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1
Add PostgreSQL
Connect your payments ledger or warehouse. See Add connectors.
2
Index and mark key tables
Flag transactions, payments, fraud scores, chargebacks, and settlements.
3
Ask your first question
Try: What is payment approval rate by payment method for the last 30 days?
4
Build the dashboards below
Give risk and treasury teams a shared view of volume and operational health.
See it in Vizkraft
Your data
Tables to mark during indexing
- Transactions and payments — volume and approval rate
- Fraud scores — flagged rate and model performance
- Chargebacks — dispute ratio by category
- Settlement batches — treasury operations
- Merchants — tier and segment analysis
Dashboards to build
Payment volume and success rate
Answers: Is payment volume growing and are authorizations healthy? Include volume, approval rate, and average transaction value KPIs; daily volume trend; and breakdown by payment method.Fraud and chargebacks
Answers: Where is risk concentrated? Include flagged rate and chargeback ratio KPIs; chargebacks by reason; and a table of flagged transactions.Merchant performance
Answers: Which merchants drive GMV and who needs support? Include active merchants and GMV KPIs; volume by merchant tier; and a top merchants table.Settlement operations
Answers: Are payouts on time? Include pending settlement and average lag KPIs; batch volume over time; and overdue batches table.Questions to ask by role
Example conversations
Approval rate
Ask: What is approval rate by payment method for the last 30 days? Compare methods by both rate and volume so low performers are not hidden behind small sample sizes.Metrics worth defining
Add to Connector memory as needed:- Approval rate — successful payments ÷ transaction attempts
- Chargeback ratio — chargeback amount ÷ settled volume
- GMV — gross merchandise value from settled payments
- Settlement lag — days between payment and batch settlement