TL;DR:
- BBVA aims to harness the potential of large language models (LLMs) like ChatGPT.
- DataRally competition involved 440 employees to test their skills with LLMs.
- Positive feedback from participants prompts BBVA to integrate DataRally into its generative AI courses.
- BBVA explores generative AI to enhance efficiency and value for customers while prioritizing security.
- Identifying and training in-house talent in LLM usage is crucial.
- Winners of DataRally displayed exceptional skills with the fewest prompts and the shortest time.
- Generative AI holds significant potential for businesses’ internal processes and global development projects.
- BBVA plans to include generative AI courses in its Data University training program.
Main AI News:
In its quest to harness the potential of large language models (LLMs) powering the success of innovations like ChatGPT, BBVA has embarked on a mission to identify and nurture exceptional in-house talent. This endeavor aligns with the bank’s strategic pursuit of projects rooted in generative artificial intelligence (AI). The recent introduction of DataRally, a competition that drew the participation of approximately 440 employees, stands as a testament to BBVA’s commitment to fostering AI prowess within its ranks. Encouraged by the overwhelmingly positive response from contestants, BBVA is now contemplating the integration of the DataRally framework into its forthcoming generative AI courses within the ambit of its in-house Data University training program.
In recent months, BBVA has ventured into various exploratory initiatives aimed at assessing the transformative potential of generative artificial intelligence in enhancing organizational efficiencies and delivering augmented value to its clientele. Throughout this journey, the bank has steadfastly upheld the primacy of security considerations.
Unleashing the latent possibilities entailed by this burgeoning technology hinges on the identification and development of the most adept in-house practitioners, well-versed in the utilization of the underlying language models. To facilitate this essential process, the Advanced Analytics discipline and BBVA’s GenAI team joined forces to orchestrate the DataRally competition. This multifaceted challenge drew participants from across the countries where the bank operates, tasking them with navigating 12 distinct large language model (LLM) challenges spanning various domains. These tasks ranged from handling quantitative data analysis to identifying anomalies within financial reports and evaluating the sentiment levels of hypothetical customers based on their feedback. Following each checkpoint, participants received valuable feedback to refine their prompt entry strategies, ensuring incremental learning and skill development.
After an arduous four-week competition, three standout performers emerged victorious: Carlos Gutiérrez, a data specialist in the Global Talent & Culture division, Joel de la Cruz, a data scientist within the Advanced Analytics Engineering team at BBVA Spain, and Hans Hidalgo, also a data scientist specializing in Client Solutions at BBVA Peru. Their remarkable achievements were marked by their ability to conquer all challenges with the fewest prompts and in the shortest time.
Josep Amorós, the Data manager at BBVA and the driving force behind the DataRally, expressed immense satisfaction with the competition’s enthusiastic response, fostering a healthy spirit of competition among participants. He noted that 75 percent of the contestants expressed high levels of satisfaction with their experience, and over 95 percent indicated their willingness to participate again. Many participants also conveyed their appreciation for BBVA’s commitment to providing activities and training in Generative AI.
“Generative AI is not a passing trend,” declared Curro Maturana, Global Head of GenAI at BBVA, emphasizing its enduring significance. Maturana highlighted the colossal potential it holds for businesses as they revamp internal processes and embark on global development endeavors that enable simultaneous product and service deployment across diverse regions. BBVA is already on a mission to nurture the finest talent within its ranks to harness this potential effectively.
To further reinforce the cultivation of generative AI skills, BBVA will incorporate generative AI courses into its in-house Data University training program. The successful implementation of the DataRally has paved the way for a dynamic learning experience centered around prompt engineering, a framework that could potentially be extended to empower more employees through these courses.
Conclusion:
BBVA’s commitment to fostering generative AI expertise among its employees through initiatives like DataRally demonstrates its strategic readiness to embrace the transformative potential of AI technologies. This not only enhances its internal capabilities but also positions the bank favorably in a market increasingly reliant on AI-driven efficiencies and global expansion opportunities.
