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January 14, 2025

Why AI-powered Email Protection Became Essential for this Global Financial Services Leader

Hear the cybersecurity transformation story of this leading money transmitter, who facilitates more than $9 billion in remittances via thousands of agent locations across the US serving more than two million active customers.
Inside the SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
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Jan 2025

When agile cyber-attackers don’t stop, but pivot  

When he first joined this leading financial services provider, it was clear to the CISO that email security needed to be a top priority. The organization provides transfer services to millions of consumers via a network of thousands of agent locations across the US. Those agents are connected to hundreds of thousands of global payers to complete consumer transfers, ranging from leading financial institutions to small local businesses.

With this vast network of agents and payers, the provider relies on email as its primary communications channel. Transmitting billions of dollars every year, the organization is a prime target for cyber criminals looking to steal credentials, financial assets, and sensitive data.

Vulnerable to attacks with gaps in email security and visibility

The CISO discovered that employees were under constant attack by phishing emails impersonating his company’s own executives. The business email compromise (BEC) attacks were designed to deceive employees into sharing credentials or clicking on malicious links.

Upon discovering that their Microsoft 365 tenant lacked secure configuration, the CISO implemented necessary changes to strengthen the service, including enabling authentication controls. While his efforts significantly reduced BEC attacks, cyber criminals changed their tactics, sending employees malicious phishing emails from seemingly valid email accounts from trusted domains like Google and Yahoo. The emails passed through the organization’s native email filters without detection.

The CISO also sought to strengthen defenses against third-party supply chain attacks that could originate with any of the hundreds of thousands of third-party agents and payers the company works with around the world. While the larger institutions typically have sophisticated email security strategies in place, the smaller businesses may lack the cybersecurity expertise needed to effectively secure and manage their data, putting the organization at risk.

While the CISO knew the company was vulnerable to phishing and third-party threats, he didn’t have visibility across the flow of email. Without access to key metrics and valuable data, he couldn’t get the crucial insights needed to quickly identify possible threats and adjust security protocols.  

Skilled analysts bogged down with low-level tasks

Like many enterprise organizations, this leading financial services provider relied on a crew of highly skilled analysts to respond to alerts and analyze and triage emails most of their workday. “That shouldn’t be how we operate,” said the CISO. “My role and the role of my staff should be to focus on more strategic projects, support the business, and work on important new product development.”

Balancing user experience with mitigating threats

Enabling greater email security measures without negatively impacting the business, user experience, and customer satisfaction was a daunting challenge the CISO and his security team faced. Imposing restrictions that are too stringent could restrict communication, delay the delivery of important messages, or block legitimate emails – potentially slowing down money transfers, frustrating customers, affecting employee productivity, and impacting revenue. However, maintaining controls that are too permissive could result in serious outcomes like data theft, financial fraud, operational disruption, compliance penalties, and customer attrition.  

Self-Learning AI is a game changer

After conducting a thorough POC with several modern security solution providers, this global financial services provider chose the Darktrace / EMAIL an AI-driven email security platform. The CISO said they chose the solution for two key reasons:

First, Darktrace / EMAIL offers modern capabilities

  • Self-Learning AI uses business data to recognize anomalies in communication patterns and user behavior to stop known and unknown threats
  • Secures the organization’s entire mailflow across all inbound, outbound, and lateral email
  • Protects against account takeover attacks by identifying subtle anomalies in cloud SaaS
  • Catches sophisticated threats like impersonations, session token misuse, adversary-in-the-middle attacks, credential theft, and data exfiltration

Second, they pointed to Darktrace’s experience, innovation, and expertise

  • Deep cybersecurity and industry knowledge
  • Demonstrated customers successes worldwide
  • At the forefront of innovation and research, establishing new thresholds in cybersecurity, with technology advances backed by over 200 patents and pending applications

Moreover, and most importantly, this organization trusted Darktrace to deliver on its promises.  And according to the CISO, that’s just what happened.

