Strong Corporate Governance Standards

The Company was founded with the philosophy of being institution owned, board controlled, and management run. The U GRO Capital`s 2019s Board is majorly independent and comprises financial industry luminaries with expertise from across the array of financial services viz lending, regulations, rating agency, etc. The Governance standards are further strengthened by strong policies and processes enshrined in the Articles of Association. U GRO Capital has also opted to be a listed entity from day one, which demands a higher degree of regulatory oversight and transparency.

Experienced Leadership Team

The company has able senior management that works to build the systems and processes with a larger time frame in mind. To that effect, the company hired industry leaders that have a proven track record of delivering results & possess the right acumen necessary in the build-out phase of any organization. Setting the right team in place has helped the company tide through the crisis effectively.

Large Institutional Capital

The company is institutionally owned and professionally governed. The Company has specifically decided to raise a huge institutional equity capital right from the start. U GRO Capital closed one of the largest fund-raises for a start-up in India, raising around Rs 920 Crores from a diverse group of investors as it embarked on the stated mission of U Gro. Raising this capital has helped the Company to have adequate capital based to grow in the first few years. Having a large institutional capital is also perceived positively by lenders & the company has been able to solidify its position in terms of the liability book. As of December 31, 2021, 89.11% of the paid-up share capital of the Company is held by institutions / private equity funds like ADV Partners, New Quest, Samena Capital, PAG, IndGrowth, PNB Metlife, Chhattisgarh Investments.

Technology

The Company has built proprietary GRO Score 2.0 which combines credit bureau data & banking data and provides superior performance through use of ML Models. A holistic credit score for MSMEs built by combining repayment history and cashflow transaction data; provides improved performance by fitment on own data, extensive feature creation and use of machine learning models. It combines entity, individual and banking data into one model. It reduces dependency on any specific bureau data and provides 10-20% higher approval rates for similar or lesser riskcases.