In boardrooms, trust is often described as a value. But in the digital economy, it’s something far more fragile – a technical condition.
Trust determines whether customers transact, whether partners connect their systems, whether regulators grant operational freedom, and whether markets continue to believe in an organisation’s stability. Yet many leaders underestimate how quickly that trust can collapse.
It doesn’t happen gradually. It happens suddenly.
When cyber risk begins to translate into real-world impact, often through financial crime, organisations experience what I call a trust-collapse moment – the point where they can no longer determine what is real fast enough to respond effectively. This doesn’t happen because technology has failed. It happens because visibility has failed. And once visibility collapses, leadership loses something far more valuable than systems or data.
They lose time.
In cyber-enabled fraud, time determines whether organisations disrupt the attack early or discover it only after financial loss and trust damage have already begun.
In this blog, I’m exploring why the traditional separation between cybersecurity and fraud teams is creating dangerous blind spots, and why organisations need better visibility across the entire attack lifecycle. I’m partnering with Mastercard to look at how the convergence of cyber and fraud intelligence can help organisations detect threats earlier, disrupt attacks before transactions occur, and ultimately protect trust at scale.
One example of this in practice is Mastercard Threat Intelligence, which brings together global fraud signals with cyber threat intelligence to provide earlier visibility across the attack lifecycle—connecting signals that would traditionally sit in separate teams.
In early testing, this approach enabled the identification and takedown of malicious domains impacting nearly 9,500 eCommerce sites, linked to an estimated $120 million in fraud.
What this demonstrates is simple: when organisations can see the attack earlier, they create the opportunity to act before it becomes a loss—and before trust begins to erode.
The Question No One Could Answer
I’ll never forget the look on the CISO’s face when he realised his team had detected the breach six weeks before the fraud team discovered the losses.
He’d done everything right. His team had flagged the anomaly. They’d investigated. They’d documented. But, they hadn’t connected it to fraud because fraud “wasn’t their domain.”
By the time both teams were in the same room, millions had been stolen and thousands of customers were affected. The CISO kept asking the same question:
“How did we see the breach and still lose the money?”
The answer? Because seeing isn’t the same as knowing. And knowing isn’t the same as acting.
This wasn’t an isolated incident. It’s a pattern I’ve observed across financial services, retail, and healthcare organisations. Not a predictable timeline, but a predictable pattern that organisations only recognise once it’s too late.
The Trust-Collapse Timeline
The timeline varies, but the pattern doesn’t.
Day 0: Initial breach. Unusual activity is detected – but without context, it’s dismissed as a “low-level anomaly.”
Days to weeks: Attackers establish access and begin extracting data. No visible financial impact yet.
Weeks later: Stolen credentials are tested. Fraud teams begin to see anomalies – but without visibility of the breach.
Shortly after: Fraud losses appear. Investigations escalate, still treated as a financial issue.
Only then: The connection is made. What appeared as isolated signals are revealed to be part of the same attack chain. This is the trust-collapse moment.
The killer question is this: Where in this timeline could your organisation have disrupted the attack?
If your answer is “when fraud appears,” you’re reacting to symptoms. If your answer is “at the point of breach,” you have visibility across the attack chain.
Most organisations don’t.
The Cost of Getting it Wrong
When trust collapses, the financial impact is measurable and severe. IBM’s 2025 Cost of a Data Breach Report found that lost business, driven by customer turnover and reputational damage, remain substantial, with the global average breach cost at $4.44 million. Research analysing major data breaches shows stock prices declining between 3.5% to 7.8% in the weeks following public disclosure, with recovery to pre-breach levels taking an average of 46 days.
But the timeline reveals something more troubling – the issue isn’t how long the attack takes. It’s how long it takes to connect the signals. Because in most cases, organisations have days or weeks to intervene. They just can’t see the full picture in time.
The Dangerous Divide
This is a structural problem many organisations still face. Cybersecurity and fraud teams operate in parallel worlds. Cyber teams focus on breaches, vulnerabilities, and threat actors. Fraud teams monitor suspicious transactions, financial anomalies, and payment patterns.
