The Data Analytics Blog

Our news and views relating to Data Analytics, Big Data, Machine Learning, and the world of Credit.

All Posts

The History Of Fashion Retail Credit In South Africa

October 8, 2017 at 7:53 PM

InfographicMost industries owe their levels of sophistication to the visionaries in their space.  The South African credit industry is no different.  Whilst the bureaux and the banks have played a significant role in developing the South African credit landscape, arguably the fashion retailers have also played a pioneering role in revolving credit. And so our vibrant industry owes much to the role of the fashion retailers.  But how did it all begin?

Many of the major players in fashion retail today opened their first stores at the beginning of the 20th Century. The story of wide-spread fashion retail credit has its beginnings in the 1930s with Eli Ross and Sydney Press of Edgars.  The 1930s were years of depression and for many, out-right purchases were not possible.  Although lay-bys were common in all stores for those who could not afford goods, they were a logistical problem and hardly consumer friendly.

And so decentralised fashion retail credit and the 6-month no-interest account was introduced. Although launched in the urban stores initially, it was quickly adopted by rural branches.  In the rural areas it was notably in the female-run stores (where there existed strong relationships between the female manager and the mostly female customer-base) where it proved most successful.

Infographic 2.png

Consumers were assessed on character and developed a personal relationship with the store manager and were able to purchase goods immediately.  Such relationships were good for both brand reputation and for the customer, particularly during the depression years.  Little was done on merchandise margin to account for bad-debt and net-present value of money, the facility simply increased merchandise purchases and cemented trusted relationships with customers.


Over time, other retailers also introduced credit in their stores. Truworths first offered credit in the 1950s.  It was however with the migration to computerised systems that centralised credit first became possible.  Woolworths became the first retailer to adopt a computer when they did so in the 1960s.  By the 1970s they ran a computerised merchandising system.  Other retailers followed suit.

Centralised Credit

Woolworths east london.pngAs systems were more widely adopted, it was the early 80s that saw the advent of centralised credit.  Edgars again paved the way with the first centralised retail card. There was a gradual process of migrating store-managed accounts to the central debtors’ system. For the first time a customer could shop at multiple stores with the same card hassle free.   One of the key enablers was automatic authorisations.  Previously shopping at another store would require one manager to phone your home store to confirm your current open-to-buy amount.

Technology and Analytics

Evolution of retailThe approval process for retail credit has also come a long way.  In the early days of centralised credit decisioning was basic rule-based. Application scoring really began in the 90s. That decade also brought the first bureau score when TransUnion (then ITC) launched Empirica. Outside of originations, credit managers would apply regular limit increases for those up-to-date accounts with balances close to the account limits.  Behavioural scores were first adopted in the mid-90s when Edcon, Foschini, Truworths and Woolworths all graduated to FICO’s (then Fair Isaac) account management platform TRIAD.  Thereafter, South African retailers enjoyed phenomenal growth driven by sophisticated credit and marketing strategies as well as diversifying into other financial products.  Expert strategies became data-driven strategies and have since, in some cases, become mathematically optimised strategies.  Truworths were the first credit issuer in Africa to adopt mathematical optimisation in credit decisioning when they did so in 2006.

Principa are proud to have established long-lasting relationships with almost all of the retailers mentioned here.  Our data analytics, strategic consulting and support of FICO software has allowed us to be part of this exciting and pioneering journey.  We look back proudly at nearly twenty years of value-generating projects and we look forward eagerly to the challenges that still lie ahead.

Get IFRS 9 Compliant

For more information about what Principa offer in the credit space please return to our home page and look under our “Product & Solutions” menu tab.


Thomas Maydon
Thomas Maydon
Thomas Maydon is the Head of Credit Solutions at Principa. With over 17 years of experience in the Southern African, West African and Middle Eastern retail credit markets, Tom has primarily been involved in consulting, analytics, credit bureau and predictive modelling services. He has experience in all aspects of the credit life cycle (in multiple industries) including intelligent prospecting, originations, strategy simulation, affordability analysis, behavioural modelling, pricing analysis, collections processes, and provisions (including Basel II) and profitability calculations.

