Microcredit is a method of lending small amounts of money to low-income individuals who have no access to traditional financial institutions. Upon applying for a loan, an individual may either be able to repay it and be granted a loan again, otherwise s/he demands for a new loan. These events influence certain factors, which can be illustrated through a hidden Markov model (HMM). This study provides a hidden Markov representation of microcredit taking into consideration the borrower's acquisition of small businesses. Model algorithms used in addressing the problems in HMM, such as the Viterbi algorithm, are discussed and implemented via numerical examples.
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