We promise fast payouts, but that leaves very little time to catch fraudulent claims. Today our claims specialists spot suspicious cases by hand, which does not scale. A good solution must flag risky claims within seconds, before money moves, plug into our app backend, explain why a claim was flagged, and keep pricing transparent.
Fintech · Payments · 200–1000 · Asia-Pacific #b037_10
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We are a payment gateway and bulk disbursement provider serving a very large base of online businesses in a fast-growing real-time payments market.
- Industry
- Fintech · Payments
- Size
- 200–1000 employees
- Region
- Asia-Pacific
- Tools budget
- $5K–20K per month
- Needs
- Fraud prevention. Fraudsters adapt within days, so our merchant risk rules need better models and faster feedback loops.Today: a real-time merchant risk engine built and sold in-house · Urgency: this yearChargebacks & disputes. Dispute volumes swing with merchant mix, and assembling representment evidence is still largely manual.Today: manual merchant dispute handling supported by internal risk rules · Urgency: this yearPayouts & disbursements. Bulk disbursements to bank accounts and wallets fail for many reasons, and tracing each failure is slow.Today: a bulk disbursal product it runs itself with growing volume · Urgency: this year
- Who decides
- head of product · procurement
- Expects from suppliers
- Real-time scoring with low added latency; Supports local instant-payment and card rails; Explainable decisions for merchant-facing teams
- Not a fit
- Tools without local data residency; Batch-only analytics with day-old data
- Stack
- cloud: AWS-class hyperscaler, Kubernetes, data warehouse: cloud
- Buying triggers
- scaling transaction volume, security incident risk
Needs
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Cooperation
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We wish for a lightweight routing layer that sits over instant bank rails, with automatic fallbacks and ready-made handling of bank error codes, so our small team stops hand-coding it. We would judge it by setup in days not months, local data residency, transparent usage-based pricing, and how little engineering time it needs afterward.
Our transaction monitoring floods analysts with alerts, and most turn out to be noise. Our compliance staff review each one and draft suspicious activity reports by hand. A good solution must cut false positives, handle digital asset flows and higher-risk business clients, explain why each alert fired, and speed up report drafting.
We wish for a fraud monitoring tool that plugs into our cloud warehouse and turns raw transaction data into always-on detection, replacing our ad hoc queries. We would judge it by how fast analysts can tune rules without engineers, whether alerts stay explainable, European data residency, clear pricing, and a team trial that proves value.
As a card provider for small and mid-sized businesses, we struggle to spot misuse on employee cards without blocking legitimate spend. Our analysts review rules by hand, and false alarms frustrate honest customers. A good solution must adapt quickly, explain its decisions, keep data in Europe, and fit our existing cloud setup.
We lend online across several products, and fraud schemes shift faster than our reviews can catch them. By the time losses show up, the pattern has already moved. We need earlier detection of new schemes, signals we can feed into our own decisioning, and full explainability. Card-present retail tools won't work for us. Who has handled high-volume online lending?
We open our platform to anyone, and bad actors keep abusing free credits and stolen payment methods. We need risk scoring at sign-up and at payment, decided in real time, with low false positives for honest developers. Retail-style fraud tools and manual review queues won't work. Clear APIs our engineers can wire into billing are essential.
We are rebuilding how we watch card transactions for fraud, and we must decide what to build ourselves versus buy. Our merchants are small and local, so patterns look different from big retail. A good solution must score in real time, combine explainable rules with models, and be proven on small-merchant portfolios. Enterprise-only pricing is a no.