Release Notes

In this release, we’ve expanded support for additional Classify and Capture documents, introduced enhancements to the Docs-to-Digital feature (including severity scoring for mismatches, reason codes, related transaction linking, and a new Docs-to-Digital Excel sheet), added the new book.income.updated webhook event, announced the deprecation of the Middesk integration, and introduced further enhancements to the SMB Dashboard Analytics.

What's new?

Analyze

Cash flow benchmarking [Beta]

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This feature is in beta!

This feature is in beta. You may occasionally experience unannounced changes or bugs. We'd greatly appreciate your feedback on this feature and its accompanying documentation.

We’re excited to announce the beta launch of Cash Flow Benchmarking (CFB), a powerful analytics capability that enables underwriters to evaluate a merchant’s financial performance in the context of their peers. With this new feature, underwriters can evaluate how key metrics such as revenue, expenses, and fintech inflows/outflows rank relative to anonymized SMB Books submitted to Ocrolus, segmented by industry and timeframe.

By adding percentile-based insights, CFB enhances underwriting accuracy, reduces guesswork, streamlines decision-making, and enables more confident credit evaluations with data-driven, context-aware insights.

Underwriters can now:

• Benchmark applicant performance relative to their industry peers.
• Validate borrower strength using percentile-based metrics.
• Prioritize attention on outliers and atypical businesses.
• Add objective context to subjective credit decisions.

For example, if Jill’s Coffee Shop reports $50K in revenue for March 2025, benchmarking shows how that figure stacks up against other coffee shops Ocrolus has analyzed for the same month, whether it’s in the top 25%, below average, or above typical industry levels.

Salient features

Benchmarking metrics for SMB Books

The newly added GET /v2/book/{book_uuid}/benchmark API returns percentile rankings for the following cash flow metrics:

• Revenue
• Expenses
• Fintech Inflows
• Fintech Outflows

Industry aware benchmarking (NAICS4)

Benchmarking results are grouped by the 4-digit NAICS industry code for each book, derived from Ocrolus’ internal classifier or an organizational override if present, and each metric is compared against books from similar businesses within the same industry and period.

To learn more, see the cash flow benchmarking API.

Webhook

New book.income.updated webhook event

A new event,`book.income.updated, has been added to both organization-level and account-level webhooks. This event is triggered whenever the income calculation for a specific Book is edited or updated. It ensures that systems and stakeholders are promptly informed of any changes to income data, supporting accurate downstream processing and reporting.

To learn more, see the Webhook page.

{
    "severity": "HIGH",
    "book_uuid": "a2801064-e875-4d1f-b43d-dbf5dfc907be",
    "event_name": "book.income.updated",
    "notification_type": "STATUS",
    "notification_reason": "Analyze Book Income Updated for the book"
}

Classify and Capture

New Classify and Capture supported documents

The Classify and Capture supports are enabled for the following newly onboarded documents:

Other

• Purchase Advice
• Purchase Advice and Wire Details (Final)

To learn more, see the All Supported Documents page.

Classify

New Classify-specific documents support

Classify support is now extended to the various documents. Click the category name below to expand/collapse the list of newly supported documents:

To learn more, see the All Supported Documents page.

Enhancements

Inspect

Inspect insights counter on dashboard

A new counter has been added to the Inspect tab on the Mortgage Dashboard to improve visibility and engagement with Inspect insights. This feature ensures that you are immediately aware of any outstanding insights requiring attention. The key improvements are:

• A yellow counter now appears on the left navigation menu next to the Inspect tab, displaying the number of unresolved Inspect insights.
• The counter reflects only unactioned discrepancies for the selected Book.
• When discrepancies are resolved (but not yet imported), the counter updates accordingly.
• The counter behaves similarly to the existing Insights counter and supports:
  • Both collapsed and expanded navigation views.
  • Live updates when the page is refreshed and insights have changed.

To learn more, see the Inspect insight counter.

SMB dashboard and analytics

We’re excited to announce the latest set of enhancements to the Ocrolus SMB lending platform. This release delivers key advancements aimed at enriching lender context, improving underwriting efficiency, and increasing dashboard usability.

Industry classification via API and dashboard

Ocrolus now surfaces industry classifications for small businesses across both API and dashboard experiences, providing lenders with valuable business context for each borrower. Wherever possible, Ocrolus will return the 4-digit 2022 North American Industry Classification System (NAICS) code and corresponding description for each small business application.

API enhancements

The Book summary endpoint now includes:

• naics_code: A 4-digit integer representing the merchant's industry classification, based on the latest NAICS standard.
• naics_description: A textual description corresponding to the NAICS-4 code category.

