> ## Documentation Index
> Fetch the complete documentation index at: https://docs.vizkraft.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Fintech / payments

> Connect payment and merchant data, build four dashboards, and monitor volume, fraud, and settlements — modeled on PayStream.

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This cookbook is for **payment and fintech** teams tracking merchants, transactions, fraud, chargebacks, and settlements. The examples use **PayStream**, a fictional payment gateway.

## Who this is for

|                  |                                              |
| ---------------- | -------------------------------------------- |
| **Company type** | Payment gateway, fintech, merchant services  |
| **Connector**    | PostgreSQL                                   |
| **Teams**        | Risk, treasury, merchant success, compliance |

## Get started

<Steps>
  <Step title="Add PostgreSQL">
    Connect your payments ledger or warehouse. See [Add connectors](/guides/add-connectors).
  </Step>

  <Step title="Index and mark key tables">
    Flag transactions, payments, fraud scores, chargebacks, and settlements.
  </Step>

  <Step title="Ask your first question">
    Try: *What is payment approval rate by payment method for the last 30 days?*
  </Step>

  <Step title="Build the dashboards below">
    Give risk and treasury teams a shared view of volume and operational health.
  </Step>
</Steps>

## See it in Vizkraft

<CookbookDemoVideo slug="fintech-payments" caption="PayStream payment analytics in Vizkraft" />

## Your data

| Table                | What it holds                                 |
| -------------------- | --------------------------------------------- |
| `merchants`          | Merchant profile, category, tier, region      |
| `accounts`           | Ledger balances by merchant                   |
| `transactions`       | All payment attempts — amount, method, status |
| `payments`           | Settled payments and fees                     |
| `chargebacks`        | Disputes — reason, amount, status             |
| `fraud_scores`       | Risk score and flagged transactions           |
| `settlement_batches` | Payout batches and status                     |

### 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

| Role             | Questions to try                                                          |
| ---------------- | ------------------------------------------------------------------------- |
| Risk analyst     | What is the flagged transaction rate by payment method and merchant tier? |
| Treasury         | What is settlement lag and total pending batch amount?                    |
| Merchant success | What is approval rate by payment method?                                  |
| Compliance       | What is chargeback ratio by merchant category?                            |

## 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](/features/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