Godrej capital builds a data-driven lending platform with Snowflake’s AI data cloud

odrej Capital, the financial services arm of Godrej Industries Group, has implemented Snowflake’s AI Data Cloud as its integrated data platform to support its financing solutions. The platform is used to improve customer loan processes, predict customer behaviour, and provide tailored services. By leveraging data, Godrej Capital aims to manage risks, develop financial models and scorecards, streamline regulatory reporting, and make data-driven decisions regarding its loan offerings.

The company selected Snowflake’s AI Data Cloud due to its security, scalability, and flexibility. The cloud-based platform and pay-as-you-go pricing model were factors in the decision, as they allow for efficient scaling of workloads with minimal downtime. The collaboration, which began four years ago, is part of Godrej Capital’s broader strategy to enhance its data management capabilities and adopt digital financial services.

The platform has been integrated into Godrej Capital’s analytics and sales processes. The analytics team generates financial reports that meet regulatory compliance requirements, while sales teams use data insights to track customer preferences and refine loan products. Data governance measures, including role-based access controls and multi-factor authentication, have been implemented to manage access and security.

According to Jyothirlatha B, Chief Technology Officer at Godrej Capital, the company has invested in AI and machine learning to develop innovative financial products. The adoption of a data platform was intended to enhance security, scalability, and governance. The system provides encryption and governance features while enabling data-driven decision-making and streamlining loan processes.

The integration of the data platform has also automated several manual tasks, such as incentive calculations for partners and sales teams. Previously, report generation took several days per month, whereas it can now be completed in near real-time with minimal manual input. Real-time performance analytics are also used to support decision-making related to sales forecasting, product development, and technology investments.

Additionally, the platform facilitates the automation of business reports, including those related to outstanding payments, collections, and loan disbursements. By consolidating and processing large datasets in real time, the company can optimise its loan offerings, identify potential customers, and make data-driven business decisions. Centralising historical data has further supported regulatory compliance and in-depth analysis of missed cases.

The financial services sector in India is experiencing rapid technological advancements, with increased adoption of data-driven approaches to improve customer experiences and risk management. The use of a secure, scalable, and integrated data platform is intended to support these developments and enhance operational efficiency