Sophisticated Loan Endorsement System

ISBN-13: 9786206739258 / Angielski / Miękka / 112 str.

Dr. K Venkata Naganjaneyulu; Dr. Suneel Pappala; Dr. Avinash Roy

Opis

Humankind's survival and standard of living have been enhanced through technology. We aim to produce new and original content every day. In the banking industry, the candidate receives proofs/backup prior to the loan amount being approved, therefore we have machines to support our lives and somewhat complete us. The system's use of the candidate's history data determines whether or not the application is granted. Numerous individuals ask for loans in the banking industry every day, yet the bank's resources are constrained. Using a classes-function algorithm in this situation would be quite advantageous. Several examples include support vector machine classification, logistic regression, and random forest classifiers. The quantity of loans a bank makes or loses depends on how much the client or candidate pays back the loan. The most crucial task for commercial banks is loan recovery.

O autorze

Dr K Venkata Naganjaneyulu presently working as a professor of CSE Dept in Lords Institute of Engineering and Technology (an autonomous institution), affiliated to Osmania University, Hyderabad, Telangana State, India. Dr K Venkata Naganjaneyulu worked as a professor of CSE Data Science Dept in StMary's Goup of Institutions, Hyderabad, JNTU, TS.