Panel: The Hidden Value behind Cryptoanalytics
summary
Cryptoanalytics uses the public ledger to detect scams and trace hacks faster than legacy finance — examples cited include Sam Bankman‑Fried’s rapid unmasking and public tracing of alleged Hamas funding — and claims up to $4.5B lost from wrong addresses and ~$20B in fraud exposure. Practical tools: query chains via Google BigQuery and SQL, train machine learning/LLMs on labeled on‑chain patterns, and embed analytics as wallet co‑pilots. Challenges are sheer data volume, many new chains, and lagging real‑time feeds; startups built analytics stacks since 2016 and are integrating AI into product flows.
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chapters (11)
- 0:00Welcome
- 1:47Value of crypto analytics
- 5:24Fraud and crime prevention
- 8:53Adoption challenges
- 9:57Smarter investments
- 12:51Reputation and trust
- 16:43Standing out in market
- 20:18Learning resources
- 23:57Choosing tools
- 26:08Future of crypto analytics
- 30:29Q&A
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