Merchant cash advance platform modernizing underwriting and risk decisioning
Greenbox Capital funds small businesses through merchant cash advances, invoice factoring, and short-term loans — a capital-intensive business where speed and risk precision are competitive moats. The tech stack reflects a company mid-migration: heavy Azure cloud adoption (Data Factory, SQL Database, Cosmos DB, Data Lake Storage), paired with Python + Spark analytics and Salesforce for underwriting workflows. Active hiring skews senior (4 of 6 roles) in data and engineering, concentrated on origination modernization and legacy replacement, suggesting they're rebuilding core decisioning and risk infrastructure to reduce manual processing and accelerate approval cycles.
Greenbox Capital is a direct lender serving small businesses across the US, Puerto Rico, and Canada with merchant cash advances, invoice factoring, and working capital loans. The company operates a proprietary platform called The Box, designed to improve deal quality, funding speed, and underwriting consistency for broker partners. The business model depends on rapid credit decisions and efficient portfolio management; current priorities include replacing legacy systems, automating operational workflows, optimizing pricing and risk-adjusted revenue, and re-engaging repeat merchants. The organization is based in Miami and operates as a privately held alternative lender.
Greenbox Capital uses Azure (Data Factory, SQL Database, Cosmos DB, Data Lake Storage), Databricks with Unity Catalog, Python, Spark, Salesforce with Apex, Power BI, Tableau, Looker, HubSpot, FastAPI, Flask, Vue, Streamlit, and OpenAI/GPT integration.
Current projects include origination ecosystem modernization, legacy system replacement, Salesforce underwriting workflow buildout, API integrations, workflow automation to reduce manual processing, and optimization of credit decisioning and pricing frameworks.
Greenbox Capital's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.