Tag: facial recognition

8 Frightening Forecasts For The Future Of Fraud

Fraud is entering a new era. Businesses across North America expect fraud trends like biometric fraud, deepfake scams, and synthetic identities to become more common in 2026 as criminals adopt faster and more sophisticated tools.

This visualization, created by Visual Capitalist’s Julia Wendling, in partnership with Inigo for the Fraud in Data campaign’s sixth post, uses data from the Sumsub Fraud Report 2025 to explore the fraud trends businesses believe will shape the future of digital risk.

Biometric Fraud Could Become the Biggest Threat

Surveyed businesses expect biometric fraud to rise the most, with 67% predicting an increase. As companies rely more on facial recognition, voice authentication, and remote onboarding, fraudsters are finding new ways to exploit those systems.

Deepfake technology is already making identity verification harder. In the future, AI-generated videos, cloned voices, and stolen biometric data could make fraud attempts more convincing and more scalable than ever before.

Businesses also expect synthetic identity fraud to grow, with 56% anticipating a rise. Criminals are increasingly combining real and fake information to create identities that can bypass traditional fraud checks.

AI and Deepfakes Are Changing Fraud Trends

Businesses expect fraud attacks to become more automated in 2026. Around 44% predict increases in advanced AI-driven attacks, deepfake scams, and forged identity documents.

Another 33% expect AI-generated fake profiles to rise as fraudsters use generative AI tools to impersonate real users online. These scams could become faster to produce and harder to detect across financial services, ecommerce, and digital platforms.

As fraud tactics evolve, businesses may need to shift from reactive fraud prevention toward real-time risk monitoring powered by machine learning and behavioral analysis.

Data Breaches Will Continue to Fuel Identity Fraud

Data breaches are expected to remain a major source of fraud risk. About 33% of businesses anticipate more identity theft linked to stolen personal data.

Organized fraud networks are also expanding, according to 22% of respondents. As cybercriminal groups become more coordinated, fraud operations could become increasingly global and industrialized.

The Future of Fraud Trends

Companies that invest in adaptive verification systems, stronger cybersecurity, and understand the data around fraud prevention may be better positioned to respond to the next generation of threats.

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Canada’s Bill C-34 Would Require ID or Face Scan to Use Social Media

Canada’s long-anticipated and dreaded Bill C-34 arrived on June 10 with the usual fanfare about protecting children.

We obtained a copy of the bill for you here.

Marc Miller, the Minister of Canadian Identity and Culture, tabled it.

Strip off the press release and what is left is a law that lets an appointed federal body order Canadians’ posts deleted across the country, decide which platforms can give an account to a 15-year-old, and tell AI chatbots to watch what you type.

It also bans Canadians under 16 from social media by charging the whole country for it, in the currency of everyone’s privacy.

The government calls it the Safe Social Media Act. Safe for whom is the question it would rather you not dwell on.

The law creates a Digital Safety Commission of Canada. Cabinet appoints its three to five members. The same body writes the rules, runs the inspections, hears the complaints, and hands out the fines, which is a regulator and a courtroom folded into one office that answers to no voter.

Everything hangs on a phrase the bill declines to nail down, “harmful content.” There are seven categories, among them “content used to bully a child” and “content that foments hatred.”

The drafters did take the trouble to say content is not hateful merely because it “discredits, humiliates, hurts or offends,” which is more care than these laws usually take.

It also changes very little because the people drawing the line day to day are the platforms, working from rules the Commission can rewrite whenever it wants. The edge of what a Canadian is allowed to say can shift without anyone in Parliament casting a vote.

So here is how a deletion goes. A platform decides it has “reasonable grounds to suspect” your post is child sexual abuse material or an intimate image shared without consent.

From that moment it has 24 hours to make the post inaccessible to every person in Canada. Down first, explained afterward. You can file representations and request a reconsideration, and your words stay gone the entire time you are waiting. Or someone skips you altogether and reports the post to the Commission, which can order it made “permanently inaccessible.” No judge appears anywhere in that sequence.

The definitions get bigger the longer you look at them. “Intimate content communicated without consent” now reaches AI images “likely to be mistaken for” a real recording of a person.

