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Navigating the Maze: Market Data Challenges in Asia-Pacific

Explore critical insights into market data and financial landscapes.

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A multinational financial services firm operating across Asia-Pacific

A well known non-profit organisation (NPO) executives and board members

An European multinational financial services company operating across Asia-Pacific

A prominent European bank with a significant presence in global financial markets

A prominent Asian securities firm mainly presents in North Asia

An Asian securities firm with a strong market presence in South Asia

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Insight Pulse

Trends That Matter

Highlights the focus on relevant, impactful trends worth knowing

Market Boom: Projected to hit USD 622.4 billion by 2030, growing at a 10.1% CAGR.

Investments: Blackstone's $10 billion QTS acquisition reflects expansion efforts.

Energy Shift: Nuclear-powered data centers address power shortages.

Sustainability: ST Telemedia adopts renewable energy to cut emissions.

Energy Savings: AI reduces cooling energy use by up to 40%, per Google's DeepMind results.

Market Surge: AI in datacentres to hit USD 15.4 billion by 2027, with a 22.5% CAGR.

Reliability: Predictive AI lowers downtime by 30% via fault detection.

Green Impact: AI-driven resource optimisation slashes carbon footprints.

Vendor Growth: Data marketplace platforms to reach USD 5.73 billion by 2030, with a 25.2% CAGR.

Product Expansion: Alternative data market to hit USD 135.72 billion by 2030, growing at a 63.4% CAGR.

Cost Inflation: Subscription renewals up 15% on average in 2024, with outliers as high as 600%.

Tool Adoption: 70% of financial firms to adopt new market data tools by 2025.

Market Growth: Alternative data market to hit USD 17.4 billion by 2027, with a 22.5% CAGR.

AI Integration: 60% of financial firms adopt AI for alternative data analysis by 2025.

Data Quality: 30% of firms report data quality as the top challenge.

Investment Surge: VC funding for alternative data startups rises 40% in 2024.

Attack Surge: 65% increase in phishing incidents in 2024.

AI-Generated Threats: 40% of phishing emails now use AI to mimic trusted sources.

Deepfake Voice Calls: 25% of phishing attempts involve voice impersonation.

Employee Training: Regular simulations reduce click rates by 30%.

Market Surge: Generative AI market to reach USD 110.8 billion by 2030, with a 34.6% CAGR.

Adoption Rate: 60% of enterprises to adopt generative AI by 2025.

Productivity Gains: Generative AI boosts content creation speed by 40%.

Ethical Focus: 70% of firms prioritise ethical AI guidelines.

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Real Insight Beat

Navigating the Maze: Market Data Challenges in Asia-Pacific

The Asia Financial Information Conference (AsiaFIC) 2025, held in Singapore from May 28–30, brought together over 300 market data professionals. Among them were fintech innovators, banking experts, and at least 100 participants from major financial hubs in the UK, Europe, and the US. The global turnout was a testament to the event's draw—but it also laid bare a critical challenge: Asia-Pacific's market data landscape is fragmented, shaped by diverse regulations, business needs, and operational realities.

Fragmentation: A Region of Contrasts

In Asia-Pacific, trading and banking authorities enforce a range of regulatory frameworks, but stock exchanges add further layers of complexity for market data users—banks, asset managers, and other subscribers.

These observations reflect widespread trends across the region rather than issues unique to any single entity. They illustrate a broader environment where standardisation is limited, and coordination remains an ongoing hurdle.

Diverse Exchange Policies:

Stock exchanges across the region often adopt varying approaches to data access, usage rights, and pricing models. For instance, some might offer straightforward data access, while others implement more intricate structures tied to usage levels. This diversity creates a patchwork of requirements, making it challenging for users operating across multiple markets to streamline compliance and vendor relationships.

Technology-Driven Disruptions:

Periodic technology updates by exchanges—such as shifts in data formats or delivery mechanisms—can create downstream effects. Market data users may encounter delays or unexpected costs as vendors adjust to these changes, impacting workflows and resource allocation.

Business and Operational Impacts

This fragmented landscape influences how market data users prioritize and manage their operations. Some may focus on securing low-latency data to maintain a competitive edge, while others grapple with controlling costs amid fluctuating vendor fees. Operational teams often find themselves managing tailored processes—such as negotiating vendor contracts or ensuring regulatory compliance—that resist regional standardisation.

A Path Forward?

AsiaFIC 2025 prompted a key question: How can Asia-Pacific’s market data community address these challenges collaboratively? One potential inspiration comes from France’s COSSIOM, a subscriber-led initiative that tackles shared issues like vendor coordination. Could a similar model help APAC users navigate their fragmented landscape more effectively?