Significantly reduced phishing threats and business risk

Since implementing Darktrace / EMAIL, the threat posed by BEC attacks has dropped sharply. “Phishing is not an issue that concerns me anymore. I estimate we are now identifying and blocking more than 85% of threats our previous solution was missing,” said the CISO. The biggest factor contributing to this success? The power of AI.

With Darktrace / EMAIL, this leadingglobal financial services provider is identifying and blocking more than 85% ofthe phishing email threats its previous solution missed.

AI wasn’t originally on the financial service provider’s list of criteria. But after seeing AI in action and understanding its potential to vastly scale their detection and response capabilities–without adding headcount, the CISO determined AI wasn’t an option but an imperative. “AI is essential when it comes to email security, it’s an absolute necessity,” he said.  

Darktrace / EMAIL’s Self-Learning AI is uniquely powerful because it learns the content and context of every internal and external user and can spot the subtle differences in behavioral patterns that point to possible social engineering attacks. Through patented behavioral anomaly detection, Darktrace / EMAIL continuously learns about the organization’s business and users, based on its own operations and data, adjusting security protocols accordingly.  

For example, when clients are transferring large amounts of money, they are required to send photos of their driver’s licenses and passports via email to the organization for verification – accounting for a large percentage of its’ inbound email. Darktrace / EMAIL recognizes that it’s normal for customers to send this sensitive information, and it also knows that it’s not normal for that same sensitive information to leave the organization via outbound mail. In addition, Darktrace identifies patterns in user behavior, including who employees communicate with and what kind of information they share. When user behavior falls outside of established norms, such as an email sent from the CFO to employees the CEO would not typically communicate with, Darktrace can take the appropriate action to remove the threat.  

“After the implementation, we gave the solution two weeks to ingest our data and learn the specifics of our business. After that, it was perfect, just amazing,” said the CISO.  

Boosted team productivity and elevated value to the business

With Darktrace / EMAIL, the organization has successfully scaled its detection and response efforts without scaling personnel. The security team has reduced the number of emails requiring manual investigation by 90%. And because analysts now have the benefit of Darktrace / EMAIL’s analytics and reporting, the investigation process is much easier and faster. “The impact of this solution on my team has been very positive,” said the CISO. “Darktrace / EMAIL essentially manages itself, freeing up time for our skilled analysts–and for myself–to focus on more important projects.”  

The security team has scaled its detection and response efforts without scaling personnel,reducing the number of emails it manually investigates by 90%

Increased visibility delivers business-critical insights

You can’t control what you can’t see, and with zero visibility into critical data and metrics, this financial services provider was at a serious disadvantage. That has all changed. “Something that I love about Darktrace / EMAIL is the visibility that it provides into key metrics from a single dashboard. We can now understand the behavior of our email flow and data traffic and can make insight-driven decisions to continuously optimize our email security. It’s awesome,” said the CISO.  

An efficient user interface also improves productivity and reduces mean time to action by enabling teams to easily visualize key data points and quickly evaluate what actions need to be taken. Darktrace / EMAIL was developed with that experience in mind, allowing users to access data and take quick action without having to constantly log into the solution.

Keeping the business focused on cybersecurity

The leadership of this global organization takes information security very seriously, understanding that cyber-attacks aren’t just an IT problem but a business problem. When it came to evaluating Darktrace, the CISO said numerous stakeholders were involved including C-level executives, infrastructure, and IT, which operates separately from information security. The CISO initially identified the need, conducted the market research, engaged the target vendors, and then brought the other decision makers into the process for the solution evaluation and final decision. “Our IT group, infrastructure team, CTO and CEO are all involved when it comes to making major cybersecurity investments. We always try to make these decisions jointly to ensure we are taking everything into consideration.”

The organization has reached a higher level of maturity when it comes to email cybersecurity. The ability to automate routine email detection and investigation tasks has both strengthened the organization’s cyber resilience and enabled the CISO and his team to contribute more to the business. His advice for other IT leaders facing the same email security and visibility challenges he once experienced: “For those companies that need greater insight and control over their email but have limited resources and people, AI is the answer.”  

