Score every transaction the way a fraud analyst would
Birdai catches the odd patterns that rules miss, without adding friction for customers who belong.
Rule engines create two problems, not one
Static thresholds are either too tight or too loose. Your team spends more time managing the rule set than managing actual fraud.
Missed fraud
Novel attack patterns slip through
A rule that wasn't written can't block a pattern it hasn't seen. Card testing campaigns, synthetic identity rings, and account takeovers evolve faster than rule update cycles allow.
False positives
Good customers treated as threats
Velocity triggers and device flags decline legitimate customers at high-value moments. Every false decline costs a transaction and risks a customer relationship that took real budget to acquire.
Three signal layers, one score
Each layer adds context the others can't see alone. Combined, they reflect how experienced fraud analysts actually think about a transaction.
Behavioral context
Each account builds a behavioral baseline over time. Birdai scores how much a given transaction deviates from that pattern, not just whether it looks unusual in isolation.
Graph signals
Fraud rings share infrastructure. Graph-based features surface shared devices, addresses, and account clusters that look clean at the individual level but reveal coordination at the network level.
Temporal pattern
Time-of-day, inter-transaction intervals, and session velocity all carry fraud signal. Birdai tracks cadence alongside transaction attributes to catch scripted and automated attacks early.
Numbers from three pilots
Based on internal benchmarks across 3 early-access payment platform pilots over a 90-day window.
The false-positive noise we were living with wasn't a feature of fraud prevention, it was a feature of our tools. Switching to behavioral scoring changed how the whole team thinks about the review queue.
Built for platforms that move money
Birdai is designed for fraud and risk teams at digital-finance operators with high transaction volume and an appetite for more precise tooling.
Digital wallets
P2P payment fraud exploits trusted sender relationships. Birdai adds behavioral context to identify authorized push payment scams before funds leave the account, not after the dispute window opens.
BNPL platforms
Buy-now-pay-later fraud clusters at origination. Birdai scores application intent signals so you can catch default risk before the first installment clears.
Payment gateways
Card testing and velocity abuse look different across merchant categories. Birdai adapts scoring to your transaction mix, reducing merchant-side chargebacks without blocking high-value legitimate orders.
Start with a 30-day pilot on your own data
We set up alongside your existing stack. No displacement, no long procurement cycle. You see signal quality on live transactions within the first week.