Both disciplines are highly specialised and perform critical work. However, attackers don’t respect those boundaries, with modern attacks moving fluidly across them.
Fraud rarely starts at the point of transaction. It almost always originates as a cyberattack, weeks earlier, with stolen credentials, probed systems, compromised merchant infrastructure, and quietly extracted data. Only later does the financial symptom appear.
The data illustrates this disconnect clearly with 57% of global fraud leaders report being notified of cyber breaches only after fraud losses begin. Unfortunately, by that stage, the attacker has already achieved their objective.
Payment fraud is no longer just a financial issue for fraud teams. With 81% of fraud teams responding faster to threats when collaborating with cyber, it’s clear this is a visibility problem – and a cybersecurity challenge that directly impacts the organisation’s bottom line.
The Shift from Detection to Intelligence
For years, cybersecurity strategies have prioritised prevention – firewalls, endpoint protection, fraud detection systems. These remain essential. But resilience in today’s threat landscape increasingly depends on something deeper – intelligence.
Threat intelligence allows organisations to connect signals that would otherwise remain isolated. By analysing cyber intrusion indicators alongside fraud anomalies and merchant vulnerabilities, organisations gain visibility across the entire attack lifecycle.
Instead of detecting fraud after it occurs, they can disrupt the attack long before financial transactions ever take place.
This is the shift from detection to intelligence. And it’s what defines mature cyber resilient organisations.
Leading organisations are now implementing systems that surface real-time alerts when cyber indicators – merchant compromise, digital skimmer deployment, unusual access patterns – suggest fraud is forming. Card testing attempts are flagged before they scale. Merchant vulnerabilities are surfaced before they’re exploited.
The technology to bridge this gap exists. But the question is: are organisations structured to use it, because when cyber and fraud intelligence sit in separate systems, they see fragments of data, limited to their own systems.
Attackers, on the other hand, see the whole – operating across the entire ecosystem.
What Success Looks Like
The organisations that will thrive now and in the coming decade won’t simply respond well to incidents. They’ll prevent the trust-collapse moment from happening in the first place.
That requires visibility across the full attack chain as well as collaboration between teams. In a world where threats move at machine speed, discovering risk only after financial loss appears is no longer sustainable. The organisations that succeed will be those that:
- See the attack forming early
- Connect signals across cyber and financial domains
- Enable real-time collaboration between cyber and fraud teams
- Act before trust begins to fracture
In the digital economy, trust is no longer a soft concept. It’s critical infrastructure. Protecting it requires threat intelligence that moves faster than the attacker, and visibility that connects cyber threats to financial risk before the trust-collapse moment arrives.
Organisations serious about this are investing in unified threat intelligence, bringing together cyber threat data and fraud insights to create a complete picture of risk.
Not to react faster. But to act earlier.
Now I Want to Hear from You
What signals do you think organisations are still missing before fraud losses begin?
Have you experienced the trust-collapse moment in your organisation? How did you close the visibility gap?
Join me on LinkedIn for the conversation and share your perspective in the comments.
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In the spirit of full disclosure: I’ve received compensation for promoting this thought leadership blog. I only align myself with organisations and solutions I believe in – those that genuinely address the challenges I research and write about. Mastercard, a longstanding partner, is one of them.
Mastercard Threat Intelligence, is the first threat intelligence offering applied to payments at scale. The solution brings together Mastercard’s fraud insights and global network visibility with curated cyber threat intelligence from Recorded Future’s platform to help payment fraud and merchant compliance teams at issuing and acquiring banks proactively detect, prevent and respond to cyber-enabled fraud.
Threat intelligence data has already helped Mastercard’s ecosystem partners identify and take down malicious domains that were responsible for the theft of payment card data. Since market testing began over the course of six months, these malicious domains had impacted nearly 9,500 ecommerce sites and were linked to an estimated $120 million in fraud.
Learn more at: Mastercard here https://mstr.cd/4mIF0Nc
