3 Major Pitfalls of Intelligence Work

Dmitry Ivanov is the founder and Head of Intelligence at SA West Global Intelligence, a private competitive intelligence firm based in Riga, Latvia and that operates in Europe, Middle East, Southeast Asia and Africa. He has over two decades experience in the business intelligence industry. Dmitry sat down in February with Fraudbeat to discuss open-source intelligence and the intelligence gathering process for business purposes.

Unfortunately, due to technical difficulties, the video recording of this interview is not available. However, below is a transcript of the conversation edited for length, meaning and narrative flow.

Distinguishing between intelligence work and investigations

Ronen Shnidman: We have a lot of readers at Fraudbeat who are fraud fighting professionals who deal with all sorts of payments fraud, insurance fraud, what have you. But how does a business intelligence investigation specifically focused on doing due diligence on a business entity differ from a typical fraud investigation?

Dmitry Ivanov: When we talk about business intelligence, we’re talking about a whole discipline built around helping decision makers make better choices. And most of those choices are about what happens next. What’s likely to happen? How will the other side react to our move? And then how should we respond to them?

Yes, part of that is assessing reliability—but not historical reliability. Compliance and investigations already cover whether someone has been reliable or lawful. Intelligence asks: Will they be reliable going forward, under changing conditions?

That’s the future-oriented question.

Investigations (including what some call ‘intelligence investigations’) are backward-looking. They examine suspicious events, anomalies, things that don’t look like legitimate business. Or it may not even be fraud. Maybe the person honestly doesn’t know how to run a business properly. Not a crook. Just… not good at making money. That’s still a past fact. Intelligence takes that finding and asks: what happens next time they’re under pressure?”

Tailoring Intelligence to Decisionmakers’ Needs

RS: So what is intelligence? What would be a deeper look into an entity and what would you be doing in a deeper report?

DI: Let me put it in the simplest way I can.

Imagine you’re dating a woman. You’re thinking long-term — marriage, kids, the whole thing.

What people don’t realize, from a due diligence perspective, is this: success doesn’t just depend on her being perfect. You could be totally wrong for her. She might hate guys like you. Or maybe she’s very attractive — really your type — but you just don’t click. Not because anything’s wrong. She hates your favorite movie. Maybe she’s a Republican, or she spells “transcendental” with no ‘c’. Little things, but they add up to a bad fit.

So you hire a private investigator. What does he tell you? He’ll tell you if she’s a citizen of another country. If she’s legally free to marry. If she already has a boyfriend. Who her family members are, what they do for a living. Stuff like that.

But he won’t even try to answer your real question: “Can you actually build a happy family with this woman? Will you both be happy together?” Not because he’s incapable—but because answering that would require him to completely reframe his approach. Different questions. Different methods. A whole different mindset.

That’s where intelligence starts. Intelligence is when you stop staring at the person in front of you and you change the frame of the whole situation. You step back and you look at your joint future. Will this work or not? And fairly speaking that’s exactly what real due diligence should be.

Here’s another example—totally made up, but it makes the point. Let’s say someone hires us to dig up information on a company in Colombia. We do deep research and we find out that this company, and the people connected to it, shipped a truckload of cocaine two months ago. So we go back to the client and say, “You should not work with these people. They just sold a truck full of cocaine.”

And the client says, “Great. That’s exactly why I need them.”

See the problem? From an intelligence perspective, due diligence isn’t just about collecting facts. It’s about understanding why the client cares about this deal in the first place. What’s their real interest? What’s the underlying situation? You have to adjust your research to their needs—not just report on the past.

Intelligence Pitfall #1: Understanding Intelligence Culture

RS: Well, what are some traps or pitfalls that an intelligence investigator should be wary of when conducting an investigation?

DI: Here’s something a lot of people miss. Intelligence mostly operates in a hostile environment. That means we’re usually not working in our own countries. We’re somewhere else—different countries, distant regions. So to do our job and deliver results to customers, we need partners everywhere: China, Vietnam, the US, Israel, the UK. You name it.

