Fintechs typically onboard customers at high volume and settle payments quickly, which leaves a narrow window to complete screening and spot suspicious activity. Mule accounts, account takeover and rapidly changing fraud patterns add pressure, and compliance headcount rarely grows at the same rate as customers and transaction volumes.

By automating the repeatable parts of the workflow: screening, risk scoring, alert triage and case handling. When customer, transaction and external risk intelligence sit in one connected system, growing volumes largely increase automated processing rather than manual review, and analysts spend their time on genuinely higher-risk cases.

Real-time screening with tuned matching logic keeps most customers moving without manual intervention, while risk-based rules reserve enhanced due diligence for the profiles that need it. Better match quality means fewer legitimate customers stopped for review, which shortens time to first transaction.

Yes. Monitoring rules and models can be configured around specific products and payment flows, flagging patterns such as structuring, rapid pass-through of funds, mule-network behaviour or activity inconsistent with a customer's profile. Alerts arrive in case management with the customer and screening context already attached.

ZIGRAM connects screening, customer risk assessment, transaction monitoring and investigation in a single workflow, backed by global risk intelligence. That gives fintechs consistent risk decisions across the customer lifecycle and the audit trail regulators expect, without bolting together separate point tools.