofing is now a daily reality, and how disciplined, layered checks can still stop losses without grinding freight to a halt. Themes include playbooks for day-one authority verification, cross-channel callbacks, document forensics, centralized communication controls, and training that sticks. Throughout, he ties lessons back to this year’s signals: nearly 50,000 entities reviewed, widespread onboarding failures in identity and authority checks, and hundreds of broker-carrier fraud reports that often began with one small mismatch.
You reviewed nearly 50,000 entities this year; where did the most convincing fraud attempts show up, and what made them blend into normal workflows? Share one case, the tells you finally spotted, and the metrics your team tracks to catch them faster.
The most convincing attempts showed up exactly where teams feel rushed: onboarding and first-load tendering. The fraudsters leaned into “clean” digital IDs, crisp insurance PDFs, and impeccable email signatures to blend into the rhythm of booking and dispatch. In one case, a supposed carrier sailed through surface checks until a minor bank field didn’t align with the corporate name format we saw in FMCSA records; that tiny inconsistency prompted a deeper dive that unraveled the whole application. We track how often identity checks fail during onboarding, denials tied to missing authority, and the share of fraud reports that convert into confirmed cases—those trend lines tell us where to tighten friction without slowing honest partners.
AI-generated IDs and photos now look “clean and professional.” What are the top three subtle inconsistencies you still see, and how do you train teams to find them? Walk through a real example and the tools or steps that exposed it.
First, lighting and depth are too uniform—portraits lack the varied shadows you see in natural captures. Second, micro-typography on IDs looks perfect but spacing around seals or holograms is off by a hair. Third, metadata betrays them: recently created files with no edit history pretending to be scans. We exposed one by comparing the headshot to a video call: the facial proportions matched, but the ear detail and skin texture on the “ID” were subtly synthetic. Our steps are simple: request an on-camera ID hold-up, cross-check the FMCSA profile, and pull file properties and embedded object lists. Training uses side-by-side spot-the-difference drills and a checklist that forces analysts to slow down and name what looks “too perfect.”
Dale Prax said, “Security begins with identity.” How do you translate that into a day-one operating authority checklist? Lay out the exact verification sequence (FMCSA, phone, insurance, banking), the time it takes, and what triggers a stop.
We start with FMCSlegal name, DOT/MC status, and contact data must align with the application. Next, we call the phone number listed in FMCSA records—not the email signature—to confirm the person, role, and lane details. Then we request insurance certificates directly from the provider, not via forwarded attachments, and validate banking through a secure portal with name-match controls. It’s designed to be completed the same business day, and we halt the process if any company name, phone, or bank detail fails a one-to-one match or if the caller resists a quick video verification.
You recommend calling the number listed in FMCSA records. What’s your playbook for cross-channel verification when a call or email seems off? Describe the steps, the thresholds for escalation, and an anecdote where a video call changed the outcome.
If something feels off, we pivot channels immediately: hang up, dial the FMCSA-listed number, and send a brief confirmation email to the domain on file. If either channel disagrees on identity or role, we escalate to a video call with screen-share of the FMCSA page and a live display of the government-issued ID. One call sticks with me: a smooth talker tried to reroute a payment; a two-minute video check revealed a background that didn’t match the alleged office and a reluctance to show ID. That mismatch triggered a stop, a fraud report, and a notification to the real company, which helped them lock down their credentials.
Spoofed emails and AI-generated voices are rising fast. Which phrases, timing patterns, or document requests most often reveal a copycat? Share a recent attempted spoof, how you authenticated the real contact, and what logs or audit trails proved decisive.
Copycats push urgency and secrecy—“process now,” “don’t loop in accounting,” or “this is a one-time remittance address.” They strike when teams are busiest and ask for updated banking or a last-minute warehouse change. We saw one “controller” demand a new payment route; we authenticated the real contact via the FMCSA-listed number and a separate message thread in our centralized system. The audit trail—timestamps, the original remittance thread, and the first-use device logs—showed the spoof originated outside our normal channel, which made the denial straightforward.
You advise centralized tools for load and payment communications. Which features actually prevent fraud (e.g., role-based access, message pinning, audit trails), and how do you roll them out without slowing ops? Give metrics from before and after adoption.
Role-based access keeps financial changes behind controlled doors, message pinning locks the latest verified instructions at the top of each load, and audit trails give us a single source of truth. We rolled them out in phases—payments first, then load updates—while preserving email for read-only notices to reduce friction. Before adoption, too many exceptions hid in personal inboxes; after, exception volume dropped in our escalation queue and verification cycle times stabilized even during peak weeks. The biggest win is cultural: people trust the pinned record and stop honoring stray requests.
Scammers now impersonate real carriers and brokers with stolen credentials. How do you safeguard your own identity day to day? Detail policies for password hygiene, MFA, certificate handling, and portal access, plus a story where proactive steps saved a relationship.
We use unique passwords with a managed vault, enforce MFA on every critical system, and require certificate-based access for portals that touch payments or authority data. Certificates are rotated on a schedule, and we never transmit them via email—only through secure provisioning. When a partner received a spoof “from us” requesting bank changes, our DMARC/DKIM setup and portal-only policy made it easy: they refused the email and pinged us in-app. That quick alignment preserved trust and let us notify others before the attacker tried again.
