60

Out of 100

N/A

Post-money

$75M

All rounds

60/100

2018

100-500 employees

March 2026

Unit21 provides a fraud and risk operations platform that enables compliance and fraud teams at financial institutions and fintechs to build, test, and deploy transaction monitoring rules and machine learning models without requiring data science resources. The platform covers transaction fraud, account takeover, ACH and check fraud, and anti-money laundering (AML) case management in a unified wor

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T

Trisha Kothari

Founder & CEO

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StageSeries C
Employees100-500
Country🇺🇸 United States

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Series C · No public funding round data available yet.

Frequently Asked Questions

What is Unit21's valuation?
Unit21's valuation is not publicly disclosed.
Who invested in Unit21?
Investor information for Unit21 is not publicly available at this time.
When did Unit21 last raise funding?
No public funding round data is currently available for Unit21.
How many employees does Unit21 have?
Unit21 has approximately 100-500 employees.
What does Unit21 do?
Unit21 provides a fraud and risk operations platform that enables compliance and fraud teams at financial institutions and fintechs to build, test, and deploy transaction monitoring rules and machine learning models without requiring data science resources. The platform covers transaction fraud, account takeover, ACH and check fraud, and anti-money laundering (AML) case management in a unified workflow.\n\nThe company raised approximately 75 million USD and serves hundreds of financial services customers including neobanks, payment processors, crypto exchanges, and traditional banks looking to modernize legacy fraud operations with configurable, model-driven risk infrastructure. Unit21 no-code rule builder allows risk analysts to respond to new fraud patterns within hours rather than weeks.\n\nFinancial fraud losses in the United States exceed 10 billion USD annually and are growing as faster payment rails reduce the window for detection. Unit21 competes with legacy vendors like NICE Actimize and SAS as well as newer entrants including Sardine and Alloy, differentiating through its analyst-friendly interface and the speed with which risk teams can iterate on detection logic without engineering dependencies.