As a ban on revenge porn; reasonable, depending on how it’s implemented. But as written, those same words also cover a tasteless deepfake of a sitting politician, and the person sorting one from the other works for the company that gets fined either way.

Companies do not agonize over that distinction. They delete and move on.

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ACLU Sues After Facial Recognition Falsely Identifies Florida Man as a Child Abductor

Police arrested a man in Florida for attempted child abduction in a town he had never visited, and the only evidence linking him to the crime was an AI facial recognition hit. Represented by the American Civil Liberties Union (ACLU), he is now suing the officers and agencies who put him through it.

In November 2023, police in Jacksonville Beach, Florida, responded to a call about an attempted child abduction at a McDonald’s. Witnesses said an adult man allegedly tried to get the child, identified as a girl under 12 years old, to leave the restaurant with him. According to a police report, facial recognition software concluded with 93 percent confidence that the suspect was Robert Dillon.

In August 2024, Deputies arrested Dillon at his home in Fort Myers, Florida—hundreds of miles away, at the opposite end of the state. “Are you shitting me, man?” Dillon asked the arresting deputy. “I haven’t been out of Fort Myers in two years.” Further, he also said he had never been to Jacksonville Beach.

Dillon posted bail and pleaded not guilty to enticing or luring a child—a third-degree felony, punishable by up to five years in prison. More than two months later, prosecutors dropped the charges after his attorney provided evidence that he was at work on the day in question.

But that doesn’t excuse the fact that he was only arrested in the first place, and threatened with prosecution for a particularly heinous offense, because of shoddy police work.

The ACLU is now suing the city of Jacksonville Beach, as well as the individual police officers and officials involved in the case. According to the lawsuit, the responding officer viewed security camera footage of the suspect but didn’t take a copy; instead, he took pictures of the screen with his cell phone. “In the photos, the suspect image is low resolution, and the suspect’s face is partially shadowed and off-axis,” the lawsuit claims.

When an investigator queried the facial recognition system, it was with the officer’s grainy secondhand cell phone photos.

But there were other leads that police could have followed, to either bolster their case or point in another direction. For example, when he approached the girl, the suspect was picking up food that had been ordered ahead; this implies he had an online account, with contact information and a form of payment attached.

“These records could have been used to identify the actual person who placed the suspect’s order,” the lawsuit notes. “Upon information and belief, Jacksonville Beach PD personnel never requested or obtained mobile ordering records, payment data, or online account information from McDonald’s.”

Further, the McDonald’s manager recognized the assailant as a “regular customer”—likely precluding Dillon, who lived and worked on the other side of the state and did not frequently travel. Besides, at no point did investigators search footage for the suspect’s previous visits, either for higher quality images or transaction records. And once they settled on Dillon as a suspect, investigators could have gotten a warrant for his cell phone’s GPS data, showing whether or not he was at a fast food restaurant 300 miles away from his home on the night in question.

The lawsuit notes that when Dillon’s name came up, investigating officer Scott O’Connell queried the police database of license plate readers, which did not detect Dillon’s vehicles in Jacksonville Beach within the 48 hours surrounding the attempted abduction.

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Facial recognition watchlist made permanent in Christchurch supermarkets after trial

A Christchurch supermarket trial of facial recognition technology has been made permanent and extended to another store after showing measurable safety improvements.

After a three-month trial, Foodstuffs South Island has decided to keep the technology at New World St Martins and Pak’nSave Papanui and Moorhouse, while expanding it to New World Stanmore.

The initiative, which ran from October 2025 to January 2026, was designed to identify and manage individuals with a history of serious and harmful behaviour in stores.

Foodstuffs South Island retail head Kent Mahon said the results gave the co-operative confidence that the system could be deployed carefully and responsibly.

“The focus has always been on reducing harm. The trial showed we can do that while keeping accuracy high and respecting customer privacy,” Mahon said.

The facial recognition system scans images of everyone entering participating stores and compares them with a watchlist of known offenders.

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“Dystopian” Police.AI Launches in UK Amid False Arrests

A new UK national center launches within days, promising to find suspects in minutes, except it costs £115 million ($155M) and occasionally arrests the wrong person.

Police.AI, the body charged with pushing dystopian artificial intelligence across all 43 forces in England and Wales, comes with a seductive sales pitch from its frontman. Catch your suspect in minutes. Turn a weeks-long manhunt into a coffee break.

