Sandbar Raises $4.8M to Combat Financial Crime with Institutional-Grade Transaction Monitoring Software

Funding Rounds

Summary

NEW YORK--(BUSINESS WIRE)--Sandbar, a provider of anti-money laundering, fraud and counter-terrorism risk detection software, today announced the availability of its product and a $4.8 million seed investment led by Lachy Groom and Abstract Ventures. Traditional AML systems, such as those based on Excel or various vendor solutions, are prone to vulnerabilities and provide incomplete or inaccurate risk assessments, allowing threats to go undetected. We take an intuitive, flexible approach that provides context and actionable guidance to analysts, while also centralizing underlying data and risk factors to reveal the bigger picture and eliminate repeated flagging of already identified and dismissed false positives.” • Flexible, off-the-shelf and custom rules for 100+ typologies and 10+ products • Ongoing screening against watchlists like OFAC, and client-defined lists • Key metrics for monitoring overall performance, rules, and more • Access to raw data tables for further investigation “Transaction monitoring is tough, but it doesn’t have to be. “Sandbar’s accuracy, immediacy of alerts, automated suggestions and built-in education allow companies of all sizes to scale their AML efforts with less and avoid costly penalties – all within one, cohesive solution,” explained solo-GP and former Stripe executive Lachy Groom. Sandbar’s holistic models and proprietary integrations enable organizations to quickly and accurately identify suspicious financial behaviors, prioritize alerts, and automate tedious casework so they can scale their business safely.

$ Funding

Review available funding amount, funding date, investors, and linked company information related to Sandbar Raises $4.8M to Combat Financial Crime with Institutional-Grade Transaction Monitoring Software in the interactive ISVWorld profile.

Classifications

industries
Fintech & Banking
applications
Governance, risk and compliance

AskAI Classifications

Labels
No AI classifications detected

Linked Companies