Decision intelligence platform for credit risk, fraud, and customer decisioning
Provenir operates a decisioning platform for financial services, unifying credit risk, fraud, and customer management workflows on a single architecture. The tech stack is modern and modular (Angular, Spring Boot, Python, FastAPI on AWS/Kubernetes), but hiring signals reveal acute sales and data scaling: 9 of 24 open roles are sales positions, with concurrent projects spanning AI research, ML/GenAI pipelines, and positioning AI capabilities in deals—indicating a shift from pure platform optimization toward AI-driven go-to-market expansion.
Provenir builds a decision intelligence platform for financial services enterprises covering consumer lending, auto financing, SME lending, and commercial credit. The platform consolidates data, models, and decision agents to optimize customer acquisition, risk assessment, and fraud prevention across a single interface. Provenir operates globally across 60+ countries and processes over 4 billion transactions annually. The company is privately held, based in Parsippany, New Jersey, and employs 201–500 people. Core customers are large financial institutions and fintechs managing mission-critical lending and risk workflows.
Frontend: Angular, TypeScript, Material-UI, Tailwind CSS. Backend: Spring Boot, Python, FastAPI. Infrastructure: AWS, Docker, Kubernetes. Observability: Datadog, New Relic, Splunk, Prometheus. Sales/marketing tools: Salesforce, Pardot, ZoomInfo, Apollo.
Headquartered in Parsippany, New Jersey. Currently hiring across United States, India, United Kingdom, and Australia with emphasis on senior and leadership-level roles (15 of 24 open positions are senior or above).
Provenir'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.