And the first—and most common—mistake intelligence practitioners make? They undervalue the intelligence culture of the countries they’re actually working in.

By “intelligence culture,” I mean the set of unspoken rules, habits, and assumptions that an intelligence community inherits from its national culture. It shapes what they consider normal, what they consider valuable, and what they don’t even think to question. It’s in the language they use, the myths they tell about their own successes, the shortcuts they take for granted.

But here’s the key: people don’t just work for a country’s intelligence apparatus. They internalize it. A retired Israeli officer, a former Russian analyst, an ex-American case officer — each of them considers the way their agency did things as true intelligence. Not a version of it. The version. Everything else looks like a mistake.

When you don’t understand that intelligence cultures differ, you design projects wrong from the start.

Let me give you an example. I work on cases involving Israel, so I work with Israeli partners.

As someone shaped by Russian intelligence culture, I might expect them to deliver information the way I’m used to getting it. But my partner is a retired Israeli officer. He has his own framework — his own idea of what’s important.

So he does things I never expected. I look at his work and think: “Too complex. Too much time, money, effort, etc.”

But for him? Those things are easy. The sources are right there. And those questions are of first importance.

And the opposite is also true. What I can do in a blink of an eye, they might not be able to do at all in their country. Probably they never even think that the problem could be approached from this particular perspective

Now, don’t get me wrong. There are unified methodologies widely adopted by the community like the very same Intelligence Community Directives, and a long list of more or less specific frameworks mostly structured by types of intelligence. On paper, it all looks very organized.

But here’s the reality: when you actually reach a source in a distant region or hire a local vendor, you’re usually not dealing with big companies that take intelligence methodology seriously. Most of the time, you’re dealing with very local intelligence companies, journalists, private contributors, or simply collecting information from human sources who have no formal intelligence training—but are likely experts in manufacturing, finance, sales, or IT. And they share information in a way that works for them, not in a well-structured format.

So why don’t we just hire the top players in the local market instead? They must take globally adopted intelligence methodology seriously. 

Two reasons.

First, they’re more expensive by default. I mean that they may charge more just because they know the craft, the language and the method. 

But second — and this is just as important — when you’re working on a sensitive project, you try to avoid sharing the full picture. Instead, you break the project into small pieces and distribute them across many vendors. That way, even if two vendors cross paths, they won’t be able to piece together what you were really trying to find out, who the ultimate recipient is, or what the overall project involves. And frankly, off the record, this option is even more expensive and time-consuming. Money matters the most — but not always. So if you hire someone who delivers valuable intelligence for a fixed price in a short timeframe, more than likely, your data is at higher risk of being reassigned to a single, less expensive company.

Actually, top players in the local market are very niche players in intelligence. They serve local clients and occasionally win pieces of global projects managed by larger companies in the field. Still, there are very focused companies — serving only banks, retail, and manufacturing, etc. These companies, while small and focused, still have an inflow of local and international projects. That’s the trap for professionals: there’s no middle ground between a very local player — a private contributor — and an intelligence company serving international clients on a global or semi-global scale.

So getting back to the main point: intelligence culture matters. And look, it’s not just about having a process. It’s about realizing that the people you’re working with halfway around the world — they don’t think like you. They don’t work like you. If you don’t take the time to understand their culture — how they collect information, what they think is important, how they actually report things — you’re going to design the project wrong from the start. And here’s what happens when you get it wrong: time runs out, you’ve got a day or two to write your report, and you’re stuck with raw data that doesn’t fit your framework. Not because they failed — but because their approach was completely different from yours. That’s true whether you’re hiring local vendors or setting up your own regional office to work alongside your analysts.

Intelligence Pitfall #2: Trust Assumptions

DI: It may sound counterintuitive, but people build trusting relationships in intelligence. That’s really what it comes down to. In a nutshell, intelligence is nothing but knowledge based on the ability to build trustful relationships with people — including those who would never voluntarily give you that knowledge.

