3.8 Challenges for banks
3.8.2 Challenges for credit managers when assessing small business credit
3.8.2 Challenges for credit managers when assessing small business credit
Collateral
Lack of adequate collateral (in the form of immovable property or valuable movables) that banks require as security in the event of default.
Source: Authors own compilation
According to Buma et al. (2010:35) banks are not equipped with the necessary skills to assist entrepreneurs, and do not have a well-defined measure of small business risk. One could ask the question then, on how it can be improved if it is not measured. Furthermore, uncertainty when considering a small business credit application for approval could lead to the bank requesting more information on the business in the hope of providing more comfort on the likelihood of the repayment of the credit amount applied for. However, as identified above, it can be particularly challenging to collect information about small businesses, more so for start- ups, due to unavailable/unreliable financial information and limited/no credit history (Berger &
Udell, 2005).
This position creates uncertainty for the bank on the credit risk of an applicant as the lack of credible information makes it difficult for the bank to determine the competence and commitment of the entrepreneur and the prospects for the business (Parker, 2002).
Furthermore, the applicant (small business) will always have a better understanding of their actual financial position, the detail of the investment project, and the intention to pay back the debt, than the bank. This results in information asymmetry as the small business has the higher ranking exclusive information (asymmetric information), leaving the credit managers to make decisions based on imperfect information (Maziku, 2012).
According to Bergh et al. (2018), information asymmetry takes place when one side to the lending transaction has more and/or better-detailed information than the other side.
Asymmetric information hence creates problems for the bank before concluding a credit transaction (adverse selection) and after the transaction has been closed (moral hazard) (Berndt & Gupta, 2009).
Adverse selection occurs as it is difficult for credit managers to differentiate between high-risk and low-risk borrowers due to the lack of credible information to base decisions on (Stiglitz &
Weiss, 1981). Due to this uncertainty, banks normally charge higher interest rates to small businesses overall to compensate for the increased risk due to the inability to determine which applicants to grant credit to. The low-risk borrowers are hence penalized at the expense of the high-risk borrowers (Maziku, 2012). Moreover, the high interest rates discourage low-risk small businesses from applying for credit and encourage the more risky businesses to apply for
more credit. As the businesses know their financial position more than the bank, the riskier businesses are normally aware that based on their high-risk profile they should be paying higher interest rates (Beck et al., 2018). Consequently, the banks normally end up with a high- risk small business credit portfolio (Berndt & Gupta, 2009).
Effectively adverse selection occurs when bad credit risks (businesses which have poor investment channels and high interest risks) become more probable to acquire credit than good credit risks (businesses with better investment opportunities and less inherent risks) (Mason & Stark, 2004).
Moral hazard occurs after the credit has been disbursed to the borrower and it arises in situations when the borrower, for example, breaches the credit agreement covenants by applying the funds in immoral projects. Information asymmetry once again in this instance resulted in moral hazard due to the bank's lack of knowledge of the borrower’s activities. Moral hazard also occurs due to the high cost to the bank to enforce the covenants of the credit agreement, which gives the borrower more leeway to invest in high risk and immoral projects (Berndt & Gupta, 2009).
Furthermore, loan cost is one of the most critical risk dimensions for banks. If the loan cost is high relative to the potential interest revenue to be earned, it may not be worthwhile for the bank to grant that specific loan. Small business loans are considered less profitable than the larger loans as they are considered by banks to be more banker-time intensive, are more difficult to automate, have higher costs to underwrite and service, and are more difficult to securitize and collect on (Minnis & Sutherland, 2017).
As most loan costs are fixed, the net profit on small business loans relative to the size of the loan is lower than that for larger businesses which can spread the fixed costs over more Rand value. The transaction cost per Rand lent is therefore much higher for small loans than for larger loans (Turner et al., 2008).
The limited information on customers further drives up the cost of collections. Moreover, the bank may not be able to collect at all where the defaulting customer cannot be found or traced.
Another aspect to consider is the increased competition faced by banks as there are many large retailers which now provide credit, making the pool of customers smaller for banks. In order to optimize more on profits, banks are moving toward bigger, more profitable loans with a result of a decline in small business loans (Minnis & Sutherland, 2017).
Considering that banks do not have a well-defined measure of small business risk, it appears a size bias causes both higher rates and more covenants to be levied against the smaller
businesses (Turner et al., 2008). It is a concern that small businesses may be paying interest rate premiums that are not fully warranted by extra risk (Jones, 2005:46). The other challenge identified by Kim et al. (2006) is that banks are not well placed to cater to the needs of start- ups and small businesses.
Turner et al. (2008) state that countries are beginning to use non-financial payment data such as utility bills and telecom payments when standard credit information is unavailable. However, such information is rarely collected in South Africa. Turner et al. (2008) argue that collecting more trade credit data from the informal sector could greatly expand access to credit for small businesses.
The above provided a background on the challenges faced by credit managers when assessing small business credit applications. One could derive that the challenges mentioned above could be similar to the reasons for the decline of small business credit applications. The reasons for the decline of small business applications will be further explored.