The Transaction That Never Happened: How Fraud Stifles Our Economy

Forbes

28-05-2025

Hacker and laptop made of binary code. Ones and zeros. With copy space.
Across industries, economies, and every digital touchpoint in between, fraud is quietly compounding costs, not just by stealing money, but by stopping legitimate transactions before they even happen.
While fraud attempts make headlines when a heist lands, there's a much more insidious problem right under the surface: the transaction that never happened because of our attempts to stop fraud before it happens.
These are the losses you can't always see in your quarterly report: the customers you turned away because your system flagged them as risky, the potential revenue you missed by setting your fraud filters too tight, and the businesses that slowly destroy the trust between themselves and their consumers because a few bad actors shaped how they treat everyone.
And it's only getting worse. Fraud is now multimodal.
It doesn't show up just as stolen credit cards or phishing emails like it used to. Today, fraud arrives through fake IDs, deepfaked voices, spoofed IP addresses, social engineering over messaging apps, and increasingly, through AI-generated personas that can pass casual scrutiny Any app, voice, or face can be weaponized through any channel imaginable.
According to recent estimates from Juniper Research, merchants are projected to lose over $362 billion globally to online payment fraud between 2023 and 2028.
Meanwhile, the systems designed to catch this fraud are often blocking legitimate transactions as well with false positives routinely outnumbering actual fraud.
The question that beckons an answer is simple, with answers that have deep roots: how do you protect your customers without treating them like suspects?
'Fraud doesn't just take the money in your account,' says Forter CEO and co-founder Michael Reitblat. 'It takes the trust in your system. And in trying to protect against it, too many companies go too far. They build walls so high that even their best customers can't climb over them.'
He would know.
Reitblat co-founded Forter with the belief that the future of fraud prevention shouldn't be focused solely on tightening the filters, but applying them smarter. That means knowing your customers deeply enough to recognize them when they show up, even if their device, location, or behavior looks slightly different than last time.
'We need to start by flipping the mental model companies approach fraud with,' Michael begins. 'Instead of assuming guilt and proving innocence, we should assume the customer is legitimate and be fast and smart enough to catch when they're not.'
The reason why we don't see this approach being the norm is that it requires data, huge volumes of it, and systems that can learn over time. Forter's platform, for example, sits on top of a global network of merchants, letting it see patterns no single merchant could identify on their own. It's a distributed immune system for the digital economy.
Much of the tech that modern fraud-detection relies on wasn't available just a few short years ago, and the industry is evolving faster than ever. While the tech is a key drive, Michael argues that the key to handling fraud better lies within consumer and vendor psychology. Simply put, we need to reframe what success in fraud prevention looks like.
'Everyone measures fraud prevented. But what about sales saved?' he asks. 'If your system blocks 99% of fraud but also turns away 10% of good customers, that's not success. That's loss. And it's often invisible, as is the lack of trust that underpins it all.'
Zoom out from payments, and the same principles of trust apply across cybersecurity.
Gil Geron, co-founder and CEO of Orca Security, has spent years helping companies secure their cloud environments. But for him, the real challenge is psychological as much as it is technological.
'Too much of cybersecurity is built around fear,' Geron says. 'Fear of breaches, fear of compliance issues. But when you lead with fear, you create friction. You slow down developers, frustrate employees, and erode trust internally.'
The new wave of cybersecurity professionals often argue that when everything is cloud-first and developer-led, security can't be a blockade, it has to be a partner. Geron agrees and notes that the best security is invisible: it runs in the background, integrates seamlessly, and empowers teams rather than policing them.
'What we need is secure velocity,' he explains. 'Move fast, but safely. Don't just scan the environment once a month, understand what's happening in real time, with context. This way we ladder up to trust organically, and remove the sources of friction that keep good actors from transacting on the platforms they want.'
The idea of context over details is a critical one. In fact, it can be transformative when weaponized on behalf of the consumer.
Whether you're approving a payment or flagging a risky container in the cloud, the system needs to know what normal looks like in order to detect what's not.