Just like the old anecdote: intelligence is a search for friends among enemies, and counterintelligence is a search for enemies among friends. Certainly it’s a simplification, but — as often happens — simplification can be more insightful than the most detailed and complex model.

To be in the intelligence field, you have to be trusted by the Chinese. And by the Japanese. And by someone living in Iran. And they’re all different. None of them see trust the same way. None of them build friendships the same way.

Without these relationships, you simply cannot do your work properly. And here’s the thing — even if you both speak English, or Chinese, or Japanese, it doesn’t matter how good your language skills are. You have to understand what’s at the core of local understandings of friendship, trust, and loyalty. How do they build those bonds? What does it even mean to be a trusted person in their world?

Now, here’s the challenge. While many operatives are very good at building these relationships in specific regions or cultures, it’s extremely hard to find someone who can do this on a global scale. And that’s the real skill — not just building trust but building it across worlds that don’t naturally connect.

Historically, Western intelligence craft originated not from spies working under deep cover, but from diplomats: respectful, educated, well-established, smart people who worked for the benefit of their countries — or, in practice, worked with deep respect for both the client and the target, even when their interests diverged.

Intelligence Pitfall #3: Data Manipulation and Source Accuracy

DI: A third trap is data manipulation. Now, this is hardly a secret—it happens. There’s an ongoing global phenomenon, and it’s not just disinformation originating from any single region. Misinformation campaigns have gone global. What we’re facing now is a situation where intentional inaccuracies are being planted directly into primary sources, including government datasets.

When I entered this market about twenty years ago, it was extremely rare to find inaccurate information in government data sources. Back then, if you had access to public records and official datasets, you could reasonably assume you were looking at the truth. That is no longer the case. Today, you have to verify every single piece of information—even when it comes from a high-profile primary source like an official government dataset.

RS: Why is that? I can understand needing to verify OSINT sources. But government data? Wouldn’t you trust it?

DI: The world has changed. Five, six, even ten years ago, the world was relatively unified. There was a general movement toward transparency—almost like we were all becoming one family. That era is over. Today, the world is full of conflicts. And in adversarial relationships, governments act to protect their interests. The easiest way to do that is to manipulate primary sources. Journalists and activists fight over opinions. States fight over reality itself.

And I see this in many regions around the world. Not just in the former USSR or Eastern Europe. Even in the West, where we tend to believe that governments don’t engage in that kind of trickery. But they do.

Now, here’s the real problem—and this applies even when we’re not dealing with sensitive issues. Let’s look at popular sources for investigative journalism, compliance, and private investigations. Take major leaks like the Panama Papers, WikiLeaks, or the Epstein Files. These collections contain thousands or even millions of documents. They generate dozens of scandals and hundreds of articles. But ask yourself this: can we be absolutely certain that every single document in those leaks is authentic?

What if someone injected just a handful of fabricated documents into that massive collection—a few fake emails, a doctored photo, a forged contract—specifically to manipulate public opinion? Or even more targeted: to influence the judgment of a single decision-maker, like a judge, a regulator, or a corporate board member? With so much data, would anyone ever notice? Probably not. At the very least, you would have to prove that a specific piece of data is inaccurate—which is quite complicated when the source in general looks and is accepted as authentic. 

And that is precisely why data manipulation has become one of the most dangerous traps in intelligence work today. It’s not just about governments misleading each other anymore. Not just about widely adopted manipulations of public opinion with the use of social and public media. It’s about not being able to trust the very sources we’ve relied on for years—even the ones that seem above suspicion.

Returning to Trust Based Relationships

We haven’t even talked about deep fakes yet, or the decidedly ambiguous impact that AI has had on intelligence analysis. None of this does much to bolster our confidence in sources, in the information they contain, or in the quality and professionalism of analysts themselves.

So in the end, almost the only anchor we have left in these difficult circumstances is the ability of members of the intelligence community to build trustful relationships with each other. That’s a little ironic, because we were taught to be extremely suspicious—that is part of the craft, yes, but only a part, and far from the main one. And these relationships should be built on mutual respect for the national—and certainly intelligence—cultures of every member of the community.