Heron
Heron
Heron
Heron automates document-heavy underwriting for small business and MCA lenders, turning broker emails, document packets, or Plaid data into a decision-ready view of the merchant — categorized cash flow, risk flags, and business validations.
Heron automates document-heavy underwriting for small business and MCA lenders, turning broker emails, document packets, or Plaid data into a decision-ready view of the merchant — categorized cash flow, risk flags, and business validations.
CATEGORIES
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SMB & Commercial Lending
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Cash Flow Analytics
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Document Management
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Overview
Heron automates document-heavy underwriting for small business lenders, primarily in the MCA space. It takes a submission — a broker email, document packet, or Plaid connection — and returns a decision-ready view of the merchant: categorized bank statements and cash flow, existing positions and holdback exposure, plus validations like court records, Secretary of State, EIN, and industry codes.
Use Cases
Pull categorized revenue, cash flow, and balance data (30/90/365-day revenue, COGS, opex, net/gross operating cashflow, DSCR) directly into a LendAPI decision model as underwriting variables.
Flag risk signals — negative balance days, NSF days and fees, unreconciled data, debt collection activity — as automated review triggers inside an underwriting flow.
Detect existing MCA positions and holdback exposure on an applicant's bank statements, so stacking risk is caught before an offer goes out.
Parse broker emails or document packets directly into structured, decision-ready data, cutting manual data entry out of intake for high-volume SMB/MCA lending.
Overview
Heron automates document-heavy underwriting for small business lenders, primarily in the MCA space. It takes a submission — a broker email, document packet, or Plaid connection — and returns a decision-ready view of the merchant: categorized bank statements and cash flow, existing positions and holdback exposure, plus validations like court records, Secretary of State, EIN, and industry codes.
Use Cases
Pull categorized revenue, cash flow, and balance data (30/90/365-day revenue, COGS, opex, net/gross operating cashflow, DSCR) directly into a LendAPI decision model as underwriting variables.
Flag risk signals — negative balance days, NSF days and fees, unreconciled data, debt collection activity — as automated review triggers inside an underwriting flow.
Detect existing MCA positions and holdback exposure on an applicant's bank statements, so stacking risk is caught before an offer goes out.
Parse broker emails or document packets directly into structured, decision-ready data, cutting manual data entry out of intake for high-volume SMB/MCA lending.
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