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Gal Krubiner is a prominent Israeli entrepreneur and the Co-Founder and Chief Executive Officer of Pagaya Technologies. With a deep-rooted background in finance and investment management, including a significant tenure at UBS, Gal identified a critical opportunity to revolutionize the lending industry through technology. He co-founded Pagaya in 2016, pioneering the use of a sophisticated AI-driven network to help financial institutions make more informed credit decisions and expand access to credit for consumers. Under his leadership, Pagaya has grown from a startup into a publicly-traded fintech powerhouse on the NASDAQ, partnering with major banks, credit unions, and lenders to reshape the future of finance.
Gal Krubiner's work history includes a series of influential roles in various companies. Here is a detailed list of his professional journey:
Co-founded Pagaya in 2016 and has since served as its CEO, scaling the company into a leading global financial technology firm that leverages AI for asset management and lending.
Successfully guided Pagaya through its public market debut via a SPAC merger in June 2022, a milestone that valued the company in the billions and solidified its position in the public fintech landscape.
Recognized as a key innovator in the financial technology space. He was named in 'The Top 25 Financial Technology CEOs of 2021' by The Financial Technology Report for his leadership and impact.
Forged critical partnerships with some of the largest US banks, fintechs, and auto lenders, integrating Pagaya's AI infrastructure into their lending operations to expand credit access.
Tel Aviv University - Year 2009
Gimnasia Hertzlia
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Pagaya is a global financial technology company that leverages a proprietary artificial intelligence network to help its lending partners originate more loans. The platform analyzes extensive data to more accurately assess credit risk, enabling financial institutions like banks, fintechs, and auto lenders to approve a wider range of customers without incurring additional risk. This allows them to serve individuals who might be overlooked by traditional credit scoring models.
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