Through the agreement, ThetaRay will provide MFS Africa its SONAR SaaS solution, including AI-supported AML transaction monitoring and sanctions list screening, enabling it to stay a step ahead of complex and emerging financial crime typologies, and increase growth opportunities with a trusted and secure service.
MFS Africa has made significant acquisitions in 2021, acquiring Baxi, a super-agency network in Nigeria, and the US-based fintech GTP, a processor of prepaid cards across the African continent.
As MFS Africa continues to expand its business across Africa and focuses on enabling new use-cases, ThetaRay’s advanced platform assures the company an efficient and effective solution that can support its increasing payment volumes, while reducing exposure to risk from financial crimes.
MFS Africa's full-service digital payments network connects over 400 million mobile money wallets, over 200 million bank accounts and over 150,000 agents to enable cross-platform and cross-border payments for remittance companies, mobile network operators, banks, non-bank financial institutions, and global merchants.
Company officials stated that moving from a rules-based solution to a sophisticated AI platform is a game-changer for compliance, thanks to its new breed of intelligence that reduces false positives and enables them to detect unknown cases. The company takes its role in safeguarding the integrity of payments systems very seriously, and this partnership with ThetaRay exemplifies its approach to a strong governance and controlled environment.
SONAR is based on a form of AI called ‘artificial intelligence intuition’ that makes better decisions with no bias or thresholds, offering customers a risk-based approach to effectively identify truly suspicious cases and create a full picture of customer identities including across complex, cross-border transaction paths. This enables the rapid discovery of both known and unknown money laundering threats, with a peerless 95% detection rate and up to 99% reduction in false positives compared to rules-based solutions.
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