Peter Reynolds to drive revenues as the company scales globally
ThetaRay, a leading provider of AI-powered transaction monitoring technology to protect banks and fintechs against financial crimes, announced that it is strengthening global revenue operations with the appointment of Peter Reynolds as the company’s Chief Revenue Officer (CRO).
Reynolds will lead end-to-end sales and revenue growth operations as ThetaRay accelerates global expansion with banks, fintechs, regulators, and partners.
“I am excited to join as ThetaRay embarks on a high-growth phase to scale business globally,” said Reynolds. “I look forward to working with the team, customers and partners to deliver value to the entire global payments ecosystem.”
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Reynolds has more than 20 years of experience selling enterprise software into financial institutions, fintechs and global corporations. He specializes in building world-class and high-performing revenue organizations that achieve hyper-growth. Reynolds launched his career at HSBC before holding senior sales leadership positions at Earnix, Fundtech, Reval, and Thomson Financial. He holds a law degree from London Guildhall University.
“Peter has proven success as a fintech revenue leader, and we are thrilled to welcome him onboard during this key growth stage,” said ThetaRay CEO Mark Gazit. “By creating a secure financial network, our AI transaction technology enables fintechs and banks to increase growth and revenues, improve customer service, and deliver a new standard of trust.”
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About ThetaRay
ThetaRay’s groundbreaking, AI-powered SONAR SaaS transaction monitoring solution allows banks and payment fintechs to focus on their core business and increase revenue opportunities through secure, reliable cross-border payments. ThetaRay’s technology is the only SaaS offering end-to-end artificial intuition solutions, from data integration to alert resolution. It provides innovative data integration and quality capabilities, advanced analytics, portfolio management, increased monitoring of supervised and unsupervised data, and other machine learning technologies in a single unified platform.
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