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Redefining Digital Banking: How Generative AI is Shaping the Future

The landscape of Artificial Intelligence in banking is undergoing a significant transformation. Traditional AI, primarily based on predictive systems, is giving way to a new paradigm embodied by Generative AI. While traditional AI tools were designed to forecast future trends, produce patterns, and develop highly accurate predictions, Generative AI shifts the focus from analytical tasks to creative applications of technology.


Our C-Innovation specialist, Charlotte Ford, discussed in one of her recent C-Innovation podcasts, explaining how "traditional AI was the master of efficiency, GenAI is the maestro of creativity", opening new avenues for the relationship between users and their assets, and consequently, between users and banks.


In this blog, we will examine some interesting points regarding the application and impact of AI systems by digital banks, marking a decisive turning point in what can be defined as a transition process from digital banking to AI banking. Specifically, we will address the following points:


1.     From Predictive AI to Generative AI in the Digital Banking

2.     The Impact and Spread of Generative AI in Neobanks and Digital Banks

3.     Generative AI Cuts Marketing Spend by 37%, Saving Klarna $10 Million Annually

4.     Synergies Unveiled: Some More Examples of Gen AI in Digital Banking

5.     The Road Ahead


From Predictive AI to Generative AI in the Digital Banking


Why do we talk about the shift from digital banking to AI banking? The growing competition in the digital banking sector, evidenced by high growth rates and year-over-year profit/loss variations of digital banks, and the constant emergence and market entry of new neobanks have highlighted the importance of customer retention, raising the bar for products and services offered, and doing so more cheaply than before. With GenAI, many creative and interactional processes can be carried out with minimal human support, significantly impacting the corporate structure in different ways and extents: sales, marketing, R&D, compliance. The direction towards AI implementation seems almost obligatory, offering a level of cost savings and increased efficiency already measured by significant empirical results from digital banks. While past banking trends focused more on products (online banking, online reporting, fund managers, integrated services), Generative AI is ready to revolutionize the process, threatening to penalize those who resist this new revolution.


The Impact and Spread of Generative AI in Neobanks and Digital Banks


AI in banking shifts from predictive to generative, revolutionizing digital banks. Discover its impact, cost-saving benefits, and future prospects.

Several players have already adopted or are adopting solutions that involve intensive use of GenAI technologies. 


The slide above shows the partnerships and the progress status of some digital banks regarding the development or adoption of GenAI solutions, with initial data from the inaugural episode of the C-Innovation podcast released in February 2024. The same slide has been updated with information from official documents and news in the following three months, showing continuous advancements in a short time.


Regarding boosting the productivity, Ally is expanding its generative AI strategy as it prepares to adopt Amazon Bedrock, a machine learning platform for building GenAI applications, while Chime will incorporate FairPlay's Fairness-as-a-Service solutions to further its mission of "helping everyday Americans unlock financial progress".


On the consumer side, Bunq has continued to enhance its in-house AI assistant, releasing the “0.2 version” of Finn, the AI chatbot that now boasts enhanced conversational abilities. Bunq states that the chatbot leverages generative AI, providing users with answers to questions about their financial life, such as spending habits and frequent restaurants. Regarding PayPal, rumors suggest a possible collaboration with Tools for Humanity following innovations introduced in tandem with its subsidiary Venmo.


Generative AI Cuts Marketing Spend by 37%, Saving Klarna $10 Million Annually


Particularly interesting (and recent) is the case of Klarna. Founded in 2005, Klarna revolutionized online shopping with its "buy now, pay later" service, quickly gaining traction in Sweden and the Nordic countries. In 2011, it secured $155 million in funding from investors like Sequoia Capital, fueling its expansion across Europe. Obtaining a full banking license in 2017 allowed Klarna to offer a broader range of financial services, including savings accounts and personal loans. In 2021, Klarna emerged as one of Europe's most valuable private tech companies, with $80 billion in online sales transactions and a valuation close to $45.6 billion. After facing a significant drop in its value to around $6 billion in 2021, Klarna is now focusing on reassessment and diversification efforts. To learn more about Klarna's journey and its plans for expansion, check out our latest article "Klarna's Resilient Evolution: Banking Expansion and AI Innovation Set the Stage for Future Growth."


AI in banking shifts from predictive to generative, revolutionizing digital banks. Discover its impact, cost-saving benefits, and future prospects.

Source: Klarna Investor Deck. 28 February 2024.


In recent years, Klarna has heavily invested in AI to enhance its services and customer experience. By integrating AI-driven credit scoring and fraud prevention systems, Klarna has increased the accuracy and efficiency of its operations. However, the most significant innovation involves the recent developments in Generative AI within the company. As reported on their official site, Klarna “has cut its sales and marketing spend by 11% in Q1 2024 while increasing the number of campaigns and updating marketing collateral more frequently. AI is responsible for 37% of the cost savings, or about $10 million on an annualized basis.” The creation of images alone contributed to saving a total of $6 million, reducing the image development cycle from the initial six weeks to just seven days. Additionally, Klarna has publicly acknowledged using AI-powered copywriting tools and integrating over 300 ChatGPT models for internal use, following direct partnerships with OpenAI, thus reporting significant monetary savings and streamlined processes.


