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

# Loan application processing

> Accelerate loan intake by combining applicant data review with document analysis and automated routing

Loan origination is one of the most document-heavy workflows in banking. Each application requires pulling credit data, verifying income documents, cross-checking against underwriting policies, and routing the file to the right decision-maker. Manual handling introduces delays, inconsistent evaluations, and bottlenecks during peak volume periods.

With Wayak, you build an agent that reviews incoming applications against your underwriting criteria, extracts key data points from uploaded documents, and routes each file based on risk tier and product type. A playbook monitors new submissions and triggers the intake workflow automatically, so your team focuses on decisions rather than data gathering.

***

## What you need

<CardGroup cols={2}>
  <Card title="Data sources" icon="database">
    * **Loan origination system** — application records, applicant demographics, requested amounts, and decision history
    * **Credit bureau API** — credit scores, trade lines, delinquency history, and inquiries
    * **Core banking system** — existing account balances, deposit history, and relationship tenure
  </Card>

  <Card title="Knowledge spaces" icon="book-open">
    * **Underwriting policy manual** — upload your current credit policy, including approval thresholds by product type and risk tier
    * **Regulatory guidelines** — fair lending requirements, disclosure rules, and documentation checklists
  </Card>
</CardGroup>

**Semantic layer:** Define these in your ontology before setting up the agent.

| Component | Name                    | Definition                                                                                            |
| --------- | ----------------------- | ----------------------------------------------------------------------------------------------------- |
| Object    | Loan Application        | Maps to the `applications` table in the loan origination system. Represents a single borrower request |
| Object    | Customer                | Maps to `customers` in the core banking system. Represents an individual or business entity           |
| Metric    | Approval Rate           | Count of approved applications / total applications, segmented by product and branch                  |
| Metric    | Average Processing Time | Mean elapsed days from submission to decision across all applications                                 |
| Dimension | Product Type            | Categorizes applications by mortgage, personal, auto, or commercial                                   |
| Dimension | Risk Tier               | Groups applications into low, medium, high, and very-high risk based on credit score bands            |

<Tip>
  See [building a semantic layer](/quickstart/build-semantic-layer) for a step-by-step guide.
</Tip>

***

## Agent setup

<Steps>
  <Step title="Create the agent">
    Go to **Agent Space** → **New agent**.

    | Field    | Value                                                                                                                            |
    | -------- | -------------------------------------------------------------------------------------------------------------------------------- |
    | **Name** | Loan Intake Analyst                                                                                                              |
    | **Role** | Loan Application Reviewer                                                                                                        |
    | **Goal** | Review incoming loan applications, verify completeness, assess preliminary risk, and route to the appropriate underwriting queue |
  </Step>

  <Step title="Set the description">
    > You are a detail-oriented loan intake analyst. You evaluate each application against underwriting policies, flag missing documents or data discrepancies, and classify risk tier using credit bureau data and internal account history. You prioritize accuracy and regulatory compliance over speed, and you never approve or deny an application — you prepare it for human decision-making.
  </Step>

  <Step title="Scope data access">
    Grant access to:

    * Loan origination system (applications table, decision history)
    * Credit bureau API (scores, trade lines)
    * Core banking system (customer accounts, deposit history)
    * Underwriting policy manual knowledge space
    * Regulatory guidelines knowledge space
    * Loan Application and Customer objects, Approval Rate metric
  </Step>

  <Step title="Add skills">
    <AccordionGroup>
      <Accordion title="Application completeness check">
        **Trigger:** User asks the agent to review a specific application or batch of applications.

        1. Retrieve the application record from the loan origination system.
        2. Compare submitted fields against the required-documents checklist from the underwriting policy manual.
        3. Flag any missing or inconsistent fields (income verification, employment letter, identification).
        4. Pull the applicant's credit score and trade line summary from the credit bureau API.
        5. Look up the applicant's existing account relationship in the core banking system.
        6. Generate a completeness summary with a pass/fail status and a list of items needing follow-up.
      </Accordion>

      <Accordion title="Risk tier classification">
        **Trigger:** User asks the agent to classify an application by risk level.

        1. Retrieve the applicant's credit score, debt-to-income ratio, and trade line count from bureau data.
        2. Pull deposit history and average balance from the core banking system.
        3. Match the product type to the corresponding risk-tier thresholds in the underwriting policy manual.
        4. Assign a risk tier (low, medium, high, or very-high) based on the combined criteria.
        5. Return a structured summary with the assigned tier, contributing factors, and the applicable policy section reference.
      </Accordion>

      <Accordion title="Routing recommendation">
        **Trigger:** User asks the agent where to route an application.

        1. Check the application's completeness status and risk tier from previous assessments.
        2. Look up the routing rules in the underwriting policy manual for the given product type and risk tier.
        3. Identify the correct underwriting queue (auto-approve, standard review, senior review, or decline queue).
        4. Flag any regulatory holds (e.g., fair lending review triggers).
        5. Return the recommended queue, expected SLA, and any special handling instructions.
      </Accordion>
    </AccordionGroup>
  </Step>
</Steps>

***

## Automation

### Playbook: New application intake router

<Steps>
  <Step title="Set the trigger">
    Set the trigger to **Event — New record** on the `applications` table in the loan origination system. The playbook fires each time a new application is submitted.
  </Step>

  <Step title="Build the workflow">
    The workflow performs a multi-step evaluation of each new application:

    1. **Query** the application record and join it with the applicant's credit bureau data and core banking profile.
    2. **Condition** — check whether all required documents are present. If documents are missing, branch to a notification step that emails the applicant with a list of outstanding items.
    3. **Condition** — evaluate risk tier. If the risk tier is "low" and all documents are present, route to the auto-approve queue. Otherwise, route to the appropriate review queue.
    4. **Action** — update the application status in the loan origination system with the assigned queue and tier.
    5. **Delivery** — send a Slack notification to the underwriting channel with the application ID, applicant name, product type, risk tier, and assigned queue.
  </Step>

  <Step title="Configure delivery">
    * **Slack** — send to the `#loan-underwriting` channel with application summary
    * **Email** — notify the assigned underwriter with a detailed intake report
    * **Email to applicant** — send a confirmation with application ID and expected timeline
  </Step>

  <Step title="Test and activate">
    Click **Run now** to test with a recent application, then toggle to **Active**.
  </Step>
</Steps>

***

## What's next

<CardGroup cols={2}>
  <Card title="Customer credit scoring" icon="arrow-right" href="/use-cases/finance/customer-credit-scoring">
    Build a composite credit scoring model that feeds directly into your loan application workflow.
  </Card>

  <Card title="All Finance & Banking use cases" icon="list" href="/use-cases/finance">
    See the full list.
  </Card>
</CardGroup>