Agentic AI is a new evolutionary stage of artificial intelligence that embodies systems that make decisions independently, pursue goals and adapt flexibly to new situations without being dependent on continuous human control. This technology offers enormous potential, particularly in the highly regulated banking sector. Particularly in terms of automation, securing highly complex IT landscapes that have grown historically and manage large volumes of sensitive data. But Agentic AI is also convincing when it comes to the personalization and individual design of financial products, loans or credits – as a virtual financial advisor that advises customers individually and in real time.
The digital transformation in the banking sector is progressing rapidly. Automation and the increasing use of AI in financial management are not only revolutionizing previous working models within banking institutions, they are also presenting the entire banking industry with completely new challenges: Modern budgeting and forecasting strategies for CFOs are enabling more precise and flexible financial planning. And banks are using new digital technologies to make their risk management and fraud prevention strategies – i.e. preventive measures aimed at stopping fraudulent activities before they cause damage – even more effective and targeted in the face of ever new cyber threats.
Financial institutions are therefore increasingly recognizing the opportunities offered by the use of agent-based AI. The application scenarios that are opening up are manifold: especially in lending and process optimization, those responsible rely on automated intelligence to improve quality, speed and compliance. These are some of the key findings of a survey in the banking sector conducted by our AI experts together with the market research institute Statista.
Value in the banking sector is rated highly …
Value-oriented processing of mass data has always been at the heart of the banking business. Agentic AI offers great potential to generate even more value from this data by enabling new efficiencies and unlocking untapped potential – and for banks that invest in agentic AI at an early stage, such an investment pays off – especially in automation and process optimization. For example, 72% of the banks surveyed see the greatest added value of Agentic AI in the automation of credit checks and approvals, closely followed by the optimization of internal processes, such as AI-supported document checks (66%). 62% of financial institutions are also convinced that the new evolutionary stage of artificial intelligence provides good services and effective support in the context of modern and effective prevention and defense against cyberattacks, fraud detection and transaction monitoring. More than half of the market players surveyed (52%) are certain that agentic AI provides valuable services in the context of complex market analyses and reliable forecasts in the banking sector, while one in four are of the opinion that AI agents can certainly also be used to provide individual and target group-oriented advice and design various financial products.
… but the implementation is time-consuming
As differentiated and promising as the application scenarios for Agentic AI in banking are, the time required for implementation is high. The survey paints a clear picture here. Seven out of ten respondents from the banking sector rate the time required for implementation as high or very high. The reasons for this include strict regulation and a strong focus on securing core systems – security has always been a key issue for banks. The path to successful implementation of agent-based AI in the banking sector therefore involves removing key hurdles – particularly in terms of data protection, technical infrastructure and regulatory clarity. And these tasks are associated with challenges. It is therefore not surprising that 66% of the banks surveyed expressed concerns about security and data protection, closely followed by 59% who believe that the regulatory requirements are unclear in some areas. Other challenges include technical hurdles (noted by 55%) and the lack of specialists and expertise, which was noted by just under half of respondents (48%).
Let’s be clear: Agentic AI certainly promises long-term efficiency gains, new scope for action and innovative customer experiences for banks and financial service providers. Those who invest in Agentic AI at an early stage will therefore secure competitive advantages in the future and can skilfully set themselves apart from their competitors – particularly in terms of automation and process optimization, but also through personalized customer service with intelligent chatbots and complex portfolio optimization. But getting there is challenging and resource-intensive.
Trusted providers support banks with know-how and implementation
The survey shows: Banks and financial institutions certainly recognize the potential of Agentic AI and are willing to invest – but the path to widespread adoption is sometimes fraught with hurdles. The most frequently cited challenges include security and data protection concerns as well as technical hurdles. The autonomous operation of Agentic AI – often without human intervention – raises questions about data security and compliance, especially for banks. At the same time, the connection to historically grown, less standardized and very complex IT landscapes, which are widespread in the banking sector, makes it difficult to integrate new AI technologies. However, clear scaling strategies, resilient models and organizational maturity are required for widespread use. Technology alone is not enough to fully exploit the potential of the new evolutionary stage of artificial intelligence: An understanding of the end-to-end processes, a willingness for consistent automation and a well-structured data basis on the part of the banks are also crucial.
Against this backdrop, it is usually essential and advisable for those responsible in the banks to seek external support, both technically and in terms of personnel. A reliable implementation partner not only has the necessary expert knowledge, but also ensures a smooth changeover and thus paves the way for the long-term success of Agentic AI. Especially in highly regulated or technologically complex areas such as those common in banking, Agentic AI often requires far-reaching adjustments – and correspondingly high levels of resources and expert knowledge.