That requires machine learning, behavioral baselines, and yes, trust in your users who sometimes order flights to Aruba at 2am right after rejoining Netflix and ordering take-out from a Nepalese restaurant for the first time with the same credit card.
'Security isn't about saying no as the default,' Geron says. 'It's about having the necessary trust to say yes to the right people, in the right way, at the right time.'
Thomas Brunner, CEO of Gigapay, sees the consequences of broken trust up close.
His platform helps creators and freelancers get paid across borders. But in a world where fraudsters can fake identities and automate scams, the burden of trust has never been higher.
'In the creator economy, you don't have time to run a KYC check manually or hold payments for weeks,' Brunner explains. 'If you don't trust the user instantly, the whole model falls apart.'
Gigapay uses a mix of real-time risk scoring and user behavior analysis to spot anomalies. But the key, Brunner says, is not punishing everyone for the mistakes of a few.
'Fraud is the exception, not the rule,' he says. 'If we design our systems assuming everyone is trying to cheat, we break the experience for the 99% who are just trying to earn a living.'
The stakes are especially high in the gig economy, where payouts can make or break someone's rent. A missed transaction is a data point of deep actuarial interest for sure, but it's much more than that for those who it impacts. In fact, it's often a livelihood.
'Trust is the platform,' Brunner says. 'Without it, the economy doesn't move.'
Sometimes, the block comes from a lack of trust in the tools we use themselves.
Brooke Hartley Moy, CEO of Infactory, is building an AI insights engine designed for enterprises. Her platform helps companies find answers they can trust, pulling not just from the open web, but from verified datasets and curated sources.
'We make billion-dollar decisions based on AI,' Moy says. 'But the foundation of that AI is often unclear. Where did this answer come from? Who vetted it? Can I trust it?'
That uncertainty, she argues, is its own form of friction. Friction we should work hard to minimize.
Companies hesitate to deploy AI not because it doesn't work, but because they don't know when it will, or whether it might do something entirely different than tasked.
'Accuracy can't be an afterthought,' Moy explains. 'Having trust in your tools and the answers they give you is the difference between action and paralysis. If you can't trust the output, you won't move forward. And that's another kind of transaction that never happens.'
For her, solving this trust gap is about structure and standards. We start with what the AI says, and we trust it based on how transparently and reliably it says it.
'The future of decision-making requires not just intelligence,' Moy adds. 'It requires provenance.'
At Nightwing, an intelligence solutions company spun out of RTX, Chief Technology and Data Officer Chris Jones is thinking of fraud, trust and everything above on a bigger scale.
His job is to figure out how to protect critical systems, not just from fraud, but from coordinated attacks on the scale of the digital infrastructure of entire countries.
'There isn't a more poignant set of threat vectors than the ones we're seeing now,' Jones says. 'And it's not just about stopping bad actors. It's about making sure the good ones can still operate.'
He sees a future where cyber offense and defense break through their silos and blossom into strategic complements that build the foundations for trust across the entire economy.
'We've been playing defense for years,' he notes. 'But if we want to maintain a global digital order, we have to think about sustainability, resilience, and sometimes, deterrence.'
In other words: just like in commerce, the real cost of a breach isn't just what's stolen. It's what's prevented. In the end, friction grinds the strongest of gears down to a halt.
If attacks deter innovation, stifle engagement, or shake public confidence, they succeed without breaching a single firewall.
'The blue team can win,' Jones says. 'But we have to scale them faster than the red team evolves. That means tools, talent, and trust. It means reducing friction for the people doing the right thing.'
Fraud captures our attention and it is easy to over-index on it just because of how often it is the signal that breaks through the noise.
But its most dangerous form is quiet.
It hides in checkout forms that never get filled, apps that go unopened, accounts that never activate. It sits in the unseen shadows of the economy. The almost-purchases, the never-hires, the frozen budgets and the client who never returns.
Preventing this form of friction is first and foremost a design challenge. Those who want to surmount this challenge need to build systems that can treat trust as the default instead of the reward for perfect compliance.
In the end, what drives growth isn't just the blue team's defense or a tighter fraud-filter. Instead, it's a firm belief that the system will work as intended. That the transaction will go through. That the other side is who they say they are.
And when that belief is protected, the economy doesn't just survive.
It thrives.