Darktrace / Email solution brief screenshot

Secure Your Inbox with Cutting-Edge AI Email Protection

Discover the most advanced cloud-native AI email security solution to protect your domain and brand while preventing phishing, novel social engineering, business email compromise, account takeover, and data loss.

  • Gain up to 13 days of earlier threat detection and maximize ROI on your current email security
  • Experience 20-25% more threat blocking power with Darktrace / EMAIL
  • Stop the 58% of threats bypassing traditional email security

Inside the SOC
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
Written by
The Darktrace Community

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September 17, 2026

The Problem of Re-defining Human Value in the Agentic Age

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Newsfeeds are constantly informing us about the rapid escalation of agentic AI systems. These systems move far beyond simple machine-based computations, and  the focused, defined and bounded assistance that most AI systems started out as.

The next evolution of AI will harness the agentic properties of orchestration, automation, and heightened value-chains in IT, taking on the burden of workflow management, not just workflow delivery.

In nearly all of these instances, promises are made such as ‘this will free up human time’ or ‘this will allow people to focus on higher-order strategy’. However that message is delivered, one thing is clear: in ceding the orchestration and management of work to increasingly sophisticated AI agents and agentic systems, human value will be elevated to a particular and specific layer: the ability to judge its outputs.  As AI takes on more tasks, humans should be able to focus on a higher level of governance; making sure the decisions that AI offers us are ethical, responsible and worthwhile.  

But there are two major problems with that approach.

This blog discusses the problem of how Agentic systems are re-shaping how we review information, where we fit in, and when we make decisions.  It also discusses the problem of how the increased flow of confident, generated information affects the way we make judgement.  This blog considers how human judgement needs to adapt, and how a behavioral defense approach – using techniques pioneered by Darktrace – can help us do that.

The challenge of knowing where human judgement belongs

As we confer more automated decision-making to agentic systems, it might look increasingly less like ‘granting permissions’, and more like ‘surrendering authority’.  

The judgement layer for AI-generated work is not a fixed boundary. We have become used to the idea of a ‘human in the loop’ (HITL) and, historically, relationships between humans and IT systems were reasonably clear and bounded.  Computer and software systems were programmed to carry out certain tasks or automated functions, and humans could control the gates and decision points where actions were undertaken. Even across highly complex computational workflows, human interaction was a controllable node within the process; we were able to configure and regulate. But in the agentic age, where that human interaction sits, and what it can influence shifts every time AI systems are granted autonomy.  

This leads us to the first problem: if humans are moving themselves (or are being moved) into the ‘judgement’ part of the value chain, exactly where and when do we exercise that judgement?  

Humans are no longer the sole shepherds of computer-based or software-controlled outputs.  We are at times at least one step further (and slower) behind the new agentic shepherds.  We might also be blind to what they are doing.  Not only might we be removed and blind to the actions of our AI shepherds, but with the challenge of unknown, unapproved AI systems operating beyond our control, humans might not even know that our work is being shepherded by an AI at all.  Simply put, with the advent of greater levels of autonomy and orchestration, humans are at risk of not even knowing where to apply our newly-extended powers of strategic judgement.

Shadow AI – the use of unapproved AI systems or processes – is a growing threat to the role of effective governance and oversight. Shadow AI isn't just the AI you can't see. Its the AI you already know about being used in an unapproved way. The ability to generate effective oversight of the AI systems you use (or that are used on your behalf) will be increasingly important to ensure that human judgement in the AI value chain is effective, and deliberately placed.

The problem of what makes good judgement

The second problem lies in how flawed human judgement can be.  Humans are historically, notoriously, and, sometimes dangerously, unreliable when it comes to exercising judgement.  Humans are prone to the worst kinds of bias, the seduction of malign influence, and the sometimes-overwhelming urge to succeed. AI has long had a known flaw of operating with sycophancy, providing outputs that tend to agree with or flatter the human user.  But as AI grows ever more effective, there is a risk of both hyper-enablement (where humans increasingly and knowingly enable AI despite potential harm), as well as the greater risk of suggestion. Both of these aspects could skew the newly-elevated input of human judgement.

