• Launches Banyan 2.0 which uses Artificial Intelligence & Machine Learning Models to recommend credit decisions
Bengaluru, India, January 9, 2019 : The estimated number of MSMEs (Micro, Small & Medium Enterprises) in India is a staggering 44.50 million. One of the major driving factors of India’s GDP growth is the MSME industry, which employs 40% of India’s Workforce, contributing 45% of the output and 40% of the exports. Hence, the financial needs of this industry is growing as well.
MSMEs are also one of the most crucial customer base for NBFCs and other financial institutions, as they don’t change their financial institutions often and are a very loyal set of customers, which is why it is very important for financial institutions to deliver world-class customer service. With increasing credit requirement of the MSMEs, financial institutions should leverage technology to originate high loan volumes at faster speed, ensuring better transparency and enhancing customer service along-with decreasing the cost of the loans.
FOS platform of eSthenos Technologies enables Financial Institutions to on-board MSME Borrowers under 30 minutes with its real-time, cloud based data collection and risk assessment module. The highly sophisticated and modern design architecture enhances the security and the quality of the data collected. Availability of data in cloud and multiple internal and external API integrations results in improved reaction time for users.
Faster and accurate data collection with minimal paperwork and real-time credit worthiness check reduces the turnaround time of the disbursal. Based on algorithmic credit assessment models, the platform gives a wider and precise view of the borrower’s credit worthiness. Real-time monitoring of the performance of each application based on hierarchy helps the management to make better and faster decisions and reduces monitoring cost by a substantial margin.
eSthenos launches its improved version of its platform Banyan. Lending institutions have a mine of data, which if put to correct use can create constructive results. This data can be used to create better credit models based on the customer’s history. Banyan can analyse the data of Financial Institutions to recommend product pipelines for cross-sale, understand and benchmark competitors data, internal fraud detection and generate sales pipeline who can be approached in the future.
