Banking & Finance

The oil and gas industry depends on timely, accurate data—from the field to the boardroom. But the majority of that information doesn’t come neatly packaged in dashboards or databases. Read More

The demand for transformation in banking has reached a tipping point. Rising operational complexity, tighter regulations, and digital-first customers are forcing banks to rethink how they operate—fast. Read More

GenAI transforms banking with new opportunities and exposes risks like bias, data security threats, and transparency gaps. Banks must navigate these challenges to ensure responsible use and maintain trust. Read More

A proactive approach unlocks innovation faster. For instance, BNY’s AI tool, Eliza, leverages Nvidia hardware and cloud services from Microsoft Azure and Google Cloud, combined with AI models like GPT-4, Gemini, and Llama. Read More

Before deploying AI, banks must establish strong data infrastructure. GenAI thrives on high-quality, clean data, and banks must invest in building data platforms that ensure their information’s availability, consistency, and integrity. Read More

Banks can proactively identify and mitigate potential cost overruns due to regulatory changes, cybersecurity threats, or technological challenges using risk management frameworks. This approach ensures that contingency plans are in place. Read More

AI models, especially those using deep learning, offer powerful predictive capabilities but often work like a “black box,” making it hard for bank staff to fully understand how decisions are made. Read More

Banks are using generative AI models to analyze data and deliver highly personalized customer interactions. Rather than waiting for customer inquiries, AI anticipates needs, delivering tailored advice and product recommendations. Read More