Banking is undergoing a structural shift driven by technology rather than incremental change. As discussions at every apac banking event increasingly highlight, artificial intelligence and open finance are no longer future concepts; they are active forces redefining how financial institutions operate, compete, and serve customers. From decision-making and risk assessment to customer engagement and ecosystem collaboration, these two pillars are reshaping the foundations of modern banking. Their impact is not limited to efficiency gains; they are altering expectations around transparency, speed, and personalisation.

Understanding how AI and open finance work together provides clarity on where banking is headed and why traditional models are rapidly evolving.

The Changing Architecture of Modern Banking

Traditional banking systems were built around closed architectures, limited data sharing, and manual decision layers. While reliable, these models struggle to keep pace with digital-native customer expectations.

AI introduces intelligence at scale, while open finance introduces connectivity. Together, they transform banks from standalone service providers into dynamic platforms. This shift allows institutions to move beyond product-centric thinking and focus on customer-centric financial journeys, supported by real-time data and adaptive intelligence.

Artificial Intelligence as a Core Banking Capability

Artificial intelligence has moved from being a support tool to a foundational capability within banking operations. It now drives core decision-making, enabling banks to analyse data at scale, respond in real time, and operate with greater accuracy and efficiency across functions.

From Automation to Intelligence

AI in banking has evolved far beyond basic automation. It now supports predictive, adaptive, and contextual decision-making across the value chain.

Machine learning models analyse vast datasets to identify patterns humans cannot detect at scale. This enables banks to anticipate customer needs, detect anomalies, and optimise operations continuously rather than reactively.

Where AI Is Creating the Most Impact

• Risk and Compliance

AI-driven monitoring systems assess transactions in real time, improving fraud detection and regulatory compliance accuracy.

• Customer Engagement

Chatbots, virtual assistants, and recommendation engines deliver personalised interactions without sacrificing efficiency.

• Operational Optimisation

AI streamlines back-office processes, reducing costs while improving speed and accuracy.

Strategic Implications for Banks

Banks that treat AI as a standalone tool often see limited benefits. Those embedding AI into core decision frameworks gain long-term advantages through better insights, faster responses, and scalable intelligence that adapts as conditions change.

Understanding Open Finance Beyond Open Banking and What Open Finance Really Means

Open finance extends the principles of open banking beyond payments and accounts. It enables secure, consent-based data sharing across a wider range of financial products, including investments, insurance, and lending.

This model shifts control toward customers, allowing them to decide how their financial data is used and by whom.

• Why Open Finance Matters Now

Customers increasingly expect seamless financial experiences across platforms. Open finance enables this by breaking down data silos and fostering interoperability between institutions and service providers.

• The Infrastructure Behind Open Finance

APIs, consent management frameworks, and data standardisation are foundational. Without strong governance and security layers, open finance cannot scale sustainably.

How AI and Open Finance Reinforce Each Other

AI and open finance are most powerful when deployed together rather than independently. Open finance expands the data universe available to banks, while AI extracts actionable insights from that data. 

This combination enables more accurate credit assessments, hyper-personalised offerings, and real-time financial advice tailored to individual behaviours rather than broad segments. The result is smarter banking built on trust, transparency, and intelligence.

Customer Experience in an AI-Driven Open Finance World

In an AI-driven open finance environment, customer experience is shaped by how intelligently and responsibly data is used. Banks are no longer limited to isolated interactions; they can understand customers across multiple financial touchpoints. This broader visibility allows experiences to feel seamless rather than fragmented. When executed well, it shifts banking from reactive service delivery to proactive, value-led engagement.

• Personalisation at Scale

AI analyses open financial data to understand customer behaviour holistically. This allows banks to offer relevant products at the right moment without intrusive sales tactics.

• Reduced Friction Across Journeys

Open finance removes repetitive data entry and verification steps. AI further streamlines journeys by predicting intent and guiding customers proactively.

• Trust as a Competitive Advantage

Clear consent mechanisms and explainable AI models help build confidence. Customers are more willing to share data when the value and safeguards are transparent.

Risk Management and Compliance Transformation

AI and open finance are reshaping how banks approach risk. AI models continuously assess credit, market, and operational risk using real-time data rather than static snapshots. 

Open finance enhances this by providing a broader financial context, reducing blind spots. Regulatory technology powered by AI improves reporting accuracy and reduces manual compliance burdens. However, governance remains critical to ensure fairness, transparency, and accountability.

Ecosystems, Partnerships, and New Business Models

Open finance encourages collaboration between banks, fintechs, and non-financial platforms. AI enables these ecosystems to function efficiently by orchestrating data flows and decision logic.

Banks increasingly act as platform providers, embedding services into external journeys rather than expecting customers to come directly to them. This ecosystem approach expands reach while maintaining relevance in a crowded digital landscape.

Challenges Banks Must Address

Despite the opportunities, transformation is not without challenges.Legacy systems can limit AI integration and API scalability.

Data quality issues undermine model accuracy. Talent shortages and ethical considerations around AI decision-making also require attention. Success depends on aligning technology investment with governance, culture, and long-term strategy rather than pursuing innovation in isolation.

Looking Ahead: The Future of Banking

As conversations at every apac banking conference suggest, the future of banking will be defined by institutions that combine intelligence with openness responsibly. AI and open finance are not about replacing banks but redefining their role as trusted financial orchestrators.

Industry platforms such as WFISINDONESIA continue to reflect these shifts by bringing together perspectives on technology, regulation, and strategy shaping modern banking. The path forward belongs to banks that view AI and open finance not as trends, but as foundational capabilities for resilience, relevance, and sustainable growth.