Chainalysis Targets Faster Fraud Detection With New Automation

Chainalysis has launched a new automation feature aimed at letting investigators and compliance teams run common blockchain analyses without writing code, as crypto scams increasingly scale through AI and organised laundering networks.

The feature, called Workflows, offers prebuilt templates that standardise recurring investigative steps. Chainalysis said it reduces reliance on custom SQL or Python and makes it easier to repeat the same checks across multiple cases. 

Senior product manager Ekim Buyuk said the tool is designed to ask investigation-level questions, such as which wallets, entities, or time windows matter, rather than requiring users to understand data schemas.

We plan to expand to hundreds of no-code workflows over time. These mini applications will enable users to automate even their most complex tasks. We’re prioritizing outcomes our customers care about most.

Chainalysis

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Protecting Users From Scams

Chainalysis is framing the release around rising fraud workloads. Buyuk cited company research claiming AI-enabled scams extract 4.5 times more money from victims, arguing that scam networks are quick to adopt new technology and investigators are being asked to monitor more complex patterns.

The company also argues that onchain investigations can miss the true scale of fraud when incidents are viewed one by one. A single theft may look minor, but tracing can link many small losses to broader networks with large aggregate totals.

In a recent report, Chainalysis estimated crypto scams and fraud drained about US$17 billion (AU$26.01 billion) in 2025, driven by impersonation schemes and more industrialised operations using AI, deepfakes and professional money laundering.

Read more: From Metaverse to Institutional Money: Why Real-World Assets Are Blockchain’s Real Breakthrough