Blits.ai

BLITS.AIManage supplier listing

A continuously-built cross-institution money-mule graph plus the investigator dispositions on top of it. Nodes are accounts, customers, devices, IP addresses, postal addresses and phone numbers; edges are payment flows, updated continuously from onboarding and payment data. Enriched with external signals the vendor ingests: scam reports from other banks, confirmation-of-payee mismatches, industry and central-bank mule lists, and law-enforcement requests. The valuable residue is the labelled outcome layer: per-account mule-likeness scores with the behavioural reasons attached (rapid in-and-out, pass-through balances, sudden change after dormancy), graph-derived cluster and layering-chain membership, circular-flow detection, agent-drafted fund-flow case narratives with timelines, and the investigator's ultimate restriction or recall decision. Vendor-published outcome evidence from a live deployment: 4x false-positive reduction and 82% fraud-loss reduction at bunq (vendor claim), across 6 public deployments