QuantaVerse, the first in the market with artificial intelligence (AI) solutions purpose-built for identifying financial crimes, finished 2017 strong as adoption of AI and machine learning to identify suspicious financial activity continues to accelerate.
The QuantaVerse AI Financial Crime Platform helps financial institutions and corporations effectively address multiple types of financial crime. Not only does it assist in addressing AML (Anti‐Money Laundering) and FCPA (Foreign Corrupt Practices Act) regulatory and compliance requirements, it effectively identifies suspicious activities that may indicate money laundering, terrorism financing, fraud, bribery or corruption. Increased certainty in the ability to accurately evaluate entity and transactional risk frees organizations to confidently operate in markets and industries that have historically been considered uncertain.
“The success of QuantaVerse can be largely attributed to our focus on developing an AI and machine learning platform dedicated to finding financial crimes. Being ahead-of-the-curve in product development has created advantage for us in the AML space and has sped our expansion into addressing other financial crime challenges,” explained David McLaughlin, CEO and Founder of QuantaVerse.
Key milestones contributing to the company’s success in 2017 include:
The increased adoption of its solutions in 2017 led the company to add new funding which will be used in 2018 to increase market share and expand product development and customer support teams.
Each year, trillions of dollars are laundered through global banking system. That money supports numerous illicit activities including human trafficking, drug trade, terrorism, tax evasion, and the lavish lifestyles of criminal networks. Other financial crimes, such as bribery and corruption, have an adverse effect on both corporations and countries. The expensive penalties stemming from FCPA enforcement actions continue to increase year over year.
Traditional financial crime detection tools and methodologies used to find financial crimes, such as Transaction Monitoring Systems (TMS), have proved ineffective. The industry estimates that approximately 95 percent of transactions flagged by TMS are actually legitimate in nature while 50 percent of money laundering trafficked through global banks is missed altogether. QuantaVerse’s approach marries its AI-powered platform with customer-provided data and myriad other datasets to more efficiently and effectively identify financial crimes. Through this approach, QuantaVerse helps organizations reduce regulatory and reputational risk by identifying anomalous data patterns related to both known and not yet identified financial crime typologies.