Around the world, financial institutions are turning to artificial intelligence (AI) to reimagine how capital markets operate. It has been hailed as a force that can make processes more efficient, enhance surveillance and broaden access to financial services.
In the Philippines, where policymakers and regulators are pushing to deepen domestic markets and modernize supervision, AI presents a compelling opportunity. However, its adoption also raises questions about ethics, governance, accountability and systemic risk.
Where AI can add value
The potential use cases are wide-ranging. Back-office functions such as client onboarding, know-your-customer (KYC) checks, reconciliation and compliance filings are time-consuming and prone to human error. Machine learning and robotic process automation can shorten processing times, reduce costs and improve accuracy.
Market surveillance is another promising frontier. AI tools can sift through enormous volumes of trading data to detect unusual patterns linked to insider trading, spoofing or layered manipulation much more effectively than rule-based systems.
Risk management is also fertile ground, with AI able to capture nonlinear relationships in market data and run complex scenario analyses that give investors and regulators a clearer picture of vulnerabilities.
At the customer interface, brokers and wealth managers are experimenting with AI to tailor investment advice and rebalance portfolios, potentially expanding retail participation. Supervisory agencies themselves can deploy the same technology to triage regulatory filings and scan corporate disclosures, making oversight more timely and efficient.
A Philippine context
These possibilities are not abstract. The Bangko Sentral ng Pilipinas (BSP) has been studying AI adoption in financial services through thematic reviews and stakeholder consultations, signaling a readiness to integrate AI into regulatory frameworks suited to Philippine conditions.
The Philippine Stock Exchange has also upgraded its infrastructure, adopting Nasdaq’s EQLIPSE trading technology to ensure that the market’s backbone can support advanced analytics and automated tools.
Meanwhile, the Securities and Exchange Commission (SEC) has acknowledged the role AI can play in surveillance and automation, but has also cautioned against misuse — noting that automation should go hand in hand with back-end support and safeguards.
What global regulators say
International bodies have offered guidance that can inform local approaches. The Financial Stability Board (FSB) has warned that while AI can improve efficiency and risk detection, its widespread use can also create systemic vulnerabilities if models are opaque or if too many firms rely on the same vendors.
The International Monetary Fund has echoed this caution, noting that model concentration and correlated trading strategies could amplify stress in times of volatility.
Meanwhile, the International Organization of Securities Commissions has published recommendations for member regulators to align AI deployment with investor protection and market integrity.
Benefits and drawbacks
If designed and deployed well, AI could help the Philippines achieve several long-standing goals. Faster client onboarding and reduced compliance costs would lower barriers for retail investors and small and medium-sized enterprises seeking to access capital markets.
Enhanced surveillance capabilities could strengthen enforcement, addressing concerns about governance lapses and boosting investor confidence.
Innovation in products and services could encourage more Filipinos to invest in equities and bonds, especially if paired with parallel reforms such as reducing board-lot sizes. In these ways, AI could help democratize access to capital markets and broaden the investor base.
Yet the drawbacks cannot be ignored. One of the most persistent challenges is explainability. Many AI models, especially deep learning systems, function as “black boxes.” Their inner workings are difficult to interpret, making it hard for regulators or market participants to understand why a model flagged a transaction or recommended a product. In capital markets where accountability is paramount, opacity undermines trust.
Vendor concentration poses another risk. If multiple institutions rely on the same AI provider, a single malfunction, data poisoning incident, or outage could trigger widespread disruption. This concentration effect, highlighted in FSB analyses, has particular relevance in small but growing markets like the Philippines.
Bias and fairness are also concerns. Models trained on incomplete or skewed data can produce discriminatory outcomes, disadvantaging certain groups or leading to unsuitable investment advice. Data governance and cybersecurity risks add further complexity, since AI models are only as secure as the datasets they draw from.
Legal and regulatory uncertainty compounds these risks. Disclosure and fiduciary rules designed for a pre-AI world may not adequately cover automated trading, robo-advisory services, or machine-generated disclosures.
Safeguards and next steps
Addressing these challenges requires deliberate action. A risk-based supervisory approach is essential. Philippine regulators such as the BSP and the SEC must focus their oversight on areas where AI materially affects investor protection and market integrity. This could mean closer scrutiny of algorithmic trading strategies, robo-advisory services, and AI-based surveillance systems.
Strong model governance frameworks will be needed, including documentation of data sources, validation methods, and performance monitoring. Firms should be able to demonstrate that their models are reliable, explainable and subject to human oversight.
Vendor oversight is equally crucial. Regulators can require firms to map their dependencies on external AI providers and to test the resilience of their contingency plans. Sector-wide exercises, akin to financial stress tests, could help reveal correlated vulnerabilities.
Data governance standards must also evolve. For consumers, disclosure requirements must keep pace with technology. Retail investors should be told when recommendations are AI-generated, what data underpins them, and what are the limitations.
Cautious optimism
AI offers the Philippines a chance to accelerate market modernization and attract long-term investment. If deployed wisely, it could make capital markets more efficient, accessible and resilient.
But the path forward must be guided by careful governance, robust safeguards and a clear-eyed understanding of the risks.
The challenge now is to turn those efforts into concrete rules and practices that ensure AI strengthens, rather than destabilizes, the country’s capital markets.
The author Ma. Aurora Geotina-Garcia is chairperson of SharePHIL. She is also founding chairperson and president of the Philippine Women’s Economic Network and president of Mageo Consulting Inc., a corporate finance advisory services firm.
To learn more about SharePHIL, visit https://sharephil.org/
