Oracle and NVIDIA Join Forces to Drive AI Innovation in Bank

The explosive growth of artificial intelligence in banking and financial services has created unprecedented demand for robust infrastructure and expertise to support AI initiatives at scale. 

Through their strategic partnership, technology giants Oracle Corporation, a global provider of enterprise software and cloud computing solutions, and NVIDIA Corporation, the world leader in accelerated computing, are positioning themselves as key enablers of this transformation.

The financial services sector stands at a crucial turning point in its technological evolution. 

“AI has been a great motivator to either make that move to get the data closer to cloud services, or adopt cloud services inside of their own premises,” says Leo Leung, GVP of Oracle Tech and OCI at Oracle. 

“I'll spend quite a bit of time talking about data today, because I think that's one of the prime assets for a lot of financial institutions, and being able to leverage that data with AI is critical.”

The adoption of AI technology is reshaping how banks operate and serve their customers. Forward-looking institutions are implementing AI solutions across multiple dimensions, from customer support to investment recommendations. 

Following the launch of ChatGPT, the industry entered a phase of rapid experimentation and innovation.

Kevin Levitt, Global Industry Business Development, Financial Services at NVIDIA, has observed this acceleration firsthand:

“What financial institutions have quickly realised is that there are so many use cases and so many opportunities to generate either operational efficiencies and/or new revenue streams. Today, banks are operating against hundreds of use cases. It'll be thousands into the future.”

Industrial-Scale AI Factory Development

The partnership's strength lies in its ability to offer solutions at multiple levels, from infrastructure to software-as-a-service. 

This flexibility has enabled significant improvements in operational efficiency, as demonstrated by a Brazilian customer, which achieved a 90% reduction in document identification processing time by implementing these solutions to enhance its anti-fraud solutions.

This dramatic improvement in processing capability has transformed their operations. As Leung explains: “What previously took hours or even days can now happen in seconds. Now the process is interactive and they can work with the customer in real-time, improving customer experience.”

At the heart of this transformation is the concept of AI factories - centralised platforms that combine hardware, software and development tools for AI application creation. 

These sophisticated environments represent a fundamental shift in how financial institutions approach AI development. “It's not just about the hardware and it's not just about the software, you need a platform and a full stack that integrates the two,” Levitt explains.

Historical Context and Demonstrable ROI

The financial services industry has consistently been at the forefront of technological innovation, with each new advancement building upon previous successes. 

Levitt emphasises this evolutionary journey: “Our industry has a great history of leveraging technological innovation to remove operational efficiencies and deliver new revenue opportunities. 

“You've got ATMs and the internet and online banking, to mobile banking and cloud, and certainly now AI and generative AI.”

This latest wave of AI adoption represents a particularly significant shift, as it enables institutions to extract more value from their most crucial asset: data. 

The return on investment is becoming increasingly evident across multiple areas of banking operations, from customer service to risk management.

Advanced Language Models and Generative AI Implementation

The implementation of AI in banking has moved far beyond simple automation. Leading financial institutions are now developing sophisticated approaches to AI deployment. 

This includes the adoption of open-source foundation models, which are then customised for specific banking applications through domain adaptive pre-training and fine-tuning.

Security and accuracy remain paramount concerns in these implementations. 

As Levitt notes: “It's not enough to take an off-the-shelf, API-based solution and release that into the market in financial services, because the accuracy isn't there.” 

Instead, banks are implementing comprehensive frameworks that include retrieval augmented generation (RAG) and other advanced techniques to ensure AI systems provide accurate, compliant responses.

Oracle Database Integration and Customer Experience

The partnership's approach to data integration represents a significant advancement in how financial institutions can leverage their existing information assets. 

Oracle's extensive presence in banking infrastructure, with most major financial institutions running critical operations on Oracle databases, provides a unique foundation for AI implementation.

The solution offers multiple deployment options, from public cloud to on-premises implementations, including specialised offerings like the EU Sovereign Cloud for European Union data protection requirements, to on-premises implementations, like the OCI Dedicated Region. 

This flexibility proves crucial for financial institutions operating across different regulatory environments and jurisdictions.

Leung emphasises the practical importance of this flexibility: “That's a little bit of a tagline for us, bringing AI to the data, as opposed to the other way around. Oftentimes it's just more practical and pragmatic to do that versus a forced migration.”

The integration capabilities extend beyond basic data access. Financial institutions can now combine their historical transaction data, customer profiles and operational metrics with advanced AI models. 

This integration enables banks to create more sophisticated customer experiences while maintaining strict control over their sensitive data.

“We're able to leverage the technology on multiple different levels,” Leung explains. “We think there's a great opportunity for a secure combination of proprietary data, LLMs and open-source tools, where so much of the world's business data is inside of the Oracle database.”

For many institutions, the ability to maintain existing database investments while adding AI capabilities has proven crucial. The partnership's solutions allow banks to implement AI gradually, focusing on high-value use cases without requiring wholesale infrastructure changes.

Transforming Banking Operations

The impact of AI adoption extends across all aspects of banking operations, but perhaps nowhere more significantly than in capital markets. 

Here, financial institutions are using AI to transform how they analyse market data and make investment decisions. These implementations range from automated trading systems to sophisticated risk analysis tools.

Levitt explains that organisations are “utilising generative AI to scour earnings reports and all manner of unstructured data, such as earnings calls, to understand what are new investment themes, new strategies, new portfolio optimisation opportunities to improve returns.”

In risk management, AI-powered systems now analyse vast amounts of data to identify potential risks before they materialise. 

Banks have implemented early warning systems that combine traditional financial metrics with AI-driven market sentiment analysis, news flows and economic indicators.

The partnership's solutions also address one of the most persistent challenges in consumer banking and payments: fraud detection. 

By combining Oracle's data management capabilities with NVIDIA's AI processing power, financial institutions can now analyse transactions in real-time, identifying suspicious patterns while reducing false positives that can frustrate legitimate customers.

This transformation goes beyond just improving existing processes. The integration of AI technologies is enabling entirely new approaches to financial services, fundamentally changing how banks operate and serve their customers. 

From automated customer service systems that can handle complex queries to sophisticated trading algorithms that can process vast amounts of market data, AI is reshaping every aspect of banking operations.

Partnership Evolution and Future Roadmap

The partnership continues to evolve, with new technologies such as the Blackwell platform and Grace Blackwell platforms, and OCI’s Supercluster promising to further enhance AI capabilities. 

These developments represent not just technological advancement, but a deeper understanding of the financial services sector's specific needs.

Both companies bring extensive domain expertise to the partnership. 

As Leung notes, they can accommodate various deployment preferences: “In some cases, it's totally fine for a financial institution to just use public cloud. In other cases, they want to stay completely on-prem and still get managed cloud services. We can do both.”

“Part of a successful partnership is being able to bring our joint expertise to our client base,” Levitt concludes. “We're super excited to see more banks taking advantage of the joint capabilities, to make their AI journey as accelerated as possible.”

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