Beyza Karakoy is an analyst in GlobalData’s Thematic Intelligence team. Her expertise lies in the financial services industry and in themes including cybersecurity, AI, metaverse, cloud, robotics, and regulation.
Lara Virrey: What are the most exciting developments in AI for the banking and payments industry today?
Beyza Karakoy: AI offers many use cases in the banking and payments industry making developments in the technology exciting. Conversational platforms have been an important development in AI for banks, as with the shift to digital banking, more customers demand round-the-clock support. Banks are also using AI-powered chatbots and virtual assistants to offer personalised customer support.
Using machine learning, chatbots can continuously improve their responses to customer inquiries and tailor interactions based on individual customer preferences. This ultimately helps them to improve their customer relationships while streamlining their operations.
The development of computer vision is another area of AI that has benefited the banking and payments industry. Identity management tools that incorporate computer vision technology can enhance robust preventative cybersecurity for banks.
Most recently, Generative AI has been an exciting development for the banking and payments industry. The launch of ChatGPT in November 2022 sparked renewed interest in AI and today generative AI is the fastest-growing AI technology.
Lara Virrey: How can companies in the banking and payments sector benefit from advances in generative AI in particular?
Beyza Karakoy: Generative AI has many applications in the banking and payments industry. These include offering personalised customer experiences, enhancing decision-making capabilities, and enabling efficient process automation. Generative AI can be used to develop virtual assistants that provide personalised customer support. Using large language models (LLMs), these virtual assistants can analyse financial data to provide tailored recommendations aligned with customers’ financial goals and preferences.
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Generative AI can also play a critical role in portfolio management using machine learning techniques. It can provide risk assessment, market analysis, and portfolio optimisation.
Lara Virrey: Which barriers to implementation of AI remain in the banking and payments industry, and how could they be overcome?
Beyza Karakoy: Concerns around data privacy and security whilst processing large datasets is one barrier to the implementation of AI in the banking and payments industry. Banks hold some of the most important and sensitive personal data: not just names and addresses but also direct access to financial data, savings, and investments.
They must protect this data from both malicious entities and outright losses. Using AI itself can provide a solution to this. For example, machine learning can identify the normal pattern of behaviour for customers and raise the alarm if there is a deviation from this norm.
Another barrier to the implementation of AI in the banking and payments industry is the weakness of legacy systems, so banks with insufficient infrastructure cannot accommodate new AI technologies. Incompatible legacy IT frameworks need to be addressed and banks should implement intelligent infrastructure that is able to adopt AI.
Lara Virrey: Which companies are the leading adopters of AI technologies in the banking and payments sector?
Beyza Karakoy: AXA, Bank of America, BBVA, DBS, Goldman Sachs, HSBC, JPMorgan, Morgan Stanley, RBC, and Santander are some of the leading adopters of AI technologies in the banking and payments sector.