Anti-fraud analytics embedded in your product
Fraud teams and merchants need answers in the moment: which corridors spiked chargebacks, which devices look anomalous, and where to intervene. QueryPanel embeds tenant-scoped anti-fraud dashboards with an AI assistant so each customer only sees their own risk data.
Product preview
Desktop and mobile inside your app
Mocked browser and phone frames show how QueryPanel looks embedded—AI answers and charts scoped to each customer tenant.
Open cases
128
+12%
Avg risk score
64
-3
Blocked txn
4.2k
+8%
Chargeback rate by corridor
AI assistant
“Which payment corridors had the highest chargeback rate last 30 days?”
SEPA→LATAM cards led at 2.8% chargebacks (↑0.6 pts). Device reuse clusters drove 41% of disputed volume.
Risk pulse
Ask about disputes on the go
Open cases
128
Avg risk score
64
Chargeback rate by corridor
Ask
Which payment corridors had the highest chargeback rate last 30 days?
Best fit
Payments, marketplaces, and fintech products that expose fraud ops to customers or internal risk teams.
Must-have
Strict tenant isolation so one merchant never sees another’s disputes or device fingerprints.
QueryPanel angle
Headful React workspace with AI charts, plus optional headless Node SDK for zero-trust execution.
Short answer
What anti-fraud analytics should look like inside a SaaS product
Anti-fraud analytics for SaaS means embedding risk dashboards and natural-language answers inside your product so merchants and analysts investigate chargebacks, velocity spikes, and device anomalies without exporting CSVs to a separate BI tool. QueryPanel’s primary product is its headful React SDK with a Notion-like dashboard workspace and AI assistant for tenant customization.
- Every chart and AI answer is scoped to the authenticated tenant.
- Analysts ask questions like “show me 3DS failures by BIN” and get charts in-product.
- Ship defaults fast, then let each customer customize their risk views.
Product fit
Questions your customers already ask
Fraud surfaces fail when they only show static KPI tiles. Merchants need conversational investigation on their own data—without your team writing a custom report for every corridor.
- “Which SKUs drive the most friendly fraud?”
- “Compare false-positive rate after our rule change.”
- “Show refund-to-chargeback conversion by issuer.”
Architecture
Tenant-safe fraud insights without a second BI stack
Mint short-lived JWTs with organization and tenant claims on your server. QueryPanel generates tenant-aware SQL, runs it through controlled infrastructure, and renders the React workspace inside your app. For stricter boundaries, the headless Node SDK keeps credentials and query results on customer infrastructure.
More solutions
FAQ
What is anti-fraud analytics in an embedded product?
It is customer-facing fraud and risk reporting—chargebacks, disputes, velocity, and device signals—rendered inside your SaaS with per-tenant isolation and optional AI Q&A, instead of a shared internal BI workspace.
How does QueryPanel keep fraud data isolated between merchants?
Tenant identity comes from server-minted JWTs. SQL generation and execution carry that tenant context so charts and AI answers only return the requesting merchant’s data.
Can fraud analysts ask natural-language questions?
Yes. QueryPanel’s headful React SDK includes an AI assistant that turns questions into charts and SQL-backed answers inside the embedded workspace.
Do we need a data warehouse before launching?
No. QueryPanel connects to databases such as PostgreSQL, ClickHouse, BigQuery, and MySQL. A warehouse is optional, not a prerequisite.
When should we use the headless Node SDK instead?
Choose the headless Node SDK when you need a fully custom fraud UI and zero-trust execution boundaries where credentials and query results stay on your infrastructure.