Many cases start with small mismatches—phone numbers, authority details, contact info. What’s your “mismatch triage” workflow? Explain who validates what, how long it should take, the checklists you use, and where most teams make mistakes.
Intake flags the mismatch and tags it by type—contact, authority, or banking—then routes to the right specialist. Identity specialists handle FMCSA and phone; risk handles insurance and banking; ops confirms load-level details like pickup windows. The checklist forces a fresh, source-of-truth pull rather than reusing cached data, and the target is same-day closure unless a provider has to confirm. Most mistakes happen when teams try to “explain away” one bad field instead of pausing the entire transaction.
In 2025, over 10,000 identity checks failed in RMIS onboarding and 4,700 accounts lacked authority. What do those numbers tell you about fraud patterns versus simple errors? Share the top three denial reasons and the corrective steps that actually work.
Those figures show a mix: true fraud trying to slide in alongside a high volume of sloppy data. The top denial reasons we see are identity mismatches, incomplete or unverifiable insurance, and missing or inconsistent authority. Corrections that work are straightforward: re-verify identity via FMCSA and a call-back, have the insurer send certificates directly, and update authority records before reapplying. If an applicant resists any of those steps, it often confirms our initial doubt.
You investigated 494 fraud reports from brokers and carriers. Which report types led to confirmed fraud the most, and what early signals did they include? Walk through a case from report intake to closure, including timestamps and handoffs.
The strongest leads came from reports of sudden banking changes and contact info that didn’t match FMCSA. Early signals included domain lookalikes and phone numbers that failed reverse checks. One case moved fast: intake logged the report, risk verified the bank request against the centralized thread, and identity called the FMCSA number to validate the contact. Within the business day, we froze the transaction, informed the real company, and closed the case with a documented trail and guidance to tighten their own controls.
For fake documents, what metadata or source checks catch the most issues (file history, fonts, embedded objects)? Give a step-by-step doc validation routine and an example where a small detail—like a bank field—unraveled the scheme.
Metadata is gold: creation apps, timestamps, and author fields often contradict the story. Fonts and kerning betray pasted lines, and embedded objects reveal layered edits. Our routine: request the doc directly from the source (insurer or bank portal), inspect file properties, compare fonts and seals to known-good samples, and confirm data against FMCSA and our system of record. In one case, the bank name was right but the beneficiary field used a format we’d only seen in templates—one call to the provider exposed it as a manipulated PDF.
When AI voice spoofing hits dispatch, how should teams respond in the moment? Outline a call-back script, verification questions only the real contact would know, and a debrief process that strengthens SOPs. Include one misstep to avoid.
The move is polite exit and pivot: “I’m going to call you right back at the number on your official profile.” On the callback, ask for lane specifics, prior load references shared in your system, and the last verified payment method—details a real contact can answer without hints. Debrief immediately: log the attempt, capture the audio, update the playbook with any new phrases used, and brief the next shift. The misstep to avoid is staying on the spoofed line to “get more info”—that’s when social engineering ramps up.
What’s your training cadence for frontline staff on these threats, and how do you measure retention? Share quiz topics, tabletop drills, score benchmarks, and a story where training directly prevented a loss.
We run recurring, bite-size sessions tied to real incidents so lessons feel current. Quizzes focus on spotting domain lookalikes, reading insurance certificates, and executing call-backs; tabletop drills rehearse hot-load exceptions and banking-change requests. Retention shows up in the field: fewer escalations that lack evidence and faster, cleaner case notes. A dispatcher recently paused a “pickup location change” because the instruction bypassed our centralized thread—training muscle memory stopped a bad handoff.
How do you balance speed with verification when “freight moves fast”? Describe SLA targets for checks, exceptions for hot loads, and the metrics leadership watches (false positives, cycle time). Include a time you chose to slow down—and why it paid off.
We design SLAs to clear routine checks within the day while embedding stop-points for identity doubts. Hot loads get a fast lane, but only if FMCSA, phone confirmation, and pinned payment details align. Leadership watches false positives, cycle time, and conversion rates from fraud reports to confirmed cases so we can fine-tune friction. We once held a late-day tender because the email domain had a subtle swap; the delay prevented a misdirected shipment and protected the relationship with the real carrier.
Looking toward 2026, which fraud vectors worry you most—credential theft, deepfake voices, or back-office email takeovers? Map the controls you’re prioritizing, expected ROI, and one investment that small carriers can implement this quarter with clear results.
Credential theft paired with deepfake voices is the nightmare—it blends access with persuasion. We’re prioritizing stronger identity proofing at onboarding, hardened email authentication, and stricter, portal-only payment changes with audit trails. The ROI shows up as fewer failed identity checks, cleaner authority validations, and faster closure on fraud reports. For small carriers, move all sensitive docs and remittance changes into a secure portal and lock email to notifications—overnight, you reduce exposure to the most common spoof patterns.
Do you have any advice for our readers?
Treat identity as a living control, not a one-time hurdle. Use the official FMCSA phone number, insist on source-to-source insurance and banking, and centralize every critical instruction where it leaves an audit trail. When in doubt, slow down—fraud moves faster only when you let it. The companies that win are the ones that verify twice and move once.
