Two students from UCT have designed South Africa\u2019s first systemic risk ranking \u2013 which outlines what could happen in a financial crisis and identifies who is putting the system most at risk, and why.<\/p>\n
The ranking system highlights some of the dangers and risks facing South Africa\u2019s banks \u2013 an industry that has been hit by recent revelations of collusion and currency fixing, resulting in the Competition Commission referring to the Tribunal for prosecution against 17 banks.<\/p>\n
Designed by two students from the University of Cape Town (UCT) African Institute of Financial Markets and Risk Management (AIFMRM), the SA Financial Institution Systemic Risk Ranking rates South African financial institutions according to their contribution to systemic risk \u2013 which is the likelihood that the failure of a bank would lead to the failure of the financial system as a whole.<\/p>\n
While the ranking does not give any indication of the likelihood that a financial institution will default, it gives an indication of how such a default would affect other South African financial institutions.<\/p>\n
\u201cWe thought it was very important to understand the financial system as a whole and to be able to look at who is putting the system at risk and why,\u201d said Qobolwakhe Dube, a PhD student at UCT. \u201cWe used a lot of statistics and mathematics to arrive at our model, which can be updated easily with a few clicks of the button,\u201d he says.<\/p>\n
The model is an adaption of the SRISK model which was developed by Nobel laureate Robert Engle from the New York University\u2019s Stern School of Business following the financial crisis of 2008.<\/p>\n
\u201cIt is especially valuable for policy makers and regulators to know which companies contribute most to systemic risk and may be in need of additional scrutiny and oversight,\u201d said UCT Masters student and co-founder of the ranking, Tr\u00e9sor Kaya.<\/p>\n
The point of the systemic risk ranking is not to identify institutions that are at risk of failure, but to look at which institutions would have the greatest impact on other institutions should they fail.<\/p>\n
According to Dube and Kaya\u2019s model, this would be the Standard Bank Group, which leads the ranking quite significantly at 25.56% before Barclays Africa Group at 13%. In third place is the FirstRand Group at 12.94%.<\/p>\n
\u201cIt is significant because it shows that only three financial institutions constitute up to 50% of all systemic risk in South Africa,\u201d said Dube. \u201cThis is why it was possible for them to collude on fixing the rand. There is too much concentration and a lack of competition, which is not healthy for the industry.\u201d<\/p>\n
Systemic risk is affected by factors like the company\u2019s share price as well the activities the bank engages in. Liabilities also come into play as well as to whom the banks owe money.<\/p>\n
\u201cOur ranking will be most beneficial to those in industry, to the regulators as well as policy makers,\u201d said Dube. \u201cIt provides novel and very useful information and helps financial institutions to internalize their systemic risk contribution.\u201d<\/p>\n
Dube and Kaya intend updating the ranking frequently and have made the code they used freely available as open source.<\/p>\n
Financial institutions with the highest Systemic Risk Contribution<\/strong><\/p>\n <\/p>\n\n\n
\n #<\/th>\n Financial group<\/th>\n Contribution (%)<\/th>\n<\/tr>\n \n 1<\/td>\n Standard Bank Group<\/td>\n 21.56%<\/td>\n<\/tr>\n \n 2<\/td>\n Barclays Africa Group<\/td>\n 13.00%<\/td>\n<\/tr>\n \n 3<\/td>\n FirstRand<\/td>\n 12.94%<\/td>\n<\/tr>\n \n 4<\/td>\n Nedbank Group<\/td>\n 12.61%<\/td>\n<\/tr>\n \n 5<\/td>\n MMI Holdings<\/td>\n 10.70%<\/td>\n<\/tr>\n \n 6<\/td>\n Sanlam<\/td>\n 10.34%<\/td>\n<\/tr>\n \n 7<\/td>\n Alexander Forbes Group<\/td>\n 10.21%<\/td>\n<\/tr>\n \n 8<\/td>\n Old Mutual Plc<\/td>\n 2.77%<\/td>\n<\/tr>\n \n 9<\/td>\n Coronation Fund Managers<\/td>\n 2.04%<\/td>\n<\/tr>\n \n 10<\/td>\n Sygnia<\/td>\n 1.55%<\/td>\n<\/tr>\n \n 11<\/td>\n PSG Consult<\/td>\n 0.89%<\/td>\n<\/tr>\n \n 12<\/td>\n JSE<\/td>\n 0.65%<\/td>\n<\/tr>\n \n 13<\/td>\n Investec<\/td>\n 0.36%<\/td>\n<\/tr>\n \n 14<\/td>\n Investec Plc<\/td>\n 0.26%<\/td>\n<\/tr>\n \n 15<\/td>\n Prescient<\/td>\n 0.09%<\/td>\n<\/tr>\n \n 16<\/td>\n Ecsponent<\/td>\n 0.03%<\/td>\n<\/tr>\n<\/tbody>\n<\/table><\/div>\n<\/div>\n
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