# Step 1 - Create a Document AI Schema Config

Set up the Data 360 Document AI processor configuration for a bank statement data extraction. This configuration uses an LLM model to analyze an uploaded bank statement, define the structured fields for extraction, and ensure the output is delivered as a clean, structured JSON schema.
Learn more about [Document AI](https://help.salesforce.com/s/articleView?id=data.c360\_a_document_ai.htm\&type=5).

## 1. Create a New Configuration

1. On the **App Launcher**, find and select the **Data 360** app (it may appear as **Data Cloud**).
2. Go to the **Unstructured Data** tab (in some orgs, this may be labeled **Process Content**).
3. On the left-hand navigation menu, click **Document AI**.
4. Click **New** to create a new configuration.
5. Choose how you want to create your document schema configuration by selecting **Without a source object**.

## 2. Configure Data Extraction

1. Prepare your bank documents for upload. In the document schema builder, click **Upload Files** and select your bank statement.
2. On the top left, select any LLM model. Gemini 2.0 Flash is recommended for PDF analysis.
3. Configure extraction fields:

   - On the right, under **Outputs**, click **Create Manually** and then click **Next**. Alternatively, you can use [auto-extraction](https://help.salesforce.com/s/articleView?id=data.c360\_a_document_ai_new_config.htm\&type=5) and change the fields to reflect what is shown below.
   - Click **Add Field** and add the following fields one-by-one.

| Name            | API Name          | Field Type | Prompt Instruction                                                            |
| :-------------- | :---------------- | :--------- | :---------------------------------------------------------------------------- |
| Monthly salary  | `Monthly_salary`  | string     | Based on the transactions, identify the average salary of the account holder. |
| home loan taken | `home_loan_taken` | boolean    | 1 if there are EMI transactions for home loan.                                |
| auto loan taken | `auto_loan_taken` | boolean    | 1 if there are EMI transactions for auto loan.                                |

![Extraction Fields](https://a.sfdcstatic.com/developer-website/sfdocs/data-ae/media/loan-agent-step-1-2.png)

## 3. Test and Save

Verify the results of the bank statement data extraction.

1. Click **Test**.
2. Document AI processes the uploaded file and extracts the defined fields. Review the output to verify that all fields are extracted correctly.
3. Save the configuration:

   - Click **Save**.
   - Enter a **Document Schema Name** and **API Name**: `bank_stmt_analyzer`. Copy and save the API name for next steps.
   - Click **Save**.

You successfully created your Document AI processor configuration for bank statement data extraction. For an example JSON schema, see the [complete document schema configuration](/docs/ai/loan-agent/guide/aes-document-ai-schema-configuration.md).

## Next Step

[Step 2 - Create Flow to Retrieve File ID from Email Address](/docs/ai/loan-agent/guide/aes-create-flow-to-retrieve-file-id.md): Create a screen flow to identify the bank statement file from the customer's email address.