The Southeast Asian fintech landscape has witnessed significant growth over the past decade, propelled by a rise in digital adoption and increased venture capital (VC) interest. Amid a global slowdown in fintech investment globally, the region saw a steady resilience, with some sectors seeing optimistic growth.
According to PwC, total venture funding in fintech startups in the region stood at US$20 billion from 2015 to the first three quarters of 2024 (excluding undisclosed deals). Meanwhile, Generative artificial intelligence (Gen AI) in Southeast Asia has experienced substantial global funding growth, with a 38 percent year-on-year increase from $16.1 billion to $22.2 billion from the first three quarters of 2023 to the same period in 2024.
Within this context, AI agents, or autonomous software systems that can perceive their environment, make decisions, and execute tasks, are poised to become central to delivering further fintech innovations. These agents leverage machine learning (ML), natural language processing (NLP), and advanced analytics to deliver services such as automated underwriting, personalized customer support, and risk management.
What are AI agents?
AI agents are more than just chatbots or simple logic/decision trees. They are dynamic systems that combine capabilities in data analysis, deep learning, and automation to interpret complex information streams. These include transaction data, user profiles, and market signals. AI agents then act and make decisions with minimal human oversight.
In fintech, these agents are particularly attractive due to their ability to process high volumes of transactional data, assess risk profiles in real-time, and automate complex processes like regulatory compliance checks.
Key applications in Southeast Asia’s fintech sector
Customer engagement and onboarding. AI-powered virtual assistants can handle large volumes of inquiries about account openings, loan eligibility, or insurance claims. This is especially valuable in diverse linguistic markets like Southeast Asia. By integrating NLP capabilities, AI agents can provide localized support in multiple languages.
Risk assessment and fraud detection. Banks and fintech in the region grapple with complex know-your-customer (KYC) and anti-money laundering (AML) requirements. AI agents can rapidly analyze high-volume transactional data and flag suspicious activities in real time. These systems rely on machine learning models trained on historical fraud patterns to anticipate and counter new threats.
Automated lending and credit scoring. In many parts of Southeast Asia, limited credit histories can be a bottleneck to securing loans. AI agents can evaluate alternative data, like mobile phone usage, e-commerce transactions, or social media behavior.
For example, Kredivo offers a “Buy Now, Pay Later” (BNPL) solution by using AI-driven credit scoring that taps into alternative data sources such as e-commerce transactions. The company reports to have achieved over $4 billion in business financing serving about 100,000 SMEs in the region.
For businesses, Funding Societies (also known as Modalku) employs AI to evaluate borrower risk profiles rapidly, using machine learning to reduce underwriting times and default rates. This approach is particularly relevant for SMEs that lack traditional collateral but demonstrate potential growth.
Robo-advisory and wealth management. Robo-advisors extend the concept of AI agents by offering automated portfolio management, risk profiling, and personalized investment strategies.
An example is Stashaway, which offers various investment and wealth management services utilizing AI and data analytics. This digital wealth manager offers investment portfolios and wealth management solutions for both retail investors and high-net-worth individuals and reports to have at least $1 billion in assets under management (AUM).
Challenges and considerations
Regulatory complexity. Countries like Singapore and Malaysia have robust regulatory frameworks that encourage fintech innovation but also require strict compliance with data privacy and AML standards. Other nations’ regulators are closely following suit. AI agents will need to be transparent and auditable to gain approval from regulators such as the Monetary Authority of Singapore (MAS) and the Bank Negara Malaysia, which provide regulatory sandboxes that ensure the safety and compliance of fintech apps as they are developed and made available to the market.
Talent scarcity. KPMG reports that the global shortfall of full-time software developers and cybersecurity professionals in this industry is expected to hit 8 million this year. Skilled AI engineers, data scientists, and ML specialists are still in short supply in the region. “We believe that while certain jobs will be replaced by machines and AI, more roles and industry sectors will be enhanced and augmented by tech developments in the future,” talent platform Glints has reported.
“Despite the proliferation of readily available foundational models today and the ramp-up in educational infrastructure, the skills to create, implement, deploy and evaluate AI systems in a production capacity are still sorely needed,” said Yeo Puay Lim, commercial director at Glints.
Ethical and bias concerns. If AI agents rely on limited or skewed training data, they could inadvertently exclude or misjudge marginalized groups, which is a common concern with how large language models analyze and crunch data. Dataset diversity and explainability in algorithmic decisions is critical for building trust and ensuring financial inclusion, which is something that AI governance frameworks need to address.
Conclusion
By analyzing massive datasets and autonomously executing complex tasks, AI agents lower operational costs and expand access to critical financial products. However, challenges related to regulation, talent, and ethics persist.
Nevertheless, the momentum is unmistakable. As both startups and established players collaborate with regional VCs, the widespread adoption of AI agents in fintech will likely redefine how consumers and businesses engage with financial services—highlighting a more inclusive and innovative digital economy across the region.
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