Imagine a highly competent AI system that has just orchestrated and managed a dizzying array of processes and workflows.  The AI is designed to present the human decision-maker with recommendations; based on analysis, comparison and other programmed factors.  This is where the human judgement layer is enabled.  But what if that judgement is summarily diffused by an AI-based recommendation that emulates the decision, provides plausible but unattractive alternatives, then suggests (or, worse, directs) the human end-user to take a particular course of action.

The risk here is that you are given a recommendation, tailored to your preferences (which the AI has learned, or which you have divulged), and which appears to make perfect sense.  It appears to be a well-weighted recommendation, with sound arguments that tap into our inherent biases or inclinations so that a specific decision-path is followed. With the growth of agentic systems specifically designed to match user profiles (from Cowork agents to ‘digital twin’ models), the likelihood of agentic influence could badly skew human judgement or, at the least, devalue the proposition that humans are taking a higher-layer of strategic control over AI-based decisions.

If AI convincingly recommends something that may be problematic, it can be difficult to discern both accurate data, and the context required to make the right judgement.

Given the two problems described above, the job of exercising valuable human judgement in the agentic age can draw down to these two questions:

  • When should humans intervene in the agentic process?  
  • How can we make the best possible judgement calls?

What humans contribute that AI cannot

For all the flaws that make human judgement unreliable, people have the edge over even the most sophisticated and powerful AI systems when it comes to issues such as ethics and social context.  An AI system can, with startling granularity, rank the value of adopting a new business proposal: offering predictive metrics on costs, returns, market value, time-to-deliver operations, conformance with legal registers, etc.  But it can’t tell if the business proposal is ethically sound, or if the business venture will potentially affect groups outside of the analyzed proposal. It can’t tell you if the CEO has a ‘bad feeling’ about this effort.  It can’t tell you if this is the right thing to do.  

The ability to add social context, balance complex interpersonal dynamics, understand nuance, and to go beyond what seems economically reasonable is where human judgement can add value.  

Human judgement is difficult to encapsulate in metrics. And the way we train our development may need to adapt too. Rather than building up a gradual, experiential knowledge base, we should think about training the skill of judgement itself; especially for an agentic age.

How behavioral security strengthens AI governance

If this all feels like a vicious circle (‘I need AI help to make good judgements’ / ‘AI can twist what I need to judge’) it needn’t be. The key to this is having a defense-in-depth approach, with tools that can actually help.

This is precisely where behavioral security becomes important. The complex and nuanced way that humans exercise judgement is often rooted in our ability to recognize behavior that doesn't look right. We may not always be able to articulate it immediately, but we can often identify when an action, recommendation, or outcome feels inconsistent with the context around it. As AI systems take on more responsibility across the decision chain, preserving that ability to recognize meaningful deviations becomes increasingly important.

Darktrace’s / SECURE AI is designed to do exactly that. It applies behavioral security to AI ecosystems, helping organizations understand how people, AI tools, identities, and agents interact across the business. By learning the patterns of normal AI usage and surfacing activity that deviates from those patterns, it provides security teams with the context needed to investigate risk, understand unusual behavior, and make informed governance decisions. Rather than relying solely on predefined rules or assumptions, this behavioral understanding helps organizations distinguish between expected AI activity and behavior that warrants closer scrutiny.

This matters because we are already in an era of information overload. If humans are expected to elevate their value through strategic judgement, the ability to do this without being overwhelmed by data (good or bad) will be critical.  

We need the ability to discern when we're being misled by AI, and whether our judgement calls are being made on the basis of accurate, contextual information. Darktrace / SECURE AI provides that additional layer of defensive security for activity we cannot easily see. Whether it is suspected Shadow AI or skewed recommendations, the net result is a protected organization, where users can more effectively use AI to make positive judgements.

