AI Platform Lending Market Analysis

End-user (Bank, Educational Institution, Government Organization)

The global AI platform lending market is segmented and analyzed for demand and supply by end-user into bank, educational institution, government organization, and others, out of which, the bank segment is anticipated to witness major growth over the forecast period. The growth of the segment can be accounted to the rising number of banks and their users. In 2018, the number of banks worldwide was anticipated to be around 45,000. The automation and digitization of banks increase the preference of people for banks for their financial support. More government and private banks are increasing their branches in rural and urban areas to increase their turnover. The banks initiated many policies for farmers with less interest in improving customers and loan transactions in public and private banks. The regulations and documentation process required for loan processing are increasing the adoption of AI tools in the banking sector, which in turn drives the growth of the market segment.

Type {Natural Language Processing (NLP), Deep Learning (DL), Machine Learning (ML)}

The global AI platform lending market is also segmented and analyzed for demand and supply by type into natural language processing (NLP), deep learning (Dl), machine learning (ML), and others. Amongst these three segments, the machine learning segment is expected to garner a significant share. ML and AI-based lending help to save time and energy by using raw data very efficiently. The ML application in finance helps to automate many tasks, including calculation, data monitoring, claim to process, and paper works. This reduces labor costs and improves customer service. Customer behavior can be easily analyzed and their preferences can be generated by ML and AL in IoT devices. Algorithm trading, detection of fraud activities, security portfolio management, high-frequency trading, chatbot creation, risk management, trade settlements, customer acquisition, onboarding automation, and asset valuation are done through ML in many financial institutions.

Our in-depth analysis of the global market includes the following segments: