Realistic distributions
Velocity, amount, counterparty fan-out, currency mix, time-of-day cadence — the
statistical shape of the synthetic stream matches what production systems actually
receive, so the system under test cannot tell it from real traffic in shape.
Adversarial patterns on demand
Specific typologies — structuring, smurfing, mule-network fan-out, bust-out fraud,
layering chains — can be injected at controlled prevalence levels. The team running the
test knows exactly where the needles are and can score the haystack accordingly.
Fully synthetic, fully shareable
No real customers, no real accounts, no real identities. Streams can be reproduced,
archived and shared between teams without privacy, GDPR or banking-secrecy concerns — they
are simply not personal data.
Reproducible by design
Streams are seeded and deterministic. The same seed produces the same stream every time,
so test results are comparable across runs, across versions of the system under test, and
across teams.