Hishab’s Credit Scoring system is a machine learning based model where the system could provide with a score 1-10 (1 is the minimum score and 10 being the maximum score). The score would mean that the individuals capability of financial inclusion (getting loan and repaying the loan from either MFIs or Banks). In Hishab credit scoring system, all the MSE (Micro Small Enterprises) would go through a call based Psychometric Analysis. Approximately around 30 questions would be asked by Hishab AI (Artificial Intelligence). Based on each question the dialogue flow is created and based on the answers the next questions would be conversed. Based on the conversation, now Voice based Lie Detection could analyse the voice tone and provide a result on the metrics of lie. The core intention with Psychometric Analysis and Lie Detection is to judge the entrepreneurial skills, the right amount of money to be disbursed, judging his intention to give back regular installments. To have much more precision on the users behavior and to come up with accurate score, the system could also judge past business records and loan repayment records (if any). Based on all the accumulated data, a score could be published to the MFI’s and Banks stating the creditworthiness. All the information would be shared with the Banks and MFIs through an API.