{
  "book_pk": 12345678,
  "book_name": "Ocrolus popsicle stand",
  "txn_count": 310,
  "naics_code": 7225,
  "naics_description": "Restaurants and Other Eating Places",
  "daily_balances": {
    "2025-07-16": 83559.21
  },
  ...

Dashboard enhancements

• The industry classification appears in the Ocrolus SMB dashboard in the following places:
  • The Account Summary tab
  • The new Book Overview page
• Override capabilities: Admin users can now override the Ocrolus-assigned industry classification for a small business by selecting a validated code from the NAICS reference list. This allows you to refine and enhance the industry product offering. Overrides apply only within the lender’s organization. Additionally, you can revert to the original system-assigned classification at any time using the Reset to Default option if you no longer wish to keep the manual override.

To learn more, see the Book Overview and Account Summary.

New Book Overview page in SMB dashboard

A newly designed Book Overview page provides SMB underwriters with an at-a-glance summary of key borrower data, streamlining the underwriting process and minimizing the need to switch between tabs. This page is now the default landing view when accessing any SMB book in the dashboard.

Key components

• Summary metrics bar: It includes the following details
  • Total Loan Proceeds
  • Total Loan Payments
  • Average Daily Balance
  • Debt Coverage Ratio
  • NSF and Overdraft Counts
• Insight cards row: These visually distinct cards can be used for:
  • Fintech loan and merchant cash advance sources
  • Revenue summary (top 5 counterparties with % contribution)
  • Expense summary (top 5 counterparties with % contribution)
• Right-side panel widgets: These widgest provide:
  • Industry Classification
  • Bank Accounts Summary, along with an accordion layout showing account holders, date ranges, and addresses

To learn more, see the Book Overview.

Financial analysis and counterparty insights - Account summary tab

We have introduced rich financial and counterparty components to the Account Summary tab within the SMB dashboard. These enhancements help you gain deeper insights into monthly trends and exposure analysis directly within the dashboard. They equip underwriters with comprehensive information at both macro and granular levels, enhancing visibility and reducing reliance on exported files. The new components include:

Month-over-Month Revenue, Deposits, Withdrawals, and Expenses table

Monthly breakdown for the following:

• Revenue and Revenue Count
• Expense and Expense Count
• Deposits and Deposit Count
• Withdrawals and Withdrawal Count

Top Counterparty widgets

• Revenue and Expense Counterparties (top 5 each)
• Displays name, amount (USD), and proportional share (as decimals)
• Cash Flow at a glance, including Industry details, Cash Flow summary, top 5 revenue counterparties, and the top 5 expense counterparties.

  📘

  Note

  The previously known Cash Flow at a Glance section has been moved from the horizontal layout to the right-side vertical bar.

To learn more, see Account Summary.

Docs-to-digital matching - severity scoring

We’re excited to announce an enhancement to the Docs-to-Digital reconciliation workflow: severity scoring for mismatched transactions! This powerful new capability brings clarity and prioritization to the process of comparing Plaid transaction data with uploaded bank statements.

Underwriters often face the challenge of manually reviewing long lists of mismatches, many of which are low-risk. With this update, each mismatch is automatically assigned a severity level (High, Medium, or Low) and helps teams focus their attention on the most critical discrepancies, like NSFs, debt-related transactions, or potential fraud indicators.

To further support underwriting workflows, we’ve introduced a dedicated Docs-to-Digital Excel sheet in the SMB Excel export. This new sheet offers an at-a-glance summary of mismatch severity, key metrics comparing Plaid and bank statement data, and a detailed breakdown of each mismatched transaction, including reason codes, tags, and related transaction references. The result is a more efficient and consistent reconciliation process, enabling faster funding decisions with less manual effort.

Severity scoring for mismatched transactions

Docs-to-Digital now includes an intelligent scoring system that assigns a severity level to each mismatched transaction between Plaid data and uploaded bank statements. Mismatched transactions are automatically categorized as High, Medium, or Low severity based on business rules developed in collaboration with lending partners. High-severity mismatches occur when transactions involving NSFs, MCAs, overdrafts, refunds, crypto, or gambling appear in either the digital data source or the bank statement, but not both. Identifying these high-risk transaction mismatches helps underwriters focus on red flags that could impact funding decisions.

