At a time when financial inclusion remains a global challenge, SAS hosted an exclusive forum in Johannesburg to explore how artificial intelligence (AI) and data analytics can transform the banking sector and reach the underserved.

The event underscored the necessity of extensive AI governance and industry-wide collaboration to address the challenges posed by financial crimes and ensure ethical AI use across all applications.

The forum featured thought-provoking sessions from prominent guest speakers, including Paul Morley from Nedbank and Marli Dietrichsen from Capitec. Morley explored the evolution of digital banking, emphasising the transformational journey from automation to data-driven strategies, while Dietrichsen highlighted the importance of context-driven data approaches tailored to South Africa’s unique financial landscape. Their insights provided valuable perspectives that complemented SAS’s focus on leveraging AI and data analytics to drive innovation and inclusion in the financial services sector.

SAS experts Alex Kwiatkowski, Naeem Siddiqi, and Stephanie Ora took centre stage to share actionable insights on how AI is reshaping the financial services landscape.

Alex Kwiatkowski, Director of Global Financial Services Industry Marketing at SAS, highlighted the persistent issue of global financial exclusion: “Financial inclusion remains a pressing concern, with 1.5 billion people globally still unbanked. Despite progress, it’s troubling that so many remain excluded from basic financial services. Banking must be for everyone.”

Kwiatkowski also emphasised the importance of adapting to changing economic and environmental landscapes: “Banks must embrace multiculturalism and address trends like climate change and hybrid cloud strategies. These factors are critical for driving innovation and ensuring sustainable growth.”

Naeem Siddiqi, Global Advisory for Risk Management Practice at SAS, focused on how AI and alternative data are transforming credit risk management. He illustrated the potential of machine learning (ML) models to improve decision-making processes: “The integration of alternative data and machine learning enables better credit scoring models and promotes financial inclusion by enabling the scoring of unbanked and underbanked populations.

Banks that have invested in sustainable, integrated analytics infrastructure are best positioned to take advantage of the vast amounts of data and increased number of models this combination presents. Return on investment only happens when you can deploy your models quickly for decision making.”

Siddiqi also highlighted the role of climate risk modelling in enabling a more resilient financial system. “It’s not just about projections; it’s about actionable insights. Integrating climate risk factors into lending models and conducting scenario analysis and stress testing help institutions understand the impact of climate risk on their operations.” he explained.

Stephanie Ora, Global Lead for Financial Crimes Analytics at SAS, showcased innovative AI-driven solutions to address the growing threat of financial crimes. She pointed to the power of AI in streamlining investigative processes and improving outcomes: “AI has transformed the fight against financial crime through anomaly detection, behavioural modelling, and real-time decisioning. These tools help institutions proactively identify and mitigate risks throughout the customer lifecycle.”

Ora also discussed the role of synthetic data in training robust financial crime models while protecting sensitive information. “Synthetic data can overcome the challenge of insufficient data, enabling predictive modelling and network analytics,” she said. “However, the success of these models relies heavily on trustworthy AI frameworks supported by ethical practices and human oversight.”

Throughout the forum, a recurring theme was the importance of collaboration across the financial ecosystem. The speakers underscored the need for industry-wide cooperation to address challenges such as regulatory compliance, fraud prevention, and customer trust.

“To harness AI’s full potential, we must adopt robust governance frameworks that ensure fairness, transparency, and compliance,” said Kwiatkowski.

Attendees also explored collaborative strategies, such as federated learning models (a method of training AI models across decentralised data sources without sharing sensitive information), responsible data sharing, and enhanced governance frameworks, to foster financial inclusion and address risk more effectively.

The forum’s discussions reinforced the role of technology in fostering financial inclusion for underbanked South Africans. Federated AI models, offline credit decisioning, and customised risk scoring were highlighted as key solutions.

This SAS executive forum underscored the necessity of collaboration across the financial ecosystem to address pressing challenges. With AI and advanced analytics at the forefront, the banking industry is poised to drive innovation and inclusivity.

“AI will become an indispensable tool in helping banks not only survive but thrive in a digital world. However, the technology must be supplemented by human intelligence and guided by ethical principles,” concluded Kwiatkowski.

As financial institutions continue to navigate the challenges of a digital-first era, events like this forum serve as an important platform to discuss innovation, offering a roadmap to harness the power of AI for a more inclusive and resilient banking future.