Alex Murray, National Crime Agency director and the National Police Chiefs’ Council’s first AI lead, wants facial recognition to do exactly that. The catch, and it is a fairly significant one, is that the technology keeps flagging innocent people.

Murray’s whole pitch is speed. “What took days, weeks, sometimes months can potentially take hours,” he said, describing AI tools that span CCTV analysis, searches of seized phones and the flagging of fake images.

He likes to point to a Bedfordshire fraud case where the software chewed through Romanian-language phone data from four suspects and produced guilty pleas. Notice the shape of the pattern, though. It is always a list of what the police get to do. The part where the rest of us get scanned, sorted and occasionally pulled off the street tends to fall off the slide.

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DYSTOPIAN Truck Tech: AI Scans Faces, Reads Lips & Checks Police Database BEFORE You Can Drive

A video exposing Ford’s dystopian patents for new vehicles has gone viral on X, fueling outrage over the accelerating war on personal vehicle ownership and freedom of movement. 

The clip details in-cabin cameras, biometric scanners, lip-reading AI, emotion detection, and real-time criminal database queries – all deciding whether your truck will let you drive.

In the video, the narrator states “imagine there was an emergency outside the truck… An accident…I jump in this truck. But it won’t shift into drive. Why? Because cameras and sensors inside of my cab won’t let me shift.”

“It detects that my eyes are big. There’s some emotion. Some panic. And doesn’t feel like I’m fit to drive. That isn’t science fiction. This is happening. Ford just filed patents,” he explains.

He continues: “Ford actually has a series of patents down at the U.S. Patent and Trade Office that deal with sensors and cameras inside their cab. And if that sensor determines you’re not fit to drive, the truck won’t shift from park to drive.”

The patents extend deep into control. Biometric systems scan face, iris, and fingerprint, cross-referencing law enforcement databases before allowing movement. 

“You wake up one morning, walk out to the driveway, climb into a vehicle with your name on the title… Before you go anywhere, before you’ve done a single thing wrong, your truck has already run your face through a law enforcement database. Ford’s own patent language describes this as ‘potentially useful for police,’” the narrator further outlines.

Lip-reading tech uses interior cameras and machine learning on vast mouth-movement datasets, plus inaudible sound waves. This enables not just voice commands in noisy conditions but also monitoring for targeted ads based on conversations. 

Ford Pro Telematics also already feeds live driver video to fleet managers.

This corporate push dovetails perfectly with government efforts to restrict mobility. Just weeks ago, Massachusetts Democrats advanced Senate Bill S.2246, directing MassDOT to set binding goals for slashing statewide vehicle miles traveled (VMT) under “climate” pretexts. 

The bill creates a new council to shove residents onto public transit, hitting rural drivers hardest who rely on cars for work, family, and essentials.

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Facial recognition to be ‘rolled out’ across UK after human rights challenge fails

Facial recognition systems will be introduced across the country, the government has said as it welcomed the failure of a legal challenge to the technology.

The case against the Metropolitan Police’s use of live facial recognition technology (LFT) in London was brought by two people over concerns it could be used arbitrarily or in a discriminatory way.

The cameras are usually mounted on vans in busy high streets and designed to identify people on police watchlists if they pass by.

Youth worker Shaun Thompson, one of the claimants, said he was misidentified by the technology. The other person bringing the claim was Silkie Carlo, from the group Big Brother Watch.

Their lawyer told the High Court that LFT would also make it “impossible” for Londoners to travel without their biometric data being taken.

But judges ruled on Tuesday that the claimants’ human rights had not been breached and the force’s policy gave “adequate indication of the circumstances in which LFR will be used”.

They also said the argument the technology risked discriminating against people due to their race had not been convincing.

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Another Wrongful Arrest Based on Faulty Facial Recognition Raises Growing Concerns

Jason Killinger walked into Reno’s Peppermill Casino in September of 2023, later that evening as he was exiting the building he would be arrested. The casino’s facial recognition system had flagged him as a “100 percent match” for an individual that had previously been banned from the property. The only problem? It was completely wrong.

