More than eight out of 10 leaders (84%) of FSI organizations say they fear catastrophic data loss while AI relaxes their data infrastructure. This comes at a time when companies rush to adopt AI, aware of its impact on daily operations and its role in obtaining a competitive advantage.
It was a discovery of the BFSI data infrastructure in 2024 by Hitachi Vantara, which requested information from 231 BFSI specialists, level C managers and computer deciders in 15 countries.
DALIMMA DATA
According to the report, the real barrier to AI’s success is not the technology itself, but the ability to manage data safely, with precision and on a large scale. In a word, many realize that their data infrastructure is not ready to support the adoption of AI.
The rapid Ascension of AI puts pressure on traditional data systems, forcing financial institutions to prioritize between security, quality and sustainability. Indeed, almost half (48%) of respondents cite data security as their major concern for the implementation of AI, reflecting the critical need to protect themselves against internal and external threats.
More sobbing is the conclusion that in BFSI companies, data is available when and where it is necessary only a quarter of time (25%), and BFSI AI models are only 21% of the time. In addition to the threat of ransomware, 36% cite IA errors causing data violations as a risk among the first three, and 32% of the attacks compatible with AI could do the same.
A question of confidence
Mark Katz, CTO of financial services in Hitachi Vantara, noted that the corporate model is fundamentally based on trust in the financial services sector. This means that reputation damage represents a significant risk, which makes the relationship between security and precision both critical and complex.
Katz observed that the consequences could be serious if a chatbot inadvertently disclose sensitive information integrated into its training data. The risk of a chatbot providing incorrect information could also be a serious threat. And if someone should act on inaccurate data, it would raise complex questions about responsibility and responsibility, he notes.
“This global research reflects what we also mean in Southeast Southeast Asia-that the real obstacle to the success of AI is not the technology itself, but the ability to manage data safely, with precision and on a large scale. Financial organizations must focus on strengthening their data foundations to ensure that AI offers a real and lasting impact,” said Joe NGO, Vice-President of ASEAN Hitachi Vantara.
The full report is accessible here.
Image credit: istock /Anthony Boulton