About
The client is a non-banking finance company (NBFC) registered with the Reserve Bank of India (RBI). The client was looking for a way to digitize their lending operations and offer an easy-to-use, AI-powered digital credit app for their customers. Sakha, as a tech partner, empowered the client through development of the app.
The Challenge
The client was looking for a way to digitize their lending operations and offer an easy-to-use, AI-powered digital credit app for their customers. They also wanted to provide spending and savings analytics to help customers better manage their finances. However, they faced the challenge of developing a solution that could process large amounts of data in real-time while ensuring the security and privacy of their customers.
Solution
The NBFC partnered with Sakha to develop an AI-powered digital credit app that would allow customers to apply for loans, track their spending, and manage their savings all in one place. The app was built on a Big Data platform that could process large amounts of data in real-time, enabling the company to offer instant credit decisions to its customers. The solution leveraged machine learning algorithms to analyze customers’ spending and saving patterns and provide personalized recommendations to help them manage their finances better. The app’s key features included:
- Easy loan application process
- Spending and savings analytics
- Personalized financial management recommendations
- Real-time credit decision-making
- Improved customer experience: The app provided an easy-to-use interface that enabled customers to apply for loans, track their spending, and manage their savings all in one place, improving their overall experience. The app resulted in a 20% increase in customer satisfaction ratings.
- Faster credit decisions: The solution could process large amounts of data in real-time, enabling the NBFC to provide instant credit decisions to its customers. There was a 30% increase in loan application processing speed.
- Personalized financial management: The machine learning algorithms analyzed customers’ spending and saving patterns and provided personalized recommendations to help them manage their finances better.
- Increased operational efficiency: The app digitized the lending process, reducing paperwork and manual processing, leading to increased operational efficiency. There was a 25% reduction in loan processing costs.
- Improved risk management: The app leveraged machine learning algorithms to analyze customer data and assess credit risk, leading to better risk management and reduced losses. There was a 15% decrease in loan default rates.