Your AI transformation starts with one question

If your fraud or AML vendor won't let you export data in an industry-standard format, your AI transformation is already in trouble – regardless of what tools you invest in.

We experienced this firsthand recently. While trying to connect an AI agent to our Outlook inbox for a routine task, we found it couldn't search the data meaningfully. The exact same agent worked flawlessly with plain text files and Notion. The difference wasn't the AI model; it was data accessibility. It's a small example, but it points to a much larger structural issue facing fraud and AML teams today.

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A signal from an unlikely source

Earlier this year, Microsoft quietly changed the underlying file format for Power BI – moving from a proprietary, machine-opaque .pbix structure to one that is human-readable and human-writable. For a company whose competitive advantage has long rested on proprietary lock-in, this is a massive shift.

The reasoning is straightforward: if data is trapped in a format that AI agents cannot read or query, customers will eventually go elsewhere. The switching cost that once protected legacy vendors is eroding fast. Fraud and AML platform vendors face exactly the same dynamic.

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What open data makes possible

The teams best placed to take advantage of this shift aren't necessarily the ones with the biggest budgets – they're the ones working with entirely open infrastructure. Once your data is genuinely open, the relationship with any vendor changes. Gaps can be filled without waiting for an arbitrary product roadmap. Custom requirements can be automated without raising a support ticket.

The most immediate value AI delivers today isn't in large, expensive, multi-year implementations. It's in the specific, one-off automations unique to each business – and that value only materialises when data is openly queryable.

In practice, for fraud and AML teams, that means

• An AI agent can read case data directly and draft a SAR narrative in seconds, not hours.
• A compliance lead can query investigation history using natural language, without submitting a report request.
• A new detection rule can be tested against historical data immediately, rather than waiting for a vendor release cycle.
• When a regulator or law enforcement agency requests data in a specific format, automation handles it – rather than the work falling to analysts.
• Cross-functional teams – data science, engineering, compliance – can all work from the same source of truth, rather than passing exports back and forth.

None of this requires a breakthrough in AI. It requires data that is accessible.

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One question worth asking your vendor

Before investing a single dollar further into AI capabilities, put a direct question to your current fraud or AML platform provider:

"Can we access our own data – today, in a format that is openly queryable – without going through you?"

If the answer is anything other than a clear yes, that constraint will heavily limit your return on AI. The teams that move their fraud and AML data onto open infrastructure in the near term will gain a definitive operational advantage. The ones that wait will find themselves negotiating that transition under pressure, rather than on their own terms.

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Why we built Fortify on Snowflake

This is why Fortify is warehouse-native. We don't ask you to move your data into our platform – we work with it where it already lives, inside your Snowflake environment. Every query, every model, every automation runs against tables you own and control.

That means your AI strategy isn't gated by us – it's enabled by us. When a new capability emerges, your team can apply it directly to your fraud and AML data without waiting for our release cycle, without an integration project, and without a single row of sensitive data leaving your perimeter.

We built Fortify this way because we believe the most useful thing a vendor can do is get out of the way – and make sure your data is always working for you, not locked away from you.

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