For those where that judgement is a critical skill (both individuals, as well as those working in security teams), improving our metacognition - the ability to understand information in a broader context - will supercharge the value of human judgement. When those judgements are grounded in context rather than assumptions we have better information to make sound decisions.

Conclusion

Human judgement is a skill that is honed over time and experience.  Darktrace’s / SECURE AI employs the same principles, but at machine-speed. Rather than influencing or directing, Darktrace / SECURE AI offers AI-enabled assurance; providing human-based judgement with the right context to make a balanced decision.  

What we judge can be valued by the legitimacy of its outputs. For AI, those outputs are valued on the speed and accuracy of the information provided.  Increasingly for humans, the value of our outputs will be based on the validity of our judgement, and how we justify our decisions in ways that engineer confidence.  

Humans often know more than we can express, while AI is prone to expressing more than it truly understands. Humans can bridge the context AI often fails to appreciate. When that judgement is supported by relevant, impartial AI systems, this is the future space where good AI governance will be exercised.

Discover Darktrace / SECURE AI.

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Jason Lusted
AI Governance Advisor

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September 4, 2026

Darktrace Advances Incident Investigation and AI-Agent Security with OpenAI Daybreak Models

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Earlier this year, Darktrace joined OpenAI’s Daybreak Defense Network to explore how their cyber capabilities can be integrated within Darktrace products and services to transform how security teams move from signal to action.

At the heart of this work is Darktrace's behavioral understanding of customer environments and identification of complex security incidents, combined with OpenAI models that can add context to help explain why an incident matters and its potential impact on the business. By bringing these capabilities into defensive workflows security teams already use, the goal is to give defenders not just greater visibility, but the context and guidance they need to act with confidence.

Since joining the program, we've been working with OpenAI to explore how these capabilities can address specific security challenges for defenders.

The problem we're solving

Attackers continue to change how they operate, including by using AI to increase the speed and scale of some techniques. Security teams are already managing a large volume of alerts, and the question isn't just what's happening, but how it could affect the organization. Even when an incident is fully investigated and correlated, technical severity alone doesn't tell a security team how much it actually matters to the business. That same challenge extends to internal AI adoption. As organizations adopt more AI systems and agents, security teams need visibility into their behavior, access and activity, along with the broader business context needed to identify and investigate potential risk.

Darktrace's Adaptive AI™ builds a detailed, organization-specific picture of what's normal for each environment, and uses that picture to investigate threats and identify complex security activity across domains. OpenAI's models can build on Darktrace's correlated, technically prioritized incidents by adding context that can help defenders understand what may be at stake.

What we're building

Our work is focused on two areas: supporting security investigation and response, and helping defenders identify risky behavior across enterprise AI systems and agents.

The first aligns Darktrace's behavioral understanding with OpenAI models to support  security investigation and prioritization. Darktrace's Adaptive AI continuously learns the unique patterns of normal behavior within each customer it protects, creating a deep, organization-specific understanding of its digital estate. When unusual activity emerges, OpenAI's models can draw on that context to help analysts investigate the incident, understand its significance and assess potential business consequences — reducing the need to manually assemble context from fragmented signals.

Second, we are exploring how these capabilities can support AI-agent and runtime security through Darktrace / SECURE AI™. OpenAI’s Daybreak models can build on the detections and visibility Darktrace / SECURE AI provides, connecting signals across a customer's environment and help defenders identify potentially risky behavior involving AI systems and agents. Activity that might appear isolated can instead be connected with related signals, helping defenders investigate the broader context and determine appropriate remediation.

Darktrace brings deep cybersecurity expertise, an evolving understanding of each customer's environment, and AI-driven identification of threats across the digital estate. Through the Daybreak Defense Network, Darktrace is exploring how OpenAI models can augment those capabilities in defensive security workflows — supporting incident investigation and response and improving visibility into AI-agent and runtime risk.

These capabilities are still in development, and we're excited to continue building on this work.

To learn more about how Darktrace continues to innovate to meet today's most pressing security challenges, register for our upcoming launch broadcast here.

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