--- title: Sardine AI Labs | Applied research on financial crime source_page: https://www.sardine.ai/ai-labs canonical: https://www.sardine.ai/ai-labs format: text/markdown description: Sardine AI Labs is an applied research group studying whether models can learn the structure of financial behavior well enough to catch attacks they were never taught to find. --- **Quick links:** [Human page](https://www.sardine.ai/ai-labs) · [Home](https://www.sardine.ai) · [Customers](https://www.sardine.ai/customers) · [Blog](https://www.sardine.ai/blog) · [Demo](https://www.sardine.ai/demo) --- # Sardine AI Labs | Applied research on financial crime Sardine AI Labs is an applied research group studying whether models can learn the structure of financial behavior well enough to catch attacks they were never taught to find. ## Advancing the frontier of intelligence to fight Sardine AI Labs is an applied research group building AI to tackle some of the hardest problems in financial crime. Grounded in Sardine’s network of device, identity, behavioral, and transaction data, we are developing models that can understand complex financial behavior and detect attacks they were never explicitly trained to find. ## Understanding the language of financial crime Our research tackles open problems in sequential modeling, transfer learning, adversarial robustness, and explainability. We test each advance against the demands of production risk systems, including detection performance, cross-institution generalization, and low-latency inference. Our goal is to turn advances in AI into measurable protection against financial crime. ## Learnings from our first foundation model for issuing risk Our first payments foundation model learned from unlabeled transaction sequences, then supplied new features to the issuing fraud model already in production. - 68%: improvement in fraud detection accuracy (AUC-PR) for a consumer card issuer that was held out from training dataset - 41%: improvement in fraud detection accuracy (AUC-PR) for a business card issuer that was held out from training dataset - 35%: more fraud caught from the same number of transactions ## Built on the fastest-growing dataset in financial crime Our research starts with the breadth of Sardine’s network and goes deep into the sequence of each customer’s financial behavior. - 6.5B+: Devices profiled - 441M: Consumer identities - 3.4M: Businesses screened - 6.58B: Transactions analyzed - $1.8T: Transactions protected ## Four questions shaping our work Financial crime is sequential, adaptive, and connected. Our research agenda is built around those realities. ## Offering $375,000 in fellowships We are awarding up to five (5) fellowships to independent researchers (students or faculty) at universities in the U.S. or Canada that can help us tackle our research topics. Applications close December 13, 2026. ## Recent publications