cSigma Finance, a financial technology company based in New York City, today announced the launch of its Real World Credit (RWC) protocol on Ethereum, connecting stablecoin holders with Institutional-grade credit opportunities.
cSigma Finance is at the forefront of transforming Real World Assets, fusing cutting-edge data analytics and Machine Learning with the foundational elements of blockchain technology. This integration marks a significant stride towards bridging the divide between Traditional Finance and the burgeoning realm of Decentralized Finance.
“cSigma’s protocol is a game-changer for the $150B stablecoin assets, with a dual mandate of democratizing SMB access to capital and improving the yields of stablecoin holders,” said Anil Jaladi, founder and CEO of cSigma Finance. “cSigma protocol not only tokenizes the debt but also offers a rigorous credit token life cycle process, monitoring borrowers’ credit quality systematically and generating probably the highest risk-adjusted yields on Ethereum”.
Lenders utilizing stablecoins gain enhanced exposure to top-tier, collateral-backed real-world credit options, bolstered by robust Machine Learning and analytical tools for more informed lending choices, alongside a comprehensive, real-time perspective of their capital allocation.
SMB debt originators and borrowers will have access to new sources of capital that are flexible and agile on a global scale to support their growth.
“We are excited to partner with cSigma Finance to provide our customers with access to capital from stablecoin investors. This partnership will allow us to offer our customers more flexible and affordable trade finance solutions, helping them to grow their businesses and succeed in the global marketplace.”, says John Fang, VP of Finance at BlueX Trade, a payments and financing logistics platform with over 25,000 importers and exporters.
About cSigma Finance
cSigma Finance is on a mission to democratize access to institutional-grade credit opportunities by leveraging blockchain and machine learning through a frictionless process.
