This appointment comes in line with SAS’s strategy towards investing in growing the organisation in South Africa driven by the market needs for advanced analytics, AI and cloud-based solutions.

Essie Mokgonyana brings 15+ years of experience in technical roles within the IT industry, with a strong focus on sales and business development, working with clients in Public Sector as well as Telecommunications and Banking sectors.

Additionally, having served as an executive, non-executive and Trustee board member before, Essie has a strong working knowledge of mapping local business governance practices to be in line with those of the multinational business and the state rules of the country.

Commenting on the appointment, Zafir Junaid, Regional Director, Africa & Emerging Middle East, said: “We are very proud and excited to welcome Essie to the SAS family! Essie is an admirable professional and, with her dedication towards delivering results and developing the teams she manages, it is not surprising that Essie has excelled in her career path. Essie’s background in the IT industry and experience across multiple sectors aligns well with our strategy in South Africa and Africa as a high growth market.”

“I am delighted to join SAS – and at such a transformational time. Never before have we experienced such rapid rates of digital transformation in all tiers of society – from government to business and industry, and consumers. And Africa is no exception when it comes to witnessing the potential of digital transformation, particularly during the past 2+ years. I am looking forward to working with our teams, partners and clients to realise the enormous potential we still have to further transform both public and private organisations through adoption of our advanced analytics, AI and cloud-based solutions,” says Essie Mokgonyana, SAS Country Manager & Sales Director for South Africa.

SAS will continue to help public and private organisations across Africa adopt cloud platforms to tap into the full potential of their analytic capabilities and resources to accelerate innovation and higher operational efficiencies.

The cloud-first strategy spearheaded by SAS supports organisations in moving to a cloud-driven environment to eliminate physical and financial barriers to align with evolving business goals and advance in their digital transformation journey. Because the SAS portfolio is both cloud-first and cloud-agnostic, or cloud-portable, customers can accelerate their move to the cloud and expand their use of analytics, machine learning and AI.

SAS analytics in the cloud provides customers with a distinct advantage to analyse intense data in the cloud, whether they’re using SAS Viya or an industry solution.

Essie Mokgonyana is confident that SAS is moving into a new phase of growth locally. “The news that the SAS Institute South Africa achieved Level 1 BBBEE status reaffirmed our commitment as an organisation to the local business and economy, and solidified SAS’ position as a preferred partner to our clients and partners. Over and above our focus and commitment to client, SAS is dedicated to accelerating its work of empowering talent across the region and playing its part in developing ICT skills. Additionally, SAS is also committed to using analytics to build a sustainable future in Africa.”

In Africa, achieving sustainability cannot be separated from social and economic issues. As more African nations evaluate and start to formulate their “net zero economy” aspirations, Environment, Social and Governance (ESG) principles have come under the spotlight in every sphere of government, business and society.

In support of this, SAS will continue to bolster the way it uses technology and expertise to help governments and businesses in the region amplify their ESG initiatives and contribute towards realising their ambitions.

With governments and businesses seeking innovative ways of navigating paradigm shifts in local economies brought by climate risks, SAS will lead the roadmap to discover new opportunities, become future-proof and overcome challenges in education, finance, healthcare, energy, agriculture, government, telecommunications and retail sectors using Analytics and AI.

In doing so, the perfect climate has been created for fraud to become even more of a challenge.

A global economic crime survey has found that one in three South African respondents cite distrust as being the most significant emotional impact of fraud.

Brand damage, loss of market position, employee morale, and lost future opportunities remain unquantified. Consideration must also be paid to the availability of more sophisticated technologies such as artificial intelligence (AI), machine learning (ML), and automation that benefit organisations and criminals alike.

Technology shifts

Our recent research indicated that the pressure to safeguard against financial crime s in this connected landscape has resulted in a third of financial institutions accelerating their AI and ML adoption for anti-money laundering (AML) technology.

In the same survey, 28% of large financial institutions consider themselves to be fast adopters of AI technology while 16% of smaller financial institutions also view themselves as industry leaders in AI adoption.

The shift in consumer behaviour due to the pandemic has forced many financial institutions to move away from static, rules-based monitoring strategies as they are not accurate or adaptive to the behavioural decisioning systems required in an AI-driven landscape.

Additionally, our insurance fraud technology study has found that anti-fraud technology is flourishing due to these and other factors.

Automated red flags, predictive modelling, text mining, and reporting capability are among insurers’ most used anti-fraud technologies. They are also embracing photo analysis technology to authenticate claim damage, identify digitally altered images, and index pictures submitted in other claims.

Tying this together is how organisations are embracing financial intelligence that unite multiple information sources with analytics connecting the dots at scale to form a true, all-source-intelligence platform. For instance, sophisticated algorithms have been deployed not only to link data, but to identify the significance of a contact and predict risk of infection from malware.

Financial crime variety

Fraud and cyberattacks are just two concerns. But money laundering has become especially pervasive recently with criminals relying on legitimate businesses through which to channel their ‘dirty’ money. This is where shell companies and offshore financial transactions become part of the picture.

And then there is procurement fraud to consider with some suggesting it has become one of the most common economic crimes around the world. Because it takes so many forms, procurement fraud is very difficult to detect and investigate. Manual detection is futile with organisations requiring the right combination of advanced analytic techniques to bolster their defences against these fraudsters.

Fundamentally, today’s payment ecosystem has broadened well beyond traditional banks. Fintechs, digital banks, and payment service providers are driving new, alternative payment services.

Payments have become increasingly cashless and opened doors for new, faster payment types. But, with all the innovation comes new fraud threats – and they are emerging on different timelines in various parts of the world.

AI weaponry

For these, and other financial crime s, it has become imperative to embrace continuous monitoring solutions. These can pull millions of records from back-office systems, including purchase orders, purchase requests, invoices, payments and other accounts payable data, and supplier data.

After extracting the data, the solutions apply AI to cleanse it at scale.

The system can enhance the data by drawing on external sources, such as company registers, information about politically exposed people and transparency indexes.

Then it processes the data using alert generation processes based on mathematical algorithms and models, such as clustering and link analysis. The outcome is a real-time risk score for both transactions and vendors.

Depending on the industry and the company needs, businesses can use analytics to check for bid rigging, duplicate invoices, travel expenses, returns, fidelity cards, subscriptions, and more.

It all comes down to embracing tools like AI and ML to enhance what human experts do. Fighting financial crime is a never-ending battle. With criminals using evolving technology to bypass organisational defences, it is up to the companies to fight fire with fire.