A fintech startup, Orca Fraud has received $2.35 million in seed funding in order to scale its operations across Africa and other emerging markets. This is a firm that specializes in real-time fraud intelligence.
The founding round was led by Norrsken22, with participation from OneDayYes, Enza Capital, and CV VC Africa. As a startup that focuses on particular issues emerging markets face, where digital payment adoption is accelerating rapidly but traditional fraud-prevention tools often struggle with fragmented data and informal financial ecosystems.
Orca’s technology detects unusual transactions across payment channels, such as digital currencies, bank transfers, mobile wallets, and cards, using machine-learning models built on actual transaction patterns from these markets.
The company claims that its platform, which works with banking institutions and payment providers throughout Africa and beyond, currently processes over $5 billion in monthly revenue from transactions across more than 70 countries. As digital banking services continue to expand throughout emerging economies, there is a growing need for effective fraud protection, which contributed to this rapid growth.
Orca Fraud’s engineering and product development teams will be developed, its fraud-detection infrastructure will be enhanced, and its partnerships with banks, fintechs, and telecom companies will receive additional support with the help of the recently raised funds. Beyond Africa, the business intends to enter extra developing nations where digital payment platforms are rapidly expanding.
About Orca
In 2024, Thalia Pillay, CEO, and Carla Wilby, CTO, established Orca Fraud in Cape Town, South Africa. The company specializes on assisting financial institutions in detecting and avoiding fraud in rapidly developing digital payment networks, particularly within emerging markets like Africa.
Real-time transaction and consumer activity monitoring is made possible by the startup’s platform’s direct integration with live payment systems. Orca can identify suspicious activity and prevent fraud before money leaves the system through analyzing transactional patterns, device signals, and data related to behavior.
