Yesim Calidag, Director of Technology Strategy and Operational Excellence at Fibabanka
The momentum GenAI is gaining in 2022 and 2023 is exciting for us all and opens up new possibilities and opportunities across many industries. The difference between GenAI and base models is that while base models are pre-trained models for various tasks, generative AI can use base models to create original content from learned patterns. This gives us unique new capabilities, particularly in extracting insights, generating content and interacting in a human-like way. In almost every industry, especially sales and customer support, GenAI’s personalized conversation capabilities (automatically generating content, analyzing text, and summarizing interactions) will find a place. Companies that sell these technologies are currently trying to develop their own GenAI capabilities and integrate them into their own solution portfolios. Coding assistants are already being used in many organizations, whether in technology companies or in the field of software development in different industries. Improve code quality and simplify code writing with the power of Code Assistant. In fact, it seems possible to design an end-to-end software lifecycle starting from the creation of a development request. This can be exciting and perhaps a little unsettling, especially in the world of software developers.
Banking and Financial Industry
The banking and finance sector is one that uses technology very well and is often the first to adapt. I think we will soon see the first applications of GenAI in finance.
GenAI is expected to improve banks’ efficiency, especially in the areas of sales and software development. 
According to 2023 Gartner research, more than 60% of bank executives say their companies have increased investments in artificial intelligence or plan to do so in the next 12 months. GenAI is expected to improve banks’ efficiency, especially in the areas of sales and software development. According to a McKinsey study, approximately 70% of bank employees will be affected by a capability provided by GenAI. According to predictions, the most prominent capabilities will be in front-end consultants.
What are we doing?
As Fibabanka, we favor caution in usage, especially at points of contact with external customers, and start primarily with internal usage scenarios. As we develop our roadmap, we first establish a team to coordinate GenAI efforts within the organization to identify usage scenarios. As a first step, we provided information within the organization about GenAI’s capabilities and what it can do. We also received requests from internal customers to identify possible needs that could be addressed through GenAI. By assessing these needs, we prioritize scenarios and work towards solutions from different dimensions. For each scenario we prioritize and start with, we determine what the success criteria are and how to measure them. We begin by summarizing scenarios such as a customer’s conversation with a call center representative and providing advice to the call center representative during the conversation with the customer. In addition, we also develop friend systems for new employees and assistant bots related to HR and technology, which do not touch external customers at all, but we mainly need these systems within the organization. We have code assistants on our software team. Our hope is to work with code assistants who learn from our own code repositories and can write software that adheres to our architectural standards and supports different technologies. In the future, we aim to use GenAI in the customer acquisition process and generate personalized marketing content in sales.
What should the CIO do?
With developments happening at a rapid pace, CIOs need to understand the potential risks and business value that new GenAI-powered solutions will bring to their organizations. It is important to assess whether the organization can meet the technical requirements of the resulting solution and whether it is ready for the solution. However, a correct adaptation process is also required. Failure in the adaptation phase of a new technology may make subsequent processes more difficult. Therefore, users need to be informed, their expectations managed, and their adaptation ensured. As with any new technology, rumors of increased productivity may create unrealistic expectations in the short term.
Another issue to consider is data quality and security. Effective processes need to be in place to ensure that the data we use is accurate, secure and up-to-date. Every new technology also brings new security vulnerabilities. We now have to consider some security vulnerabilities that we hadn’t considered before. It seems inevitable that much of the technology investment in the coming period will be focused on security. In summary, organizations need to plan how to adapt this new technology to their existing systems in a way that provides the greatest added value. We have a long and enjoyable road ahead of us. We’ll be on this journey with our business partners and customers, and it looks like we’ll learn a lot along the way.
