Discover how leading banks are using graph algorithms to uncover hidden risks, strengthen AI models, and deliver real-time ROI.
Inside you will discover:
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Why traditional systems miss connected risks and how graph algorithms reveal the full picture.
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How banks like JPMorgan Chase and Nubank use graph analytics to uncover fraud rings and drive measurable ROI.
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The six core algorithms powering modern fraud detection, AML/KYC, and customer intelligence.
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How graph-enhanced AI models improve recall, reduce false positives, and deliver regulator-ready explainability.
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Proven Forrester TEI findings validating a 229% ROI and payback in under six months.
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How to move from pilots to enterprise-scale transformation across risk, compliance, and customer intelligence.
Key Stats:
- $100M+ in annual fraud savings across top global banks
- 229% ROI and <6-month payback (Forrester TEI)
- 40% faster AML case resolution and 30% earlier intervention through graph algorithms
- $50M+ annual savings at JPMorgan Chase with 25% higher detection accuracy
- 3× recall improvement at Nubank, cutting losses by millions monthly
- Billions of relationships analyzed in milliseconds using TigerGraph’s massively parallel computation (MPP) engine
About TigerGraph
Trusted by top global banks, TigerGraph delivers real-time fraud detection at massive scale using advanced graph analytics.