The use of AI and ML is growing rapidly as banks reassess their systems and integrate the technology to improve operational efficiency.
Automating routine tasks such as data entry, compliance checks, and report generation can lead to substantial time and cost savings. Furthermore, AI-powered systems can streamline processes such as loan approval and customer onboarding, reducing the time and effort required to complete these activities.
These technologies will also be integral in defining banking for the future which will be increasingly personalised to customer tastes anticipating their needs and providing tailor made solutions for them.
The ability of AI and ML to enable banks to offer highly personalised services to their customers has made them indispensable. By analysing customer data, these technologies can identify individual preferences and behaviours, allowing banks to tailor their products and services accordingly.
This personalisation can enhance customer loyalty and satisfaction, as well as open up new revenue streams for banks. Despite the numerous benefits, the integration of AI and ML in banking is not without challenges.
Issues such as data privacy, regulatory compliance, and the need for a skilled workforce to manage and maintain these technologies must be addressed.
By enhancing customer experience, improving fraud detection, optimising risk management, and increasing operational efficiency, these technologies can drive significant advancements in banking services.
-The writer is Pan-African head of trade and working capital digital propositions at Absa