An analysis of the implementation of automated credit risk management strategy on loan recovery rate among Standard bank Zambia clients in Lusaka district, Zambia.
type: CreativeWork
description: The purpose of the study was to investigate the efficiency of automated credit risk strategy approved in 2019, compared with manual earlier used by Standard Chartered Bank, to enable reduce debt default and manage risk among clients of Lusaka, district Zambia. The study used loan client appraisal, Credit terms and policy as dimensions to compare the effectiveness of the two methods between automated and manual in credit risk management process. The descriptive and correlational research designs were used to gain understanding on the subject under investigation. Stratified simple random sampling techniques were used on sample size of 40 respondents. Questionnaires, structured interviews and test observations were used to collect qualitative and quantitative data respectively. Qualitative data were analysed using themes derived from the research objectives and quantitative data by using Regression and Correlation analysis models with the help of Statistical Package for Social Sciences (SPSS). Therefore, findings of the study reviewed, that manual credit risk strategy was not effective, it indicated incidents of loan defaults and was the cost to the bank in bad debts written off. Furthermore, the results showed a relationship of (0.9), suggested a strong positive performance of automated credit risk strategy. The study revealed, that failure to proactively follow the 5 Cs (Character, Collateral, Capacity, Capital and Condition) and lack of adequate training on loan recovery process, caused loan default, however, the study suggested that, credit risk can be mitigated by constantly sending credit reminders notices. The study further revealed, that lately, digital credit automation methodology had developed rapidly, particularly in Lusaka, district, Zambia. Even though, the study disclosed that not many clients had gotten access to digital loans. Based on the findings, the study recommended that the Bank should invest in digital automated credit risk strategy, monitoring …
abstract: The purpose of the study was to investigate the efficiency of automated credit risk strategy approved in 2019, compared with manual earlier used by Standard Chartered Bank, to enable reduce debt default and manage risk among clients of Lusaka, district Zambia. The study used loan client appraisal, Credit terms and policy as dimensions to compare the effectiveness of the two methods between automated and manual in credit risk management process. The descriptive and correlational research designs were used to gain understanding on the subject under investigation. Stratified simple random sampling techniques were used on sample size of 40 respondents. Questionnaires, structured interviews and test observations were used to collect qualitative and quantitative data respectively. Qualitative data were analysed using themes derived from the research objectives and quantitative data by using Regression and Correlation analysis models with the help of Statistical Package for Social Sciences (SPSS). Therefore, findings of the study reviewed, that manual credit risk strategy was not effective, it indicated incidents of loan defaults and was the cost to the bank in bad debts written off. Furthermore, the results showed a relationship of (0.9), suggested a strong positive performance of automated credit risk strategy. The study revealed, that failure to proactively follow the 5 Cs (Character, Collateral, Capacity, Capital and Condition) and lack of adequate training on loan recovery process, caused loan default, however, the study suggested that, credit risk can be mitigated by constantly sending credit reminders notices. The study further revealed, that lately, digital credit automation methodology had developed rapidly, particularly in Lusaka, district, Zambia. Even though, the study disclosed that not many clients had gotten access to digital loans. Based on the findings, the study recommended that the Bank should invest in digital automated credit risk strategy, monitoring …
author: Chamangwa, Justine
language: en
keywords: Automated Credit, Risk Management, Loan Recovery Rate, Lusaka, Electronic services., Bank Management and Control., Credit--Management., Risk management., Bank capital.
date published: 2022-06-09
date modified: 2026-07-27T22:06:26Z
provider: University of Zambia
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: The University of Zambia