Why the use of augmented core and data are force multipliers for delivering future-proofed technology-enabled banking

Imagine the scene. One early morning, the Chief Information Officer of FutureBank, Alex, is jolted awake by an urgent message from the bank's monitoring AI. Detecting an unusual spike in transaction volume—an order of magnitude higher than normal—the AI reports that it successfully pulled in additional compute resources from the cloud. “Ok, so…” says Alex, but the AI interrupts and says it believes that it is morphing into something more serious. Alex wonders, ‘Are we in the middle of a cyberattack?’
Imagine a world where the boundaries between physical, virtual, and augmented realities blur seamlessly. In this world, retail banking is not confined to traditional branches but extends into immersive virtual environments and augmented reality experiences. This is the reality for FutureBank, a pioneering institution that has embraced augmented core and data to transform its operations and customer interactions.

One early morning, the Chief Information Officer (CIO) of FutureBank, Alex, is jolted awake by an urgent message from the bank's monitoring AI. The AI has detected an unusual spike in the number of requests—an order of magnitude higher than normal. While the AI pivoted to handle the increased volume by pulling in additional compute resources from the cloud, it believes that it is morphing into something more serious. Alex wonders, ‘Are we in the middle of a cyberattack?’

As Alex navigates through augmented and virtual worlds to reach the office, the story of FutureBank's technological journey unfolds, highlighting both the transformative benefits and the potential pitfalls of augmented core and data.

Understanding Augmented Core & Data

Augmented core and data refer to the enhancement of core banking systems with advanced technologies, enabling banks to swiftly adopt, integrate, and swap out technologies as needed. This flexibility is crucial for maintaining competitiveness and operational efficiency in a dynamic market.

Next-Order Effects of Technological Integration

1. Enhanced Decision-Making and Strategic Planning

As Alex reviews the real-time data insights provided by AI and machine learning, it becomes clear how these technologies have revolutionized decision-making processes. The ability to anticipate market trends and customer needs with remarkable accuracy has enabled FutureBank to stay ahead of its competitors.

2. Operational Resilience and Agility

Cloud computing has provided FutureBank with operational resilience and agility. During a recent market disruption, while other banks struggled to maintain continuity, FutureBank seamlessly scaled its resources to meet fluctuating demands. This agility has ensured business continuity and enhanced customer satisfaction. Yet, the current problem underscores the importance of having contingency plans for unexpected system failures. By 2025, 55% of banks plan to migrate core banking systems to the cloud.

3. Trust and Transparency through Blockchain

Blockchain technology has fostered trust and transparency in FutureBank's operations. Customers feel secure knowing their transactions are protected by an immutable ledger, reducing the risk of fraud and enhancing the bank's reputation. However, Alex is aware that the integration of blockchain also requires constant vigilance to prevent potential vulnerabilities from being exploited by malicious actors. By 2025, 30% of major banks plan to adopt blockchain for transaction processing.

4. Personalized Customer Experiences

The next-order effect of integrating AI into core banking systems is the ability to deliver highly personalized customer experiences. By analyzing vast amounts of customer data, FutureBank can tailor products and services to individual preferences, enhancing customer satisfaction and loyalty. This level of personalization opens up new revenue streams through targeted marketing and cross-selling opportunities.

5. Cost Efficiency and Resource Optimization

While the initial investment in augmented core and data may be significant, the long-term cost savings are substantial. Automation of routine tasks reduces operational costs, while the ability to quickly integrate new technologies minimizes the need for extensive system overhauls. This optimization of resources allows FutureBank to allocate funds more effectively, driving innovation and growth. However, Alex knows that the cost of addressing system failures and security breaches can be high, emphasizing the need for proactive measures.

GenAI and Agentic AI: Transformative Technologies

Generative AI (GenAI)

Generative AI is revolutionizing the banking industry by enhancing customer-facing chatbots, preventing fraud, and speeding up time-consuming tasks such as developing code and summarizing regulatory reports. The next-order effects of GenAI include the ability to create new ideas, products, and services that can significantly improve operational efficiency and customer engagement. However, GenAI also presents challenges such as the generation of false or illogical information, intellectual property infringement, and issues of bias and fairness. In 2023, the financial services industry invested an estimated $35 billion in AI, with banking leading the charge.

Agentic AI

Agentic AI goes beyond GenAI by enabling autonomous decision-making, collaboration, and learning. This technology can independently perceive, reason, act, and learn, which can transform banking operations by rapidly processing data, increasing decision accuracy, and personalizing customer interactions. However, Agentic AI can lead to a vast explosion in the number of concurrent requests that the core has to process, resulting in massive performance considerations. Additionally, negative actors could leverage this technology to ramp up their attacks, posing significant security risks. Fifty-four percent of consumers trust the use of AI agents in financial services.

Negative Implications and Considerations

Performance and Scalability

The integration of Agentic AI can result in a significant increase in the number of concurrent requests processed by core banking systems. This requires robust infrastructure and advanced performance management to ensure system stability and efficiency. 

Security Risks

As AI becomes more integrated into banking operations, the risk of malicious actors leveraging AI for sophisticated cyberattacks increases. Banks must implement stringent cybersecurity measures to protect sensitive data and maintain customer trust. Finance firms are averaging $5.9 million per data breach.

Ethical and Regulatory Challenges

AI technologies raise ethical and regulatory concerns, including data privacy, bias, and fairness. Banks must navigate these challenges by adhering to compliance frameworks and implementing transparent and explainable AI systems. Regulatory scrutiny of risk management and governance is intensifying.

Real-World Examples

Case Study 1: AI-Driven Customer Service

A leading retail bank implemented AI-driven chatbots to handle customer inquiries. This not only improved response times but also freed up human resources for more complex tasks. The next-order effect was a significant increase in customer satisfaction and a reduction in operational costs.

Case Study 2: Cloud-Based Data Management

Another bank leveraged cloud computing to enhance its data management capabilities. This move ensured seamless data access across multiple branches, improving collaboration and decision-making. The next-order effect was enhanced operational efficiency and the ability to quickly adapt to regulatory changes.

Case Study 3: Blockchain for Secure Transactions

A major financial institution integrated blockchain technology into its transaction processing system. This not only enhanced security but also increased transparency and trust among customers. The next-order effect was a reduction in fraud-related losses and an improvement in the bank's reputation.

Benefits for Senior Technology Leaders

Strategic Advantage

Augmented core and data provide a strategic advantage by enabling leaders to make data-driven decisions quickly. This agility is crucial in a competitive market where timely decisions can make a significant difference.

Futureproofing Technology Investments

By adopting a flexible and scalable approach, banks can ensure their technology investments remain relevant and effective in the long term. This futureproofing is essential for maintaining competitiveness and driving innovation.

Improved Customer Experience

The integration of advanced technologies leads to improved customer experiences, which is a key differentiator in the banking industry. Satisfied customers are more likely to remain loyal and recommend the bank to others, driving growth and profitability.

Conclusion

As retail banks navigate the complexities of the modern financial landscape, augmented core and data emerge as critical components of a futureproof technology strategy. By focusing on the next-order effects of technological integration, senior technology leaders can drive innovation, enhance operational efficiency, and deliver exceptional customer experiences. Embracing these advancements is not just about staying current; it's about shaping the future of banking.