Latest Posts

The 7 types of credit risk in SME lending

  It is common knowledge in the industry that the credit risk assessment of a consumer applying for credit is far less complex than that of a business that is applying for credit. Why is this the case? Simply put, consumers are usually very similar in their requirements and risks (homogenous) whilst businesses have far more varying risk elements (heterogenous). In this blog we will look at all the different risk elements within a business (here SME) credit application. These are: Risk of proprietors Risk of business Reason for loan Financial ratios Size of loan Risk industry Risk of region Before we delve into this list, it is worth noting that all of these factors need to be deployable as assessment tools within your originations system so it is key that you ensure your system can manage them. If you are on the look out for a loans origination system, then look no further than Principa’s AppSmart. If you are looking for a decision engine to manage your scorecards, policy rules and terms of business then take a look at our DecisionSmart business rules engine. AppSmart and DecisionSmart are part of Principa’s FinSmart Universe allowing for effective credit management across the customer life-cycle.  The different risk elements within a business credit application 1) Risk of proprietors For smaller organisations the risk of the business is inextricably linked to the financial well-being of the proprietors. How small is small? The rule of thumb is companies with up to two to three proprietors should have their proprietors assessed for risk too. This fits in with the SME segment. What data should be looked at? Generally in countries with mature credit bureaux, credit data is looked at including the score (there is normally a score cut-off) and then negative information such as the existence of judgements or defaults; these are typically used within policy rules. Those businesses with proprietors with excessive numbers of “negatives” may be disqualified from the loan application. Some credit bureaux offer a score of an individual based on the performance of all the businesses with which they are associated. This can also be useful in the credit risk assessment process. Another innovation being adopted internationally is the use of psychometrics in credit evaluation of the proprietors. To find out more about adopting credit scoring, read our blog on how to adopt credit scoring.   2) Risk of business The risk of the business should be managed through both scores and policy rules. Lenders will look at information such as the age of company, the experience of directors and the size of company etc. within a score. Alternatively, many lenders utilise the business score offered by credit bureaux. These scores are typically not as strong as consumer scores as the underlying data is limited and sometimes problematic. For example, large successful organisations may have judgements registered against their name which, unlike for consumers, is not necessarily a direct indication of the inability to service debt.   3) Reason for loan The reason for a loan is used more widely in business lending as opposed to unsecured consumer lending. Venture capital, working capital, invoice discounting and bridging finance are just some of many types of loan/facilities available and lenders need to equip themselves with the ability to manage each of these customer types whether it is within originations or collections. Prudent lenders venturing into the SME space for the first time often focus on one or two of these loan types and then expand later – as the operational implication for each type of loan is complex. 4) Financial ratios Financial ratios are core to commercial credit risk assessment. The main challenge here is to ensure that reliable financials are available from the customer. Small businesses may not be audited and thus the financials may be less trustworthy.   Financial ratios can be divided into four categories: Profitability Leverage Coverage Liquidity Profitability can be further divided into margin ratios and return ratios. Lenders are frequently interested in gross profit margins; this is normally explicit on the income statement. The EBIDTA margin and operating profit margins are also used as well as return ratios such as return on assets, return on equity and risk-adjusted-returns. Leverage ratios are useful to lenders as they reflect the portion of the business that is financed by debt. Lower leverage ratios indicate stability. Leverage ratios assessed often incorporate debt-to-asset, debt-to-equity and asset-to-equity. Coverage ratios indicate the coverage that income or assets provide for the servicing of debt or interest expenses. The higher the coverage ratio the better it is for the lender. Coverage ratios are worked out considering the loan/facility that is being applied for. Finally, liquidity ratios indicate the ability for a company to convert its assets into cash. There are a variety of ratios used here. The current ratio is simply the ratio of assets to liabilities. The quick ratio is the ability for the business to pay its current debts off with readily available assets. The higher the liquidity ratios the better. Ratios are used both within credit scorecards as well as within policy rules. You can read more about these ratios here. 5) Size of loan When assessing credit risk for a consumer, the risk of the consumer does not normally change with the change of loan amount or facility (subject to the consumer passing affordability criteria). With business loans, loan amounts can range quite dramatically, and the risk of the applicant is normally tied to the loan amount requested. The loan/facility amount will of course change the ratios (mentioned in the last section) which could affect a positive/negative outcome. The outcome of the loan application is usually directly linked to a loan amount and any marked change to this loan amount would change the risk profile of the application.   6) Risk of industry The risk of an industry in which the SME operates can have a strong deterministic relationship with the entity being able to service the debt. Some lenders use this and those who do not normally identify this as a missing element in their risk assessment process. The identification of industry is always important. If you are in manufacturing, but your clients are the mines, then you are perhaps better identified as operating in mining as opposed to manufacturing. Most lenders who assess industry, will periodically rule out certain industries and perhaps also incorporate industry within their scorecard. Others take a more scientific approach. In the graph below the performance of an industry is tracked for two years and then projected over the next 6 months; this is then compared to the country’s GDP. As the industry appears to track above the projected GDP, a positive outlook is given to this applicant and this may affect them favourably in the credit application.                   7) Risk of Region   The last area of assessment is risk of region. Of the seven, this one is used the least. Here businesses,  either on book or on the bureau, are assessed against their geo-code. Each geo-code is clustered, and the projected outlook is given as positive, static or negative. As with industry this can be used within the assessment process as a policy rule or within a scorecard.   Bringing the seven risk categories together in a risk assessment These seven risk assessment categories are all important in the risk assessment process. How you bring it all together is critical. If you would like to discuss your SME evaluation challenges or find out more about what we offer in credit management software (like AppSmart and DecisionSmart), get in touch with us here.

Collections Resilience post COVID-19 - part 2

Principa Decisions (Pty) L

Collections Resilience post COVID-19

Principa Decisions (Pty) L