Example node in the enriched transaction endpoint :

"mismatched_transactions": [
  {
    "txn_pk": 123,
    "txn_date": "2024-01-01",
    "description": "TRANSFER TO CHECKING",
    "amount": -2000.01,
    "uploaded_doc_pk": 123456,
    "uploaded_doc_format": "PLAID",
    "severity": "High",
    "reason_code": "critical_category_mismatch",
    "related_txn_pk": 456,
    "tags": "fintech, fintech_loan",
    "counterparty": "Credibly"
  },
]

Book-level severity scoring

Every Book is now scored based on the most severe mismatch it contains. This new field, book_mismatch_severity in the Book summary API allows underwriters to triage Books at a glance. A Book with even one high-severity mismatch is flagged as High, making prioritization during high-volume periods more efficient and consistent. The book_mismatch_severity is exposed at 3 places: Book summary endpoint, Webhook response, and SMB exported excel sheet.

• Example of Book Summary endpoint where Book Mismatch Severity is found:

  JSON

  {
  "book_pk": 59582262,
  "book_name": "Ascendia Pharmaceutical Solutions",
  "txn_count": 407,
  "book_mismatch_severity": "high",
  “naics_code”: {integer},
  “naics_description”: {string},
  "daily_balances": {
  "2024-11-30": 1855880.01,
  

• Example of webhook response where Book mismatch severity is found (book.pacing.discrepancies_found and book.pacing.no_discrepancies_found events):

  JSON

  {
    "book_uuid": "1e03d9cd-7d84-4672-bc3d-c19cd19c",
    "book_mismatch_severity": "High",
    "uploaded_docs": [
      {
        "uuid": "db7fe37f-3fc8-4a0a-9066-94101a1",
        "name": "uploaded_doc.json",
        "created_ts": "2025-03-01 00:00:00",
        "overlapping_date_range": {
          "begin_date": "2025-01-15",
          "end_date": "2025-01-31"
        }
      }
    ],
    "event_name": "book.pacing.discrepancies_found",
    "notification_reason": "Discrepancies Found",
    "notification_type": "STATUS",
    "severity": "HIGH"
  }
  

• Example of the SMB exported Excel sheet where Book mismatch severity is found:

  

Reason codes for mismatches

To help underwriters understand why each mismatch was flagged, a new field, reason_code is now included for every mismatched transaction. These codes provide immediate clarity without requiring manual comparison of raw Plaid and PDF data. Example reason codes include:

• Posting Date Difference
• Non-Critical Transaction
• Critical Category Mismatch

To learn more, see the enriched transaction endpoint.

Related transaction linking

For mismatches caused by minor date discrepancies (posting date difference), Docs-to-Digital includes a related_txn_pk field that points to the likely match in the opposite data source. This gives underwriters the context they need to assess whether the mismatch is a simple posting lag or something more significant. To learn more, see the enriched transaction endpoint.

New Docs-to-Digital Excel sheet

To support customers who prefer working directly in spreadsheets, we’ve introduced a new Excel sheet within the SMB Excel export specifically for Docs-to-Digital insights. This Excel output makes it easy for even non-technical users to efficiently review reconciliation results without needing to interact with the API. This sheet includes:

• Book-Level Summary: Displays total mismatches and overall book mismatch severity.
• Comparative Metrics: Shows side-by-side comparisons of revenue, debt, NSFs, and MCAs between Plaid and bank statements.
• Critical Category Totals: Provides mismatch counts and dollar amounts broken down by risk type.
• Severity Summary Table: Summarizes the total net mismatched amount for each severity tier.
• Detailed Mismatches Table: Lists transaction details, severity levels, reason codes, tags, and source format.

To learn more, see the mismatched transactions via SMB Excel Export.

Detect - Business Verification

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Feature deprecation - Middesk Integration

The following Business Verification APIs are now deprecated:

• Create Business Verification (POST)
• Retrieve Business Verification (GET)
• Vendor Authentication (PUT)

These endpoints are no longer supported and should not be used in new integrations.

Mortgage

Delete document using the Ocrolus dashboard

You can now delete an individual document directly from the dashboard. This enhancement provides greater control over loan files during the origination process, helping to maintain cleaner and more accurate documentation. This feature will help you remove incorrect or irrelevant files, keep the loan file focused before underwriting, and streamline workflows while preserving a complete audit trail and data integrity.

When a document is deleted, Ocrolus automatically recalculates all analytics tied to the loan file to reflect the updated data set.

📘

Note

• Bank statements are not supported for deletion.
• Deleted documents are only hidden from the front-end dashboard view. They remain intact in the backend for compliance and traceability and can still be retrieved via the API.

To learn more, see the Deleting document section.