By Jens-Peter Jensen
The banking sector is set for a tidal wave of innovation as the adoption of a broad range of artificial intelligence (AI) solutions accelerates in the years ahead, supported by the growing power and scalability of the cloud.
The strategic use of AI is nothing new to the banking sector. Due to the data, processes and tech-intensive operations typical of the industry, banks have leveraged AI and machine learning to improve data classification and process automation, as well as uncover hidden patterns and predicting events, which is particularly useful in governance and compliance efforts.
The global banking, finance and insurance accounts for an 18% market share in the use of machine learning globally, second only to the ICT sector. This adoption is only set to grow as Generative AI is deployed to a broad range of use cases.
The new wave of generative AI promises new advances in employee productivity, system efficiencies, and innovation. The impacts of this innovation will likely be seen in critical areas including greater differentiation, improved financial performance, and enhanced risk management capabilities.
For banks, continued success and growth may depend on how effectively they leverage the power of business AI and the scalability of the cloud to power innovation.
One of the highest-value areas of AI-powered banking innovation is in improved strategic decision-making, especially at a CFO level.
In a banking and financial services context, the strategic role of the CFO is critical to the company's performance and its ability to both identify and adapt to emerging risks and opportunities.
To fulfil this strategic role, CFOs need access to accurate, real-time information about the performance of the business at every level of granularity, enabled by powerful modern data management technologies. However, this level of real-time insights has not been available to CFOs at the speed at which the business moves, affecting strategic decision-making.