---
title: Graph AI for Financial Services | Fraud, AML and Identity
description: How banks use graph and AI to catch fraud rings, close AML cases 40% faster and resolve identities, with results from real deployments.
---

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Report

# Connected **Intelligence**

How graph and AI are changing fraud, identity and AML in financial services

Fraud rings, mule networks and synthetic identities all hide in the same place, the links between customers, accounts, devices and payments. This report shows how financial institutions combine graph analytics with AI to see those links in real time, and what it delivered in practice, from faster AML investigations to tens of millions in annual savings.

### Download the free report

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## Results from financial **institutions**

### $50M+ in annual savings

$50M+ in annual savings at one global bank, with 25% higher detection accuracy after adding graph to its fraud stack.

### 40% faster AML case resolution

40% faster AML case resolution and 30% earlier intervention, because investigators see the full network behind an alert.

### Identity resolved across channels

Linking devices, emails and accounts exposes synthetic identities that pass single-record checks.

### One graph, several teams

Fraud, AML and customer teams worked from the same connected view instead of separate silos.

## What the report **covers**

![8429366\_ecommerce\_shopping\_online\_attention\_magnifier\_icon 1](https://info.tigergraph.com/hubfs/8429366_ecommerce_shopping_online_attention_magnifier_icon%201.svg)

### How graph and AI work together across fraud, AML and identity

![8388125\_2business\_finance\_office\_organize\_structure\_icon 1](https://info.tigergraph.com/hubfs/8388125_2business_finance_office_organize_structure_icon%201.svg)

### Case studies from leading banks, including JPMorgan Chase and Nubank

![8463505\_human\_anatomy\_body\_brain\_organ\_icon 1](https://info.tigergraph.com/hubfs/8463505_human_anatomy_body_brain_organ_icon%201.svg)

### The six graph algorithms behind fraud, AML and KYC systems

![8441437\_essential ui\_app\_web\_protection\_shield\_icon 1](https://info.tigergraph.com/hubfs/8441437_essential%20ui_app_web_protection_shield_icon%201.svg)

### Forrester Total Economic Impact findings on ROI and payback

![8538419\_web development\_website\_web design\_programming\_file code\_icon 1](https://info.tigergraph.com/hubfs/8538419_web%20development_website_web%20design_programming_file%20code_icon%201.svg)

### How to move from a pilot to enterprise-wide deployment

## Who should **read it**

Fraud, financial crime and data leaders at banks, payment companies and fintechs looking for proven ways to apply graph and AI across risk and compliance.

## Graph AI in financial services, **answered**

### What are the best use cases for graph in fraud and financial crime?

The strongest use cases are fraud ring detection, anti-money laundering investigations, KYC and entity resolution, synthetic identity detection and customer 360. Each depends on relationships between customers, accounts, devices and payments, which graph analytics can trace in real time.

### How does graph analytics detect money laundering?

Money laundering spreads funds across many accounts and entities to hide its source. Graph analytics follows money through those hops, finds circular flows and shared ownership, and ranks risky networks. Investigators get a full picture of each case, which cuts false positives and speeds up resolution.

### Can graph work with our existing fraud and AML tools?

Yes. Graph usually sits alongside current transaction monitoring and case management systems, feeding them network risk scores and linked-entity context. Teams keep their workflows and gain visibility into connections those tools miss, which helps reduce false positives in AML alerts.

![](https://info.tigergraph.com/hubfs/BG_Ready%20to%20Transform%20Your%20Banking%20Operations.jpg)

## See connected intelligence **at work**

Download the report for the full case studies and ROI data. To explore it for your institution, book a TigerGraph demo.

[Download the free report](https://info.tigergraph.com/connected-intelligence-how-graph-ai-are-redefining-fraud-identity-and-trust-in-financial-services#hs_cos_wrapper_widget_1763824094072)

## Related **reports**

[**Architecting AI that Banks can Trust** Why knowledge graphs are the missing layer for AI in banking →](https://info.tigergraph.com/architecting-why-knowledge-graphs-are-the-missing-layer?hsLang=en-us) [**The Identity Graph** A connected foundation for authentication, fraud, AML and Customer 360 in banking →](https://info.tigergraph.com/the-identity-graph-a-new-foundation-for-authentication-and-customer-360?hsLang=en-us)

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