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The Growing Role of Generative AI in Business and Banking

TECHNOLOGYThe Growing Role of Generative AI in Business and Banking

The role of generative AI in business is growing: 43% of enterprises worldwide, including those in Poland, are already investing in this technology, with another 30% planning to do so within the next year, according to the EY report “Reimagining Industry Futures Study 2024.” One of the sectors seeing the greatest potential in GenAI is finance. Banks are eagerly investing in this technology, hoping for increased sales, improved processes, and better personalization of products and services. However, GenAI also brings challenges related to data confidentiality and integrity.

“A few years ago, we talked about artificial intelligence; today, we talk about generative artificial intelligence, which relies on large language models (LLMs). These models understand human input, even unstructured statements, and can provide precise responses without human intervention. This is the difference between tools based on algorithms and machine learning and today’s solutions that understand and respond in a language comprehensible to everyone,” says Przemysław Koch, a member of the management board of VeloBank responsible for IT and operations, to Newseria Biznes.

Generative AI has firmly established itself in the banking sector. According to a study by consulting firm EY (“Generative AI in Banking”), 45% of financial institutions globally are already investing in GenAI solutions, with 52% planning to do so. Leading the way are the largest banks, with over 80% of them having dedicated teams for exploring and implementing this technology. A recent Mastercard Signals report (“Generative AI: The transformation of banking”) highlights its vast potential in improving bank operations, from data processing efficiency and employee task facilitation to providing more personalized customer experiences and services.

“Banks offer tailored solutions based on customers’ preferences, data, and finances. Technology, including GenAI, can prepare personalized products for individuals, perfectly timed and suited to their situations. For example, if a customer is on a highway and needs to buy a toll ticket, we can immediately offer a push notification, enabling them to proceed with a single tap on their smartphone. This is the added value technology provides – bespoke services delivered exactly when needed,” explains Przemysław Koch.

The EY study reveals that banks and financial institutions are motivated to adopt GenAI primarily to increase productivity (78%), improve customer experiences (60%), reduce costs (59%), and stand out from the competition (51%). Most (66%) also believe that generative AI will significantly enhance the efficiency of banking advisors by automating the creation of dedicated sales prospectuses. However, only 13% foresee a potential decrease in human interactions.

“Generative AI is a powerful tool for building organizational value,” says the board member for operations and IT at VeloBank. “It’s crucial to implement this technology correctly, selecting applications that create a competitive advantage and improve organizational efficiency by automating tasks currently performed by employees.”

Banks are currently most enthusiastic about implementing AI tools for marketing and sales support, improving chatbots (many customers currently try to bypass chat systems to reach an advisor, but AI tools may change this), and supporting anti-money laundering (AML) policies. Over half of the financial institutions surveyed by EY already use AI for predictive analytics and real-time fraud detection.

“Cybersecurity is a vast and crucial topic for banks as we must ensure the safety of the entire financial sector and each customer’s funds. We use GenAI to detect attempts at identity theft or financial fraud. At VeloBank, we have introduced behavioral biometrics, which builds an individual banking profile for each customer. This profile includes the way and angle they hold their smartphone, typing speed, and mouse movements. If we detect actions that do not match a customer’s profile, we block them and verify with the customer to prevent fraud,” says Przemysław Koch.

According to the Mastercard Signals report, potential GenAI applications in banking over the next five to seven years include talent management and employee onboarding, wealth advisory, and loan processing (AI can significantly reduce loan application processing time and costs), loyalty program management, real-time communication with participants, and ongoing analysis of social media trends to deepen consumer interactions.

On the other hand, generative AI poses challenges related to data confidentiality and integrity. Therefore, banks and financial institutions are adopting a conservative approach. Initial implementations are mainly internal, supporting management systems and conducting analyses.

Experts emphasize that the effectiveness of AI solutions depends on the quality of the data provided, making data security crucial. Currently, only 63% of banks feel adequately prepared in terms of technology, security standards, and human resources for implementing GenAI tools. Concerns about data security and privacy are the top barriers to this technology. Consequently, banks are cautious with GenAI deployment: only 27% introduced it in 2023, 64% plan to do so in 2024, and 9% will wait until 2025 (EY study).

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