Given the ongoing economic challenges, regulatory uncertainty, and increasingly rapid technological advances, what does 2025 have in store for the banking industry? Olaf Passchier (Benelux Lead for Fraud, Compliance and Public Security at SAS) shares his insights on key trends and changes in AI, data management, ESG, and other relevant topics.
Social, economic and technological developments have created an environment where fraud has become easier and more common than ever. Generative AI (GenAI), in particular, plays a crucial role in this by giving fraudsters access to sophisticated tools, such as deepfake videos and voice cloning technology.
These technologies allow them to credibly impersonate trusted individuals within an organization, significantly increasing the risk of abuse. AI chatbots are also on the rise and are increasingly being used to generate phishing messages that can mislead even the most alert employees. This leads to significant security risks and can cause serious damage to the reputation of organizations.
The key to tackling fraud lies not in avoiding technology, but rather in applying it intelligently. This requires reliable data, but also good cooperation between different parties such as companies, regulators and individuals. They must continue to act jointly and proactively to combat digital fraud as effectively as possible.
GenAI is both a curse and a blessing as it is used by fraudsters and fraudsters alike. While fraudsters are using GenAI to create increasingly difficult to detect voice and video fraud, reliability testing is playing an increasing role in banks' digital multifactor ID verification processes.
Although forms of verification and detection have existed for decades, by 2025, fraud fighters will increasingly use the latest anti-fraud technologies, including advanced authentication recognition based on AI.
"While companies and government agencies continue to innovate with apps and digital services to meet insatiable consumer demand, criminals are using increasingly sophisticated tools to detect and exploit vulnerabilities," explains Olaf Passchier (Benelux Lead for Fraud, Compliance and Public Security at SAS) explains.
"By building a robust data architecture, leveraging this data effectively and applying AI, organizations can adapt flexibly to rapidly changing threats," said Passchier
Banks can benefit from the vast amounts of data, or be overwhelmed by it.
Big Data has the potential to become the key success factor, or the biggest obstacle, for the global banking industry. The rapid increase in data, amplified by the accelerated adoption of AI, presents both opportunities and challenges.
Whether the vast amounts of structured and unstructured data represent an advantage or a risk depends largely on banks' ability to effectively develop and apply their data architecture and governance. By investing in a unified decision-making platform, banks can break through data silos and gain valuable, cross-functional insights that drive strategy and transformation.
For years, companies have operated with siloed systems that each served a specific function or customer segment. IT teams were overburdened by complex integrations and unable to provide the flexibility needed for business growth.
A major IT rationalization is ahead, where business leaders will leverage the cloud to streamline their IT infrastructure, simplify vendor relationships, increase speed and reduce costs.
Companies that modernize with an AI platform that supports multiple functions will generate the most value. This enables them to achieve an integrated data and decision-making process that spans both the entire customer and organizational lifecycle.
With continued market volatility in 2025, banks continue to invest in risk management. AI, including GenAI, plays a key role in Asset and Liability Management (ALM) by analyzing changing conditions faster and better predicting interest rate, liquidity and climate-related risks.
Modernization of risk systems and integration of cloud technology are becoming essential to provide a holistic view of balance sheet risks. The combination of AI and human expertise improves financial planning, operational efficiency and decision-making.
The industry is struggling to find a balance between the demand for AI and the power consumption this technology requires. As the need for speed, automation and productivity increases, AI needs powerful GPUs to handle the higher levels of processing.
Banks and other companies find themselves in a paradox: they consume more and more energy, while at the same time they are under pressure to improve their sustainability policies and implement ESG measures. Mandatory sustainability reporting under IFRS S1 and S2 will further strengthen the focus on energy consumption as a major cause of climate change.
In addition, a new major energy consumer is emerging: Quantum computing is expected to bring a significant increase in energy requirements. But without the development of renewable energy sources to support all these processes, the industry risks having to limit innovations to both comply with environmental regulations and maintain consumer confidence.
Banks' interest and investment in ESG initiatives will decline as they struggle to extract tangible value from ESG initiatives. Declining investor enthusiasm and concerns about "greenwashing" will weaken the importance of ESG in financial markets.
Without clear financial benefits, banks will see ESG as a cost rather than a revenue source, and it will be seen primarily as reputation protection, rather than a strategic growth factor-unless regulations mandate it or consumers demand it.
2025 promises to be an important year for AI in the banking industry. But AI's influence doesn't stop there. For predictions on trends in insurance, marketing, government and ethical AI, visit the AI 2025 predictions hub.
