Shana Maré Hitachi Vantara: Financial Services AI Needs Data Foundations

• Shana Maré of Hitachi Vantara states that the future of banking hinges on trusted, resilient, and accessible data, not just AI access.
• Banks are embedding AI into operations for outcomes like fraud detection and compliance, emphasizing data quality and governance.
• Real-time banking and instant payments necessitate accurate, real-time data for competitive advantage and customer expectations.
• Regulators and boards prioritize operational resilience, making rapid recovery from disruptions a strategic imperative.
• Financial institutions must demonstrate strong governance over data privacy, cybersecurity, and AI, with compliance becoming data-driven.

The future of banking will not be defined by mere access to AI, which is becoming universally available, but rather by an institution's capacity to leverage the most trusted, resilient, and accessible data.

The evolving landscape of financial services, particularly in South Africa, is increasingly shaped by the strategic application of artificial intelligence (AI) and the foundational role of robust data infrastructure. Shana Maré, Territory Manager at Hitachi Vantara, emphasizes that the future of banking will not be determined by mere access to AI, which is becoming universally available, but rather by an institution's capacity to leverage the most trusted, resilient, and accessible data. This perspective highlights that strong data foundations, coupled with continuous availability and advanced cyber resilience, are paramount for banks aiming to innovate, comply with regulations, compete effectively, and achieve sustainable growth.

Maré observes a significant shift within the local banking sector: AI is no longer treated as an isolated innovation project but is being deeply embedded into daily operations. The focus has moved towards achieving tangible business outcomes, such as enhanced fraud detection, improved customer service, sophisticated risk management, streamlined compliance processes, and operational automation. This transformation underscores a critical question for banks: not whether to adopt AI, but how quickly and safely they can operationalize it. The success of AI initiatives, therefore, hinges directly on the quality, governance, and accessibility of the underlying data, making these aspects central to any AI strategy.

This strategic imperative for data quality is further amplified by the rise of real-time banking and instant payments, which are rapidly becoming the industry standard. Customers now expect immediate banking services, encompassing payments, account onboarding, lending decisions, and personalized digital experiences. To meet these demands, financial institutions require access to accurate, real-time data. The ability to process and analyze information instantaneously has emerged as a key competitive differentiator, enabling quicker decision-making and significantly enhancing customer experiences.

In parallel with technological advancements, regulatory bodies and corporate boards are placing heightened emphasis on operational resilience, business continuity, cyber recovery, and demonstrable proof of recovery capabilities. This makes operational resilience a critical strategic imperative for financial institutions. Banking leaders are increasingly evaluated not merely on their ability to prevent outages, but crucially, on the speed and effectiveness of their recovery from disruptions. Consequently, resilience has ascended to a board-level business priority, reflecting its fundamental importance in maintaining trust and stability within the financial sector.

Financial institutions are also facing intensified demands to demonstrate robust governance across several key areas, including data privacy, cybersecurity, operational resilience, AI governance, and comprehensive customer protection. Compliance, particularly in the context of South Africa banking AI compliance, is evolving into a data-driven exercise. This necessitates that organizations maintain clear visibility, stringent control, and complete auditability over the ever-growing volumes of information they manage. This shift underscores the need for sophisticated financial sector data governance ZA frameworks that can adapt to rapid technological changes and evolving regulatory landscapes.

The adoption of cloud technologies presents another layer of complexity and opportunity for financial services. Most banks are not pursuing a complete migration to the cloud; instead, they are opting for hybrid architectures. These architectures allow workloads to be strategically placed based on a careful consideration of cost, performance, risk, compliance, and data sovereignty requirements. This approach enables organizations to strike a vital balance between fostering innovation and maintaining rigorous governance, all while retaining control over critical banking systems and sensitive data.

Ultimately, the future of banking will be defined by data, with resilience serving as an indispensable capability for operational resilience financial institutions. Modern banks require advanced platforms capable of handling vast and increasing volumes of both structured and unstructured data, while also supporting AI and analytics at scale. These platforms must be engineered to deliver near-zero downtime, facilitate rapid recovery from cyber incidents, and operate consistently across both on-premises and cloud environments. Crucially, they must provide real-time access to business-critical information and meet increasingly demanding regulatory requirements, including those related to AI governance financial services South Africa and real-time banking payments compliance. Hitachi Vantara is recognized for its role as a trusted and highly resilient technology partner for core banking environments, providing the stability and reliability essential for financial institutions, with a current focus on enabling client success.

Lawyers and compliance officers must advise financial institutions on developing robust data governance frameworks, operational resilience strategies, and AI ethics policies to meet increasing regulatory scrutiny, manage data privacy risks, and ensure auditability in the era of AI and real-time banking. This includes ensuring compliance with evolving data privacy, cyber security, and operational resilience regulations, which are increasingly data-driven.

Source: Original reporting via ITWeb