Faculty of Commerce, Law and Management (ETDs)

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    Towards a framework for operational risk management in the banking sector
    (University of the Witwatersrand, Johannesburg, 2022) Hoohlo, Mphekeleli
    The objective of this study is three-pronged. One, it investigates the factors that influence capital adequacy as measured by the covariates (exposure, frequency and severity) used in banking operations that accompany firms data-log loss reports. Two, it assesses the differential impact of discretionary (by adding artificial data) and non-discretionary (using real world data) loss disclosure on firms’ value-at-risk. R software is used to determine the value-at-risk. GLM and GAMLSS techniques are employed and subsequent tests of significance derive aforementioned influential factors, accompanied by a data augmentation algorithm in Matlab software to determine the differential impact of artificial and real world operational loss disclosures on firms’ performance in relation to meeting capital requirements. Three, it challenges firms’ risk-neutral assumption inherent in operational risk practice, asserting that; in theory, banking operations are more risk averse. Rattle software is used in a k-means cluster analysis method to determine whether controls compensate for persistent losses due to the firms’ natural risk aversion. The research arrived at estimates on the number of losses and their sizes; whereby exposure positively influences the risk ceded by the bank having “learned” from possible variations in past data, therefore improving operational risk manage- ment frameworks by introducing ex ante forward-looking components, whereas the addition of artificial data points by data augmentation circumvents former dilemmas of large and rare events so one can do more “learning”, notwithstanding the nature of the data’s suspect quality as they are constructs not observations. Nevertheless, the artificial intelligent EBOR framework’s performance improves on (Hoohlo (2014)’s applied data scaling and parametization techniques arrived at a proxy of about ZAR3B) former techniques for capital adequacy calculation of OpRisk opening up exploration modeling beyond historical accounts of significance to incorporate forward-looking aspects. Furthermore, checks and balances set up based on operational negligence slow down operational risk losses over time thereby establishing the move of firm risk tolerance levels away from risk neutrality, suggesting that banks are more risk averse
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    Investigating the factors that affect the willingness to adopt peer-to-peer short-term insurers in South Africa
    (University of the Witwatersrand, Johannesburg, 2023) Dörfling, Daniel
    This quantitative study aims to identify the propensity for clients (both legal and natural persons) to adopt peer-to-peer short-term policies as opposed to traditional, centralised short-term insurance policies
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    Artificial Intelligence-driven transformation of risk management function in the South African Telecommunications Industry
    (2022) Ramatar, Nitesh
    Current Artificial Intelligence (AI) solutions focus on improving business operational processes and specific applications within the risk management fraternity. AI enables organisations to accelerate processes rapidly. However, this fast pace introduces new risk exposures that require proactive risk management. Therefore, this study explored whether AI should be utilised within the risk function of a telecommunications company, to make the function proactive. The research adopted an exploratory approach that involved conducting face-to-face interviews with risk management professionals within the telecommunications environment. The respondents’ feedback was consolidated to identify and analyse findings. Findings noted that risk functions should adopt AI to help them transition from a reactive to a proactive function. However, key challenges, such as budget constraints, poor stakeholder buy-in, and limited access to AI skills and appropriate use cases, prevent risk functions from adopting AI. Establishing change management initiatives is recommended to create a culture that can overcome these challenges.
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    Digitalisation of risk management in the South African banking industry: a case study of a major South African bank
    (2020) Gresse, Lambert Francois
    The research studies the impact that digitalisation has on banking in South Africa, how it impacts the inherent risk in the system and accordingly, how banks respond to those risks that digitalisation presents using digitalised risk response strategies. The fourth industrial revolution has meant that the way in which banks are differentiating themselves from their competitors and what customers are demanding from them are rapidly changing. This is distinct from previous industrial revolutions as it is characterised by velocity, scope and systems impact. Companies are being exposed to disruptive technologies and with it comes increased complexity and risk. Therefore, there is an apparent link between digitalisation and risk management. The research aims to understand the impact of digitalisation on risk management and accordingly how banks should respond to mitigate those risks. The research adopted a mixed method, case study approach. The research was conducted using online questionnaires and face-to-face interviews, with structured and semi-structured questions. The data collected from the questionnaires and feedback from participants in the interviews were then combined to draw a conclusion based on the findings. Key findings and insights were that banks should revisit the methods and models used to perform risk management, as velocity plays an increasing role in the types of risk that disruptive technologies introduce. Furthermore, the role that staff members, their skills and the tools that they have access to, to respond to risks, needs to improve.