The turning point has long been reached. Hardly any path bypasses Artificial Intelligence (AI) anymore. The initially only slightly noticeable pressure on companies and institutions to quickly explore and utilize application possibilities for their industry is steadily increasing. Opportunities must be seized, risks avoided. Banks, too, recognize the necessary change and are taking initial steps.
Artificial Intelligence: Part of the Future of Banking
According to a Confinpro AG survey conducted in collaboration with VÖB-Service GmbH, 65 percent of over 380 surveyed experts from German financial service providers are convinced that AI and banks are inextricably linked. In contrast, 87 percent predict a significant competitive disadvantage if organizations miss out on employing the latest technologies like Machine Learning.
For many banks, AI no longer sounds like distant future music. According to the survey, two-thirds of banks and insurance companies in Germany are already using AI solutions. This ranges from chatbots in banking applications, through which bank customers can contact, to process automation. However, managing the next stage of evolution alone is not seen as feasible by survey participants. 72 percent view technology partners as a pillar for further integration of AI applications, especially to overcome hurdles together.
Overcoming Obstacles
Banks face increased challenges, especially at the beginning. Shying away and postponing implementation given the general AI armament is not a sensible alternative. Rather, it helps to uncover initial difficulties and actively seek solutions. Typical stumbling blocks include:
- – Missing data or poor data quality
- – Low expertise regarding Artificial Intelligence
- – Uncertainties about regulatory requirements (including data protection)
- – Outdated IT infrastructure
- – Lack of target definition and unclear use cases
- – Inadequate involvement of all departments/employees
If banks are aware of their individual challenges and ideally look for solutions before the project begins, they keep the key success factors for AI projects in focus. With sufficient data, data quality, IT know-how, and knowledge of their own goals as well as applicable regulations, project success is within reach.
Opportunities Identified: AI Models for the Banking Sector
But in which direction can banks think? Given the diverse application possibilities of AI, it is crucial to assess which processes can be efficiently automated, where meaningful human-machine interaction is conceivable, and where employees must remain an indispensable contact point. Three scenarios illustrate benefits.
Improving Customer Service: The idea behind it is well-known. Those who know their customers can provide them with tailored recommendations. AI algorithms take up this point and generate suggestions for bank advisors regarding funds, stocks, or bonds for their customers. Additionally, portfolio risk assessment can be automated with AI to ensure security and achieve maximum customer satisfaction.
Reducing Financial Crime: Suspicious transactions can be uncovered using AI models. Applications analyze transactions based on various criteria such as amount, currency, destination country, and transaction type. If discrepancies arise, the AI reports these to a customer advisor, who can manually review the information again and forward it to the financial crime department if suspicion is apparent. Thus, AI helps in the fight against money laundering and more.
Supporting Sustainability Topics: The ability to quickly process large amounts of data also brings advantages in the sustainability sector. Banks, for example, will have to publish from 2023 which transactions are considered "green," based on EU classifications like loans for solar and wind energy. Banks need various new data from their corporate clients for this. What was previously manually checked can be quickly and efficiently automated with AI in the future.
Future-Proof – with AI
Whether in customer service, combating financial crime, fulfilling sustainability obligations, or simply optimizing internal processes, AI already finds diverse applications in banking. Since the future holds further points of connection and thus alleviations and opportunities, it is now up to all responsible to stay vigilant with AI and seize potential early.
Are you curious about additional AI application possibilities in money management?