Finbots.AI, an AI-led, innovation-driven venture, announced it has raised USD 3 million in a Series A round from Accel. The investment by Accel comes from Fund VII, and this is the first external investment for Finbots.AI. The funds will accelerate product enhancement, marketing and sales, and customer support besides recruiting senior talent and expanding its team across its offices. Besides being a key market for the venture, India drives all of the global development and support for Finbots.AI.
Sanjay Uppal, Founder and CEO of Finbots.AI, said, “This new funding unlocks the next phase of growth for FinbotsAI. Financial institutions need pathbreaking solutions to solve the complex challenges of legacy platforms. Tapping on AI-enabled solutions can help them transform exponentially. We are thrilled to have Accel as a partner in this journey, further validating the potential and trust in our solution. Accel’s impressive track record with growth-stage companies will be a key support for FinbotsAI. We have enormous growth potential, and I am excited for our journey to transforming financial services.”
Mahendran Balachandran, Partner at Accel, said, “Finbots.AI team brings decades of collective experience in financial services and technology. We see great potential and promise in their solution – ZScore – as it strives to remedy and bridge the limitations of legacy credit systems. We at Accel are delighted to be a part of Finbot.AI’s growth as they propel forward to enhance financial services by leveraging AI technology to serve the entire community – ranging from the large banks to the small lenders. We see massive potential in the region and FinTech as a vertical.”
ZScore, Finbots.AI’s advanced AI-powered credit scorecard system, democratises access to cutting-edge capabilities for all financial institutions, enabling them to develop high accuracy scorecards and process applications in real-time rapidly. Equipped with an intuitive user interface and robust scorecard development capabilities, it rapidly develops higher accuracy credit scorecards using advanced ML algorithms that utilise historical/traditional and alternate data to automatically build, validate, and deploy real-time, high-performing risk models.