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Real Insight Beat

Mastering Market Data Spend: A Holistic Approach to Vendor Challenges

Market data is essential for financial institutions, driving decisions from high-frequency trading to long-term investment strategies. However, managing the vendors that provide this data presents significant challenges. Fragmented relationships, rising costs, compliance risks, and delays in data access strain budgets and operational efficiency. A holistic strategy is required to address these issues comprehensively. This article explores how financial firms can regain control, optimise spending, and transform market data into a strategic asset.

The Cost of Fragmentation: Centralizing Vendor Management

Managing multiple market data vendors without a unified approach leads to operational inefficiencies and inflated costs. Each vendor introduces distinct pricing structures, contractual terms, and usage restrictions, resulting in:

Inconsistent pricing that complicates expense tracking.

Overlapping subscriptions that waste budget on redundant data.

Weakened negotiation leverage due to decentralised spending.

Controlling Escalating Costs: Gaining Visibility into Spending

Market data costs often rise unnoticed, eroding budgets over time. Without clear visibility into usage, firms may overpay for:

Unused subscriptions that remain active despite low engagement.

Redundant data sourced from multiple vendors.

Mitigating Compliance Risks: Navigating Vendor Agreements

Vendor contracts are complex and carry significant risks. Inaccurate reporting of data usage or mismanagement of entitlements can lead to:

Costly audits with substantial penalties.

Reputational damage from compliance failures.

Accelerating Data Access: Streamlining Product Selection

In fast-paced markets, delays in accessing market data can hinder decision-making. Inefficiencies often arise from:

Product selection, with an overwhelming array of options.

Implementation, as teams struggle to integrate new data feeds.

A Holistic Strategy: The Path to Optimization

The challenges of market data spend — fragmentation, rising costs, compliance risks, and access delays — are interconnected. Addressing them requires a cohesive strategy:

Centralise vendor management to reduce waste and enhance leverage.

Control costs through regular audits and real-time tracking.

Ensure compliance with automated tools and proactive reviews.

Streamline access via pre-vetted solutions and modular integration.

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Real Insight Beat

AI-Driven Automation in Data Center Operations: Greater Bay Area Convention and Beyond

The Greater Bay Area Cloud & Datacenter Convention 2025, held on May 28, 2025, at Kowloon Shangri-La, Hong Kong, offered a platform for industry leaders to explore the future of data centers. A highlight was the panel "Greater Bay Area: Revolutionizing Data Center Operations with AI and Automation," moderated by Jack Ko (CEO, Keystone Group), featuring Dean Jones (CBRE), Ben Li (Equinix), Eric Liu (Global Switch). The session delivered valuable insights into AI and automation from the perspectives of facility management and operators. While these viewpoints were well-represented, the enterprise perspective — key to aligning innovations with business goals — could have further enriched the discussion.

Key Takeaways from the Convention

Energy Efficiency: AI optimises power and cooling, reducing costs and environmental impact.

Predictive Maintenance: Automation anticipates equipment issues, minimising downtime.

Operational Streamlining: Routine tasks like monitoring are automated, enhancing efficiency.

Sustainability Focus: AI aligns with the GBA’s goals for greener datacentres.

The Enterprise Perspective in Data Center Operations

As end-users of data center services, prioritise outcomes that directly support their business objectives. Their focus includes:

Cost-Effectiveness: Maximising value within tight budgets.

Scalability: Adapting resources to fluctuating demands.

Reliability: Ensuring uninterrupted service for critical operations.

Compliance: Meeting regulatory and security standards.

Trends in Enterprise Data Center Operations

AI-Powered Uptime Assurance: Predictive analytics now identify risks with higher precision, safeguarding enterprise continuity.

Energy Optimisation: A June 2025 GBA study reports a 15% increase in AI-driven energy savings, easing enterprise cost pressures.

Edge Computing Expansion: Enterprises leverage AI-managed edge datacentres for low-latency applications like IoT.

Compliance Automation: AI simplifies regulatory reporting, reducing enterprise workloads.

Challenges Facing Enterprise Data Center Operations

Legacy Integration: Older systems often clash with modern AI tools, requiring significant rework.

Regulatory Demands: AI’s reliance on data raises privacy and compliance concerns.

Workforce Skills: Implementing AI demands expertise that many enterprises lack.

Upfront Costs: Initial investments can strain limited budgets.

Looking Ahead: Integrating the Enterprise Voice

AI-driven automation — whether self-managed or operator-provided — delivers:

Reduced Downtime: Faster issue resolution and proactive fixes keep systems running.

Lower Costs: Less manual intervention means fewer service fees and operational expenses.

Improved Reliability: Continuous monitoring and optimisation ensure consistent performance.

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