Phase 0 findings now available · Phase 1 in development

FinCrimeBench™ — the independent benchmark for AI in fraud & AML

As institutions move to a zero-trust posture, fraud and AML detection becomes the line that has to hold. FinCrimeBench is the expert-built, threat-driven standard for how reliably frontier AI models actually perform that work — measured against the ≥90% accuracy operational deployment requires. Live results below; new threats added through 2026. Take a look at our leaderboards and request the report.


The Benchmark Will Eat Finance

Simon Taylor's Fintech Brainfood featured a dedicated deep dive into the launch of FinCrimeBench, analyzing how rigorous, domain-specific evaluation is shifting the balance of power in financial services AI. See the feature.


Leaderboards

NOTE: Figure 2 in the original Phase 0 whitepaper has been corrected to accurately reflect the results across the four LLMs tested.

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What we've found so far

We probed four frontier LLM providers across 110 expert-curated prompts spanning select fraud typologies. Performance on conceptual tasks was generally competent. Performance on tasks closest to operational decision-making was not.

Example: Risk Level Assessment

Of the task categories we probed, none matters more operationally than risk level assessment — the judgment that determines whether a case is escalated, a transaction is held, or a restriction is placed on a customer.

The pattern across providers was wrong in the direction that matters most, with confident-sounding rationale.

BEST FRONTIER MODEL

1 in 3

WRONG risk ratings on a four-tier classification. The other three providers ranged from 46%–53% accuracy — meaning the typical frontier model got nearly half of risk ratings wrong.

How FinCrimeBench is built

Prompts curated by practitioners

110 prompts in Phase 0, written and reviewed by financial crime experts with hands-on experience in fraud and AML. Each prompt is paired with an expert answer key reflecting how a competent senior practitioner would respond.

Anchored to recognized standards

The taxonomy and scoring framework draw on guidance from the OCC, FFIEC, FATF, FinCEN, and NIST, with the methodology referenced in the whitepaper.

Provider-neutral and independent

FinCrimeBench is independent research from CoveLabs.ai. While we are in discussions with LLM providers about financial crime training data, FinCrimeBench operates under separate governance with no provider influence over methodology, evaluation, or published results.


Get Involved

Executive Summary

A two-page overview of Phase 0 findings, methodology, and what's coming in Phase 1. Designed to be read in five minutes and shared with your team.

We'll send the summary to your inbox right away.

Full Technical Whitepaper

The complete Phase 0 report — provider-level results, prompt-category breakdowns, scoring methodology, and the detailed findings behind the headline numbers.

We prioritize access for senior leaders accountable for fraud and AML risk at financial institutions, fintechs, and RegTech providers, and LLM researchers.

Executive Briefing

A 30-minute conversation with senior fraud and AML leaders. We walk through findings relevant to your domain — including provider-level results not published in the whitepaper.

We review briefing requests on a rolling basis. Typically confirm or decline within a week.

About CoveLabs.ai

CoveLabs.ai is leading this independent research effort focused on evaluating and improving how AI systems perform on financial crime tasks. We were founded by industry and AI experts with decades of hands-on experience in fraud and AML, and FinCrimeBench is our first published initiative.

© 2026 CoveLabs.ai LLC · CoveLabs.ai · LinkedIn

FinCrimeBench™ is a proprietary benchmark developed and owned by CoveLabs.ai LLC. The benchmark name, methodology, taxonomy, prompts, expert answer keys, scoring framework, evaluation results, and all associated content, deliverables, and derivative works are the exclusive intellectual property of CoveLabs.ai LLC. The contents of this site and the available whitepaper documents, including all analysis, findings, figures, and text, are protected by copyright. No part of this work may be reproduced, distributed, or used to train, fine-tune, or evaluate machine learning models without the prior written consent of CoveLabs.ai LLC, except for personal, non-commercial reference and for the limited fair-use purposes recognized under applicable law.

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Privacy Policy

Effective Date: July 2026

Last updated: July 2026

1. Overview

This Privacy Policy explains how CoveLabs, Inc. and its affiliates, including FinCrimeBench (“CoveLabs,” “FinCrimeBench,” “we,” “us,” or “our”), collect, use, disclose, and protect personal information when you visit or interact with our websites, including fincrimebench.ai, submit forms, request research, register for events, or otherwise communicate with us.

By using our website or submitting information to us, you acknowledge that we may collect, use, and disclose your information as described in this Privacy Policy.

2. Information We Collect

We may collect personal information that you voluntarily provide to us, including when you:

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We may also automatically collect certain technical and usage information when you visit our website, such as IP address, browser type, device information, pages visited, referring pages, and interactions with our website. We may collect this information through cookies, analytics tools, server logs, or similar technologies.

3. How We Use Your Information

We may use personal information for the following purposes:

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If you request FinCrimeBench research, register for an event, download materials, submit a form, or otherwise provide your contact information to us, we may use your contact information to send you related FinCrimeBench communications. These may include new research, updates to prior research, benchmark updates, event invitations, webinars, product or service updates, and other information that we believe may be relevant to your professional interests.

You may opt out of receiving marketing, research update, or event-related communications at any time by using the unsubscribe instructions included in our emails or by contacting us at admin@covelabs.ai. Even if you opt out of these communications, we may still send you non-marketing communications, such as responses to direct inquiries or administrative messages related to your interactions with us.

FinCrimeBench is designed to provide research, benchmarks, insights, and related information concerning financial crime, compliance, risk management, and related topics. If you provide your contact information to request or access FinCrimeBench materials, we may send you additional FinCrimeBench-related communications from time to time.

These communications may include:

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We aim to be transparent about why you are receiving these communications. Our emails may explain that you are receiving the message because you previously requested FinCrimeBench research, registered for an event, submitted a form, or otherwise expressed interest in FinCrimeBench.

You may opt out of these communications at any time.

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We may use cookies, pixels, analytics tools, and similar technologies to collect information about how visitors use our website. This may include information about pages viewed, links clicked, time spent on the website, referring websites, browser type, device type, and general location information.

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We do not sell personal information.

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Where applicable data protection laws require us to identify a legal basis for processing personal information, we rely on one or more of the following legal bases:

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We retain personal information for as long as reasonably necessary to fulfill the purposes described in this Privacy Policy, including to provide requested materials, send FinCrimeBench-related communications unless you opt out, manage our relationship with you, maintain business records, comply with legal obligations, resolve disputes, protect our rights, and enforce our agreements.

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