The development of mobile and internet technologies has revolutionised every sector of the economy worldwide. Artificial intelligence has brought about the next wave of micro-finance revolution. Micro-finance has played a significant role in transforming lives of millions of households across the globe. The Micro-finance institutions (MFIs) are undergoing a digital transformation to save costs, determine credit worthiness of potential borrowers and risk. This conceptual paper focus on understanding how artificial intelligence is shaping the micro-finance sector in the 21st century. We review the literature to draw from different experiences of the micro-finance industry around the world and provides evidence from a Micro-finance Institution in Haryana, India. Both logistic regression and neural network (NN) methods was applied to the data of the MFI and results were compared. This article demonstrates how a credit scoring model can be applied for an India-based micro-finance company to estimate the relative importance of each factor involved in the probability of default. To identify the main causes of default by the micro-finance clients, a logistic regression model and Neural networks model was used and the latter was found to have better prediction power.