diff --git a/docs/examples/payment_data_extraction.md b/docs/examples/payment_data_extraction.md
new file mode 100644
index 000000000..4b7233401
--- /dev/null
+++ b/docs/examples/payment_data_extraction.md
@@ -0,0 +1,225 @@
+---
+title: Payment Data Extraction - Transaction Parsing with Instructor
+description: Extract structured payment data from unstructured text using Instructor and Pydantic. Parse transaction details, multi-currency amounts, and payment methods.
+---
+
+# Extracting Payment Data from Unstructured Text
+
+This guide demonstrates how to extract structured payment information from unstructured text such as emails, invoices, and bank statements. Using Instructor with Pydantic validation, we ensure the extracted data is accurate and consistent.
+
+## Defining Payment Models
+
+We start by defining Pydantic models that represent payment data. The `PaymentMethod` enum captures common payment types, while `Transaction` includes validation for currency codes and amounts.
+
+```python
+from enum import Enum
+from pydantic import BaseModel, Field, field_validator
+
+
+class PaymentMethod(str, Enum):
+    CREDIT_CARD = "credit_card"
+    DEBIT_CARD = "debit_card"
+    BANK_TRANSFER = "bank_transfer"
+    DIGITAL_WALLET = "digital_wallet"
+    CASH = "cash"
+    OTHER = "other"
+
+
+class Transaction(BaseModel):
+    merchant_name: str = Field(description="Name of the merchant or payee")
+    amount: float = Field(description="Transaction amount", gt=0)
+    currency: str = Field(description="ISO 4217 currency code (e.g., USD, EUR, BRL)")
+    payment_method: PaymentMethod = Field(description="Payment method used")
+    reference_id: str | None = Field(
+        default=None, description="Transaction reference or confirmation number"
+    )
+    date: str | None = Field(
+        default=None, description="Transaction date in YYYY-MM-DD format"
+    )
+
+    @field_validator("currency")
+    @classmethod
+    def validate_currency_code(cls, v: str) -> str:
+        v = v.upper().strip()
+        if len(v) != 3 or not v.isalpha():
+            raise ValueError(f"Invalid ISO 4217 currency code: {v}")
+        return v
+```
+
+## Extracting Multiple Transactions
+
+Payment documents often contain multiple transactions. The `PaymentReport` model aggregates them and validates that the total matches the sum of individual amounts (when all transactions share the same currency).
+
+```python
+from pydantic import model_validator
+
+
+class PaymentReport(BaseModel):
+    transactions: list[Transaction] = Field(
+        description="List of payment transactions found in the text"
+    )
+    total_amount: float | None = Field(
+        default=None, description="Total amount if stated in the document"
+    )
+
+    @model_validator(mode="after")
+    def validate_total(self):
+        if self.total_amount is None:
+            return self
+
+        currencies = {t.currency for t in self.transactions}
+        if len(currencies) == 1:
+            calculated = sum(t.amount for t in self.transactions)
+            if abs(calculated - self.total_amount) > 0.01:
+                raise ValueError(
+                    f"Total {self.total_amount} does not match "
+                    f"sum of transactions {calculated}"
+                )
+        return self
+```
+
+## Processing Payment Text
+
+The `extract_payments` function uses Instructor to parse unstructured payment text into our structured models. Instructor handles retries automatically when validation fails, asking the LLM to correct its output.
+
+```python
+import instructor
+
+# <%hide%>
+from enum import Enum
+from pydantic import BaseModel, Field, field_validator, model_validator
+
+
+class PaymentMethod(str, Enum):
+    CREDIT_CARD = "credit_card"
+    DEBIT_CARD = "debit_card"
+    BANK_TRANSFER = "bank_transfer"
+    DIGITAL_WALLET = "digital_wallet"
+    CASH = "cash"
+    OTHER = "other"
+
+
+class Transaction(BaseModel):
+    merchant_name: str = Field(description="Name of the merchant or payee")
+    amount: float = Field(description="Transaction amount", gt=0)
+    currency: str = Field(description="ISO 4217 currency code (e.g., USD, EUR, BRL)")
+    payment_method: PaymentMethod = Field(description="Payment method used")
+    reference_id: str | None = Field(
+        default=None, description="Transaction reference or confirmation number"
+    )
+    date: str | None = Field(
+        default=None, description="Transaction date in YYYY-MM-DD format"
+    )
+
+    @field_validator("currency")
+    @classmethod
+    def validate_currency_code(cls, v: str) -> str:
+        v = v.upper().strip()
+        if len(v) != 3 or not v.isalpha():
+            raise ValueError(f"Invalid ISO 4217 currency code: {v}")
+        return v
+
+
+class PaymentReport(BaseModel):
+    transactions: list[Transaction] = Field(
+        description="List of payment transactions found in the text"
+    )
+    total_amount: float | None = Field(
+        default=None, description="Total amount if stated in the document"
+    )
+
+    @model_validator(mode="after")
+    def validate_total(self):
+        if self.total_amount is None:
+            return self
+        currencies = {t.currency for t in self.transactions}
+        if len(currencies) == 1:
+            calculated = sum(t.amount for t in self.transactions)
+            if abs(calculated - self.total_amount) > 0.01:
+                raise ValueError(
+                    f"Total {self.total_amount} does not match "
+                    f"sum of transactions {calculated}"
+                )
+        return self
+
+
+# <%hide%>
+from openai import OpenAI
+
+client = instructor.from_openai(OpenAI())
+
+
+def extract_payments(text: str) -> PaymentReport:
+    return client.chat.completions.create(
+        model="gpt-4o-mini",
+        response_model=PaymentReport,
+        messages=[
+            {
+                "role": "system",
+                "content": (
+                    "Extract all payment transactions from the provided text. "
+                    "For each transaction, identify the merchant, amount, currency, "
+                    "payment method, reference ID if available, and date if available."
+                ),
+            },
+            {"role": "user", "content": text},
+        ],
+        max_retries=3,
+    )
+```
+
+## Example Usage
+
+Here's how to extract payment data from a bank statement email:
+
+```python
+statement = """
+Your monthly statement for January 2026:
+
+01/05 - Amazon.com, Visa ending 4532, $127.99 (Ref: AMZ-20260105-7821)
+01/08 - Uber Technologies, Mastercard ending 8901, $23.50 (Ref: UBER-8834)
+01/12 - Wire transfer to Acme Corp, $2,500.00 (Ref: WIRE-2026-0112)
+01/15 - PayPal payment to Freelancer.com, $450.00 (Ref: PP-FL-9921)
+01/20 - Starbucks, Apple Pay, $6.75
+
+Total charges: $3,108.24
+"""
+
+report = extract_payments(statement)
+
+for txn in report.transactions:
+    print(f"{txn.date} | {txn.merchant_name:20s} | {txn.currency} {txn.amount:>10.2f} | {txn.payment_method.value}")
+```
+
+Expected output:
+
+```
+2026-01-05 | Amazon.com           | USD     127.99 | credit_card
+2026-01-08 | Uber Technologies    | USD      23.50 | credit_card
+2026-01-12 | Acme Corp            | USD    2500.00 | bank_transfer
+2026-01-15 | Freelancer.com       | USD     450.00 | digital_wallet
+2026-01-20 | Starbucks            | USD       6.75 | digital_wallet
+```
+
+## Multi-Currency Support
+
+The currency validator ensures ISO 4217 compliance, and the total validator correctly handles multi-currency reports by skipping the total check when multiple currencies are present:
+
+```python
+multi_currency_text = """
+International expense report:
+- Hotel in Tokyo: JPY 45,000 (credit card)
+- Flight to London: EUR 320.00 (credit card)
+- Taxi in New York: USD 42.50 (debit card)
+"""
+
+report = extract_payments(multi_currency_text)
+# total_amount will be None since currencies differ
+```
+
+## Key Takeaways
+
+1. **Pydantic validators catch errors early** — Currency codes and amounts are validated before the data reaches your application.
+2. **Instructor retries on validation failure** — If the LLM returns an invalid currency code, Instructor asks it to fix the output automatically.
+3. **Domain enums improve accuracy** — Using `PaymentMethod` as an enum constrains the LLM to valid payment types instead of free-form text.
+4. **Cross-field validation** — The `validate_total` model validator ensures consistency between individual transactions and the reported total.
diff --git a/mkdocs.yml b/mkdocs.yml
index 53aa09487..c724c2fb7 100644
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -210,6 +210,7 @@ nav:
     - "User-Defined Bulk Classification": 'examples/bulk_classification.md'
     - "AI Model Self-Correction": 'examples/self_critique.md'
     - "Receipt Data Extraction with GPT-4": 'examples/extracting_receipts.md'
+    - "Payment Data Extraction": 'examples/payment_data_extraction.md'
     - "Slide Data Extraction with GPT-4": 'examples/extract_slides.md'
     - "Content Moderation with OpenAI": 'examples/moderation.md'
     - "Complex Entity Resolution": 'examples/entity_resolution.md'