I am a Quantitative Analyst at FNB Wealth & Investments, a part of Africa's largest financial services provider. With an undergraduate degree in Actuarial Science and a Masters degree in Financial Technology from the University of Cape Town, I seek to combine my skills in analytics, big data & machine learning, quantitative finance, and software engineering, with my interests in finance & investments and their intersection with mathematics.
Continuing from my graduate programme experience and Honours dissertation specialisation, I run the quantitative modelling for strategic and tactical asset allocation for various investment products across the retail & high-net-worth business.
My role is an interdisciplinary one, providing consultative input throughout the product lifecycle, from design to management. I assist with improving automation, efficiency, and robustness of reporting processess, and the overall data culture in the central solutions business.
As a minor component of my role I cover the South African listed healthcare sector.
My first rotation in 2020 was in the RMB Centre of Data Analytics where I have been involved in data preparation and visualisation for internal use as well as presentations to clients.
My second rotation was in FNB Digital Banking, where I performed analytics on consumer adoption of our digital platforms as well being involved in employing techniques for proactive detection of potential fraud.
My third rotation was in Ashburton Investments Fixed Income, performing analytics and machine learning on economic variables and financial instruments to help guide investment activity, as well as analysing options strategies. I provided analytics and feedback to corporate and retail clients.
My final rotation was in FNB Wealth & Investments, assisting with quantitative strategic asset allocation modelling and processes.
In 2020 I was certified as a Technical Member of the Actuarial Society and awarded the TASSA designation, and passed the F105 Finance and Investment Fellowship Principles exam in June 2021.
An innovative degree and the first of its kind on the African continent, the MPhil in FinTech seeks to distill an understanding of modern financial innovation and a mastery of big data analysis through courses in machine learning, software design, and distributed ledger technologies.
I achieved a GPA of 83% and the degree was awarded with distinction.
My dissertation was titled How to attribute credit if you must and involved a network-theoretic approach to diffusion of credit in academic writing, proposing a blockchain-based platform to enable this.
Based on my results I was granted all actuarial exemptions attempted during the degree: A111, A112, A113, A211, A202, A204, A213, A205, A311, and N211.
After a year of studying at Rhodes and excelling at my Mathematics studies, I transferred to UCT to take on the challenge of Actuarial Science.
I have experience working with the following languages and tools.
I worked with R and Excel for most of my studies, while most of the other tools and languages, I was exposed to for the first time during my MPhil.
Practically most of my work is currently done using Matlab, Excel, and Python, while I have used SQL extensively during my career for database work.
Outside of my studies, I have a keen interest in long distance running, and have completed numerous half-marathons over the last few years. In 2017, I completed my first full marathon, and in 2019 my first ultramarathon, running the Old Mutual Two Oceans Marathon.
I also have a keen interest in wine, and have worked part-time at the Newlands boutique store Wine Concepts from August 2017 until the end of 2020. Between 2017 and 2018 I was also heavily involved in the running of the UCT Wine & Cultural Society, as its Vice Chairperson. I blog about wine here.
In January 2019 I attended the South African Finance Association's annual conference and presented my Honours research project. This paper was later published in the Investment Analysts Journal's SAFA special edition.
During my MPhil, myself and two colleagues built UniCoin, a decentralized smart contract-based non-custodial research marketplace which allows researchers to benefit from commercially viable research.
Below are the links to the network visualizations that form a part of my MPhil in Financial Technology minor dissertation (placed here only for purposes of the digital longevity of the paper):
Network 1: The economic consequences of legal origins by La Porta, Lopez-de-Silanes, and Shleifer.
Network 2: Informality and development by La Porta and Shleifer.
Network 3: Extrapolation and bubbles by Barberis, Greenwood, Jin, and Shleifer.