The case study of a RCB was screened initially through eight face-to-face interviews conducted in August 2010, and then subsequent e-mail and telephone conversations. The case is a local RCB located in Jiangsu province, in the eastern part of China where SMEs were well developed. This case bank is one of the early developed RCBs in China and has developed a relatively comprehensive CRM system. Information-gathering techniques implemented during execution of the case study included obtaining historical data and documentation, as well as conducting semi-structured interviews with CRM personnel and bank managers in the case bank. Each interview has duration of approximately one hour and conducted in Chinese in the bank offices. The semi-structured interviews ensured that the researchers maintained control over each interview, without discouraging the discussion of any valuable, additional information. The information from the case and transcripts of interviews were analysed to identify risk factors facing SMEs and farming households. It is extremely important to distinguish between failures and closures. Watson and Everett note that closing firms could have been financially successful but closed for other reasons.
To define failures they create five categories: ceasing to exist ; closing,or a change in ownership; filing for bankruptcy; closing to limit losses; and failing to reach financial goals. Headd finds that only one-third of new businesses closed under circumstances that owners considered unsuccessful.In the proposed framework, stacking pots it is essential for RCBs to carry out this kind of analysis before starting to develop a default prediction model concerning their SME and farming household clients. Separating the cases of closures from the ones of failures improves the quality of the available information and of the prediction power of a model. In the credit analysis, RCBs should take into account only clients that entered into liquidation, administration or receivership.The construction of CRM framework for RCBs should be based on the analysis of various risk factors affecting failures of the major customers of RCBs. In this study these risk factors are categorised into four clusters: environmental, financial,operational, and guanxi risks. These factors reflect the perceptions of various stakeholders involved in RCBs’ CRM obtained through the case study. Different from the previous literature, this study considers both financial data and non-financial data in analysing credit risk. The value of non-financial information in SMEs’ CRM has been recognised in the literature.
The literature recognises that quantitative variables are not sufficient to predict SME default and qualitative variables should be considered along with quantitative variables in predicting the failures of SMEs.The framework is divided into five steps. The first step is to distinguish business failure and closure. In credit risk analysis, the focus should be on the failure.Business closure does not mean the failure. The second step is to identify factors contributing to the failure, which should be considered from environmental,operational, financial, and guanxi dimensions. Some factors may appear in one case, but not in other cases. The third step is to identify the principal factors by using specific techniques. Based on the key factors, RCBs design credit risk analysis models with a focus on the analysis of these key/principal factors. The final step is to use the credit risk analysis model to manage credit risks of their portfolios and individual loans. SMEs and farming firms are facing the challenges raised from globalisation, grow lights increased customer expectations, technological advances, and increased competition.The main external environmental triggers include among others government laws and regulations, globalisation of markets and the internationalization of business, major economic, political and social events, technological advancements,customer expectations, supplier requirements, increasing competition,organisational growth, and fluctuations in business cycles.
The changing demographics and the challenges to SMEs in attracting and retaining skilled workers were also identified as major factors influencing business failures. The recruitment and retention challenge is complex for SMEs and it is expected to continue over the long term. Demographic changes , specifically the aging workforce and the declining entrant pool, are occurring in China and SMEs are currently countering some of the impacts.A lack of effective risk management programme in SMEs is also a major factor contributing to the failure of many SMEs. One overriding factor that contributes to ineffective risk management in SMEs is a lack of infrastructure, risk management skills, human capital and adequate management knowledge and training. Gao et al. acknowledge the limited risk management capability building in Chinese SMEs largely due to lack of adequate education and qualification, higher staff turnover and negative attitudes of both owner-managers and employees towards the use of technology, learning and training.