By Michael Cullum, VP of Engineering at Bud Financial
Generative AI (genAI) is a powerful tool that is transforming the financial industry and empowers financial services professionals. It makes banks more data-driven and insightful, enhancing decision-making; providing deeper insights; and achieving greater agility, personalized customer service, and automation. The quality of transaction data is central to this transformation, providing invaluable insights into customer behavior and giving professionals a sense of control.
Banks increasingly adopt genAI to improve operations, from spend categorization and transaction monitoring to enhancing risk decisions and predictive customer service. The key to these benefits is enriching transaction data. This process involves enhancing raw transaction data with contextual information, including merchant identification, transaction location, payment processor details, and spending categories. Enriched data allows banks to create a comprehensive picture of customer behavior, enabling personalized services and accurate risk assessments.
The cornerstone of genAI’s effectiveness lies in the quality of a bank’s data, with customer transactions being the most valuable asset. Transaction data offers profound insights into customer behavior and market dynamics, which, when analyzed at scale, can drive significant benefits across the bank’s value chain. From refining risk decisions to shaping innovative propositions and offering predictive customer service, the potential applications are vast.
The core focus of genAI conversations in the banking context is on large language models (LLMs), which are great at dealing with text information but are most effective when working with natural language. This poses a challenge for banks because a lot of data needs to be processed to be useful for genAI. For transactions, this means adding dimensions that can be described with natural language and with as much granularity as possible to ensure that all potential patterns and matches will be found.
“The effective use of genAI hinges on the breadth, depth, and quality of a bank’s data, and the most valuable data a bank owns is its customer transactions,” said Richard Berkley, PA Consulting.
Bud Financial (Bud) helps banks and financial institutions deliver that context to their customers, alerting them to ways that they can improve their decisions. At the same time, banks can use this data to improve their own decisions around areas like credit affordability and application processes. Bud specializes in enriching customer transaction data, giving it customer context that makes it useful right across the enterprise, including as input for genAI applications, enabling banks and financial institutions to gain a deeper understanding of customer behavior, enhance risk assessments, and deliver personalized services.
The Bud platform processes vast amounts of real-time data, providing actionable insights that improve customer engagement and operational efficiency. Bud uses advanced technologies like DataStax Astra DB to manage and scale their data operations seamlessly, ensuring high performance and reliability. Astra DB’s scalability and performance enable Bud to process hundreds of thousands of transactions per second, delivering real-time insights and services.
GenAI is not just transforming financial services; it’s also inspiring banks to harness the full potential of their transaction data. Investing in data enrichment and advanced AI models allows banks to gain deeper insights, improve customer service, and drive innovation. As the financial services industry continues to evolve, financial professionals must stay updated and informed about the role genAI will play in shaping the future of banking, thereby keeping them inspired and proactive.
To learn more about genAI in financial services, read the new report, How to Use GenAI to Multiply Customer Insights from Transaction Data, from Bud and PA Consulting with contributions from DataStax, Google Cloud, and Zup Innovation. The report explores the revolutionary potential of genAI in financial services, highlighting the emergence of the ‘intelligent bank’ and the shift towards an ‘AI-first’ mindset and detailing how genAI will drive transformative changes in strategic and operational decision-making processes in banks.
About Michael Cullum
DataStax
Michael Cullum is the VP of Engineering & Data at Bud, a London Fintech company that produces a platform utilized by top global banks & fintechs to leverage the potential value and power of transactional data to gain a 360 understanding of customers and deliver actionable insights.