After the system flagged Killinger, casino security would approach him, referring to him as “Mike”, an individual who had been previously removed from the property. Despite his insistence and ability to prove that he was in fact not Mike, security would surround and handcuff Killinger before calling the Reno Police Department. Shortly thereafter rookie Officer Richard Jager would arrive on the scene.

Killinger quickly proved he was not the man identified in the system, as he was carrying three valid forms of identification, including a Nevada Real ID compliant drivers license, his Peppermill player’s card, and a debit card, all with his name on it. When this wasn’t enough he offered to retrieve more from his vehicle, which included a pay stub, vehicle registration, and a medical card. Despite all of this copious documentation proving who he was, Officer Jager declined to investigate further, not bothering to look at any of his other identifying documents. Killinger would be arrested and charged with criminal trespass.

He would then spend 11 hours in police custody, only after a fingerprint check at Washoe County jail confirmed his identity would he finally be released.

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Mexico Speeds Up Biometric ID Rollout

Mexico’s government wants you to believe that handing over your fingerprints, iris scans, and facial data is voluntary. President Claudia Sheinbaum has said so publicly.

But by July 2026, every one of the country’s roughly 130 million mobile phone lines must be linked to a biometric national ID, and unregistered numbers get suspended on July 1.

Refuse the biometric credential and lose your phone.

The CURP Biométrica upgrades Mexico’s existing population registry code, the Clave Única de Registro de Población, from an 18-character alphanumeric string into something far more personal. The updated system captures face, fingerprint, and iris biometrics, packages them with a QR code and digital signature, and produces what amounts to a mobile-readable identity document tied to your body.

Registration happens at RENAPO and Civil Registry offices, where staff scan all ten fingerprints, both irises, take a facial photograph, and record a digital signature. You’ll need a valid photo ID, a certified CURP, and an original or certified birth certificate just to walk in.

The government has framed this primarily as a tool for addressing Mexico’s crisis of forced disappearances. The biometric data feeds into a Unified Identity Platform connecting the National Population Registry with the National Forensic Data Bank and records held by prosecutors and intelligence agencies, enabling real-time identity searches. That’s the stated purpose.

The actual system being built does considerably more than locate missing people. The legislation gives broad access to biometric and personal information to law enforcement, intelligence agencies, and the National Guard, and the law doesn’t require authorities to notify citizens when their data gets accessed. You won’t know who’s looking at your biometrics, or why, or how often.

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FC Barcelona Fined for Privacy Violations Over Biometric Data Collection

FC Barcelona got fined €500,000 ($579,219) for scanning the faces and recording the voices of over 100,000 members without doing the legal homework first.

Spain’s data protection authority, the AEPD, found the club had deployed biometric identity verification during a membership census update and processed all of it without a valid Data Protection Impact Assessment.

Members renewing their details remotely were required to either submit a facial scan through their device camera or record their voice. Both systems were live, both were processing biometric data at scale, and the documentation Barcelona produced to justify any of it didn’t meet the bar GDPR sets for high-risk processing.

Article 35 of the GDPR requires organizations to conduct a DPIA before deploying any system likely to create a high risk for individuals. Biometric data used for identification qualifies automatically.

Processing that touches more than 100,000 people, including minors, qualifies. Using new technologies qualifies. Barcelona’s system hit all three. The AEPD concluded the club’s documentation was missing the essential components of a genuine assessment: no real necessity and proportionality analysis, no adequate evaluation of what the processing actually risks for the people whose faces and voices it captured.

The AEPD’s decision in case PS-00450-2024 makes one point with particular clarity: consent doesn’t substitute for a DPIA. Barcelona had asked members to agree to biometric data collection, and members had agreed.

That agreement is legally irrelevant to the separate procedural obligation to assess risk before the system goes live. The GDPR treats them as independent requirements. Satisfying one doesn’t discharge the other.

What a valid DPIA actually requires, according to the decision, is a clear description of the processing, a genuine necessity and proportionality assessment, a detailed risk evaluation, proposed mitigation measures, and a residual risk assessment after mitigations are applied. Organizations that generate DPIA documentation as a compliance checkbox, without substantively working through those questions, remain exposed regardless of what consent language they put in front of users.

The appetite for facial biometric data has become near-universal across industries, and the Barcelona case lands in a moment when that appetite is accelerating faster than the rules meant to govern it.

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