AI in banking shifts from predictive to generative, revolutionizing digital banks. Discover its impact, cost-saving benefits, and future prospects.

Source: Klarna Investor Deck. 28 February 2024.


Synergies Unveiled: Some More Examples of Gen AI in Digital Banking


Many other players in the neo-digital banking sector are advancing a series of initiatives to make Generative AI an effective tool for reducing costs, increasing productivity, and notably enhancing consumer experience.


Dave, a prominent U.S. neobank and fintech innovator highlighted in one of our recent blogs, has strategically leveraged AI technology to bolster its lending and credit capabilities. Its platform, CashAI, uses bank account transaction data to assess risk, allowing Dave to detect changes in income, spending, savings, and employment in near real-time. This sophisticated use of AI enables more accurate risk assessment and offers customers a more responsive and tailored banking experience.  Dave also launched DaveGPT, a generative AI assistant powered by Aisera's technology. This GenAI-based solution provides self-service customer inquiry resolution for Dave's 9.9 million members, enhancing overall customer service experience.


Lunar, a Danish success story in the neo banking sector, has also made significant strides in integrating AI technology. One of the notable milestones in its journey was the beta launch of Lunar's AI Co-pilot. This innovative tool is designed to help customers better understand their financial status and achieve their financial goals, all within a compliant framework.


AI in banking shifts from predictive to generative, revolutionizing digital banks. Discover its impact, cost-saving benefits, and future prospects.

In this whirlwind of exploration and innovation, even traditional banks and long-standing financial institutions are implementing or investing in products based on Generative AI technology, internally as well: financial giants like JP Morgan and Bank of America have filed hundreds of patents mentioning AI since 2021, demonstrating a real and spread interest in the technology.


AI in banking shifts from predictive to generative, revolutionizing digital banks. Discover its impact, cost-saving benefits, and future prospects.

Our research showcases several key trends in AI adoption across the banking sector:


  1. Boosting Productivity: Banks are utilizing AI to enhance efficiency and streamline workflows. For instance, BNY Mellon partners with Azure and Conquest to provide advanced data analytics capabilities for financial advisors, while Deutsche Bank uses NVIDIA's AI for improved risk management.

  2. Edge with Unique Insights: Financial institutions are leveraging AI to gain deeper insights from complex data. Deutsche Bank, for example, utilizes NVIDIA's technology to extract valuable insights from unstructured data, and JP Morgan employs OpenAI to detect trading signals from Federal Reserve statements.

  3. Personalized Customer Experience: AI is transforming customer interactions by offering personalized services. Brex and Klarna use OpenAI for real-time business spending insights and personalized shopping recommendations, respectively. Morgan Stanley explores AI for customized financial advice, enhancing client engagement. Openbank by Santander employs in-house AI, integrated with Azure, to develop an investment model that aids customers in making informed investment decisions. The model provides price targets for over 1,000 shares listed on the STOXX Europe 600 and S&P 500, offering predictions for future prices looking 1, 3, 6, and 12 months ahead.

  4. Streamlined Backend Development: AI is also being adopted to optimize backend processes. Nationwide, in partnership with Hazy, creates synthetic data to securely share with third parties, while TD Bank pilots GitHub Copilot to accelerate coding workflows, demonstrating a blend of internal development and external collaboration.


These examples highlight the widespread and strategic use of AI in the banking sector, focusing on productivity, insights, customer experience, and backend efficiency. This commitment to AI integration signifies a transformative shift, positioning banks to better meet the evolving needs of their customers and maintain a competitive edge in the market.


The Road Ahead


We've observed how digital and neobanks are making substantial investments in technology and leveraging the benefits of Generative AI. Some players, like Ally and Chime, have focused on enhancing productivity in their analytical and decision-making processes. Others, such as Bunq and Klarna, have leveraged GenAI to improve customer experiences and reduce operational costs.


Regardless of the specific business area being integrated with GenAI, neobanks and digital banks are steering towards a significant shift in their very essence, opting for an almost hybrid model, where AI assumes increasingly prominent roles and importance, with implications also for those who decide not to ride this technological wave today. While it's true that the agility of digital banks is demonstrated by how quickly they adopt new innovations, it's traditional banks that are now significantly investing the majority of funding directly into the development of GenAI-based products.


In 2023, global digital banking secured $3.8 billion, while generative AI led with a significant $20.7 billion investment (Complete article here). This means that today, it's six times more compelling to invest in the development of GenAI solutions than directly in internal processes and products within digital banks. Certainly, it will be interesting to observe the global scenario to determine the extent to which the mentioned hybrid model will endure, moving instead towards increased AI management and reduced human involvement, mirroring Klarna's trajectory.


Apart from that, the lack of comprehensive regulation and a fragmented labor market make it challenging to predict the full extent of this technology's implementation. This is particularly true when considering the potential impact on the current workforce and data protection issues. Just recently, the European Securities and Markets Authority (ESMA) issued a warning to banks and investment firms in the EU regarding the use of artificial intelligence, emphasizing the legal obligations to protect customers.


By staying informed and proactive, banks can leverage the full potential of Generative AI while mitigating risks and navigating the challenges ahead.



At C- innovation we will continue following closely the innovations in the AI domain for Digital Banks, so stay tuned!


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