Michael O’Carroll (Head: Data Transformation at Capitec)
Generative Artificial Intelligence (GenAI) has quickly emerged as a powerful productivity and insights tool. It can change how banks operate and serve clients, and companies worldwide are grappling with how it will impact our work.
We acknowledge these challenges and are committed to exploring how we can use this technology to augment our work rather than replace people.
We regularly evaluate GenAI applications to understand their benefits and risks. We keep exploring how they can help with productivity, data insights, summarising text, code optimisation, and subject matter research.
Our GenAI journey started by updating our internal operating processes and standards - we gave clear guidelines for employees to follow when using Large Language Models (LLMs).
GenAI features are accessible in tools that our teams use every day. For example, some teams use Microsoft’s Copilot in M365 apps.
Copilot combines LLMs with the bank’s data, giving employees access to a virtual AI assistant and analyst. Copilot is integrated with familiar work tools, from Microsoft Word to PowerPoint, using everyday language prompts or inputs and governed by the bank’s security, compliance, and privacy policies and processes.
Beyond core operating applications on M365 apps, we use Copilot in Power BI. Our developers are also empowered to increase their productivity and pace of software development with access to GitHub Copilot autocomplete-style code suggestions as they code. These AI tools make our teams more effective and inspire a new way of thinking, with people continually finding new use cases for GenAI.
AI assistants are there to support and enhance rather than replace humans. A human in the loop will always be necessary to safeguard against inaccurate data that could result in poor decisions and adverse outcomes for us and our clients.
Human involvement ensures that the output from the AI aligns with the bank’s standards and policies. AI tools should be used responsibly, with due consideration for ethical implications and potential discrimination against certain groups.
Education and awareness are critical for this GenAI transformation across the bank. Everyone from executives to developers must learn about new tool features and understand the limits and risks of relying on GenAI outputs.
Using GenAI in banking is about more than just using new technology. It’s also about making significant changes in the bank’s work and ensuring everyone is on board. Banks have a chance to use GenAI to improve client and employee experiences and, in the end, generate greater shareholder value.
