Research On The Calculation Of Talent Pricing And Post-loan Risk In "Talent Loan"

The issuance of "talent loans" to qualified talents to support their entrepreneurship is one of the important measures for many cities to attract talents.The "talent loan" process includes application,investigation,evaluation,approval,contract signing,issuance,post-loan management,and recovery.This article is mainly responsible for the talent pricing calculation and post-loan talent risk management in the evaluation and approval process.Although some provinces and cities have already granted large-amount credit loans to specific talents,the amount of loans lacks theoretical support and is mostly based on the experience of banks.The pricing of talents is the basis of loans,but due to the high specificity,the human capital pricing of high-level talents has always been a difficult point.The purpose of this paper is to propose a method for measuring the value of talents as the basis for talent credit loans,so that talents can obtain loan financing for their start-ups or management enterprises.First of all,this paper uses the mincer equation to estimate the current income of talents according to more possible evaluation factors,and then uses the Jorgenson-Fraumeni lifetime income method to measure the lifetime value of talents,and designs a method to measure the human resources contained in talents.Regardless of whether the applicant has current income or work experience,as long as there is enough relevant data,the bank can calculate the value of the talent based on the model,and then determine the loan amount for start-ups or individual talents.At the same time,this paper also hopes that after lending funds to talents for company operation,we can have a clearer understanding of the possibility of default of this money.We believe that the default of"talent loan" is mainly composed of two parts:one is the probability that the enterprise cannot pay due to poor management,and the other is the probability that the individual cannot repay after the enterprise goes bankrupt.The probability of default on the talent loan is the product of the two.According to the operation of borrowers and enterprises,this paper uses the regression method to find the relationship between the value and fluctuation of small and medium-sized enterprises and financial data on the basis of using the KMV model.A method that can estimate the default probability of borrowers and enterprises can be used as a reference for banks to pay attention to and control loan risks in a timely manner.In addition to traditional model methods,this paper proposes heuristic methods with the help of powerful machine learning tools.