Abstract
Information technology, Digital Services using API, Artificial Intelligence, Data Science, Mobile banking, Automation spawn tremendous contribution in the direction of growing the efficiency, increasing huge number of customers, advance eminence customer services to most banking business application processes. With the enhancement in the banking sector lots of people are applying for bank loans Individual, Mortgage Loans, House loans, Apartment loans, Agriculture loans. These days bank managers and lawyers are facing abounding complications to sanction a loan by perceiving previous 30 years of link documents for specific site for house loan. For the most part from lawyer's perspective, to sanction legal approval, he must have to verify all bulk bundles of Registration documents, link connectivity, Identifying miss matches of sale deeds, owner relationships, family member certificates, death certificates, Re-registrations on same land, verifying any Hostage lands previously. In order to do the total procedure, lawyers may grasp three months span of time to extract conclusions by studying all documents based on project cost and litigations based on lands and it may vary according to project capital of Investment. In this project, we are trying to turn down the risk factor, computational time, ill- assorted Registration documents and Cross verification of all edge communications to make decisions to sanction the loan from lawyers, Bank Mangers, legal perspective and approve loan efficiently within stipulated time using decision tree approach of " Real Time Data Science Decision Tree Approach To Approve Bank Loan From Lawyer Perspective". we incorporated PHP, Python, XAMPP Web server, HTML, Data Science Decision tree approach to make lawyers decisions for legal approval within fraction of two minutes by entering all the document details into a database. we also incorporated execution results and discussed efficiency of proposed system with multiple scenarios.
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