The banking industry has been around for more than a century, and in that time, the way it processes information has changed dramatically. Data and access to existing knowledge have become increasingly important to many banks. By effectively managing available data, banks can gain insight into customer behavior, identify risks, and personalize services, leading to improved customer satisfaction and retention. Knowledge management also enables the organization to leverage institutional knowledge, fostering innovation and maintaining a competitive edge in a rapidly evolving financial landscape. Generative AI takes knowledge management to a new level.
According to recent research, the banking industry’s spending on Generative AI is expected to reach nearly $85 billion by 2030, as institutions look for ways in which this transformative technology could deliver unprecedented value. One of the areas where this value is likely to be realized is in the use of available data and effective knowledge management – with potential benefits in terms of speed, accuracy and scale, Generative AI could be the next revolution in banking.
How banks are leveraging data and available knowledge
Although Generative AI is frequently discussed in mainstream business circles, many of today’s solutions remain theoretical or at the proof-of-concept stage. At Eraneos, on the other hand, we’ve already successfully put several solutions into production for a variety of financial services organizations. But where will most of the value come from?
The Gartner 2024 Hype Cycle for Generative AI outlines exactly how important it is already to banking executives, with industry leaders planning to allocate an average of 6.5% of their 2024 budgets to the technology. They are likely to allocate this budget to several focus areas, with the expectation that Generative AI will enable greater productivity, enhance existing technological capabilities, and accelerate innovation more broadly.
Many of the benefits banks are already reaping from Generative AI can be applied to their data- and knowledge-intensive processes, from sales and marketing to compliance and risk management. Knowledge management has long played an important role in the banking industry, allowing them to store and organize the information needed for employees to collaborate effectively, achieve goals, and deliver positive customer experiences.
Generative AI is proving to be beneficial in several areas of the industry. Here are five key use cases we have identified where banks expect to see the most tangible results in the short term:
- AI-driven internal knowledge retrieval: Bank employees often need to search through vast amounts of internal documentation, regulatory updates, and policy changes. Manually sifting though this data is time-consuming, prone to human error, and may result in outdated or incomplete information being used in critical decision-making processes. GenAI-powered tools can help employees query internal knowledge bases, regulatory documents and other internal content to retrieve precise, context-aware information in real time.
- Automating information input: Typically, employees in financial institutions spend a great deal of time manually filling out customer information. Of course, this information is essential to the bank-customer relationship, but the process of compiling information can be a significant burden on staff and prevent relationship managers from spending time with their customers. This is where Generative AI can provide a significant productivity and cost boost for institutions, with studies showing that automation can reduce the cost of manual data entry by as much as 70%. Specific use cases include automated data migration and LLM-based creation of meeting minutes in the CRM system. At Eraneos, we have recently completed a similar project at a large insurance company, using a GenAI tool we developed specifically for their needs. You can learn more about that project here.
- Ensuring compliance: Rules and regulations in the banking industry are understandably stringent due to the sensitive nature of the personal and financial data that institutions manage. While many financial services firms have already deployed rule-based automation and machine learning algorithms in compliance processes, Generative AI offers a more advanced solution by systematically incorporating unstructured data. This capability is particularly impactful in areas such as anti-money laundering (AML), know your customer (KYC), fraud detection and regulatory reporting, where traditional methods often struggle to cope with the complexity and volume of unstructured information. Concrete examples include the use of a GenAI-powered system to automatically generate regulatory reports by extracting and structuring data from various internal systems, and the use of GenAI to analyze large volumes of text and identify the key points relevant to the bank’s compliance obligations.
- Leveraging insights for more personalized client interaction: Banks must incorporate vast amounts of data into their knowledge management processes, with information coming from credit cards, transaction records, in-person branch visits, call logs, and a variety of other sources. Generating insights from this pool of data can be challenging and time-consuming for banks. However, Generative AI can significantly speed up the process of finding correlations, patterns, and trends within an institution’s data, providing a more holistic view of research and insights. This can be helpful for relationship managers who often face a knowledge gap when clients come to meetings or calls with up-to-date information on market events. When the client mentions a specific event – such as “I read that Company X just had a poor quarterly earnings report” – a real-time contextual assistant can help bridging this gap.
- Streamlining working with third parties: Banking is no longer a solo endeavor, and partnerships are becoming increasingly common in the financial sector. A study by Cornerstone Advisors in 2023 found that 70% of banks said partnerships were important to their business strategies, up from nearly two-thirds in 2022. While collaboration can help banks innovate beyond their core processes, connecting with other lenders can mean grappling with different solutions, methods, and ways of communicating. Generative AI can help streamline workflows and improve interactions, strengthening everything from onboarding to ongoing relationships with external partners.
Take the next steps in your GenAI Journey
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The next revolution in banking’s knowledge management
The banking industry is innovating by using Generative AI in a variety of ways, from Customer service to Risk assessment. Other industries are showing similar ambition, with sectors from Transportation to Healthcare and Life Sciences all exploring how they can use Generative AI to secure benefits in terms of efficiency, productivity, and more.
When it comes to knowledge management, banks are beginning to realize that Generative AI can facilitate digitization, automation, and collaboration. However, there are challenges to using Generative AI for knowledge management in this sector. Compliance and regulatory requirements remain stringent, and institutions still need access to the right technical skills to get the most out of this technology.
Some organizations talk about the potential of Generative AI. We go much further. At Eraneos, banks choose to partner with us because we are already delivering results with the technology, building solutions and delivering value – not just talking about prototypes or proofs of concept. In addition, we have more than 250 experts across Europe who can build these solutions and have been in the data and AI industry for decades. We don’t just talk about Generative AI. We walk the walk. Document management may be as old as banking itself, but it has changed significantly in recent years. Generative AI can be the next step in a bank’s knowledge management journey, enabling innovation without compromising compliance.
At Eraneos, we are ready to accompany you on this AI journey – every step of the way. Check out what a GenAI Knowledge Management offering can do for your organization here.
