👩‍🍳 How we use AI at Tech in Asia, thoughtfully and responsibly.🧔‍♂️ A friendly human may check it before it goes live. More news hereAnt International predicts that its AI model for foreign exchange (FX) could be as transformative for financial services as OpenAI’s GPT has been for the wider business world.The company has introduced the Time-Series Transformer (TST) AI FX Model to forecast trading volumes and manage financial risks.The TST model analyzes numerical data to predict cash flow and FX exposure, claiming over 90% accuracy.It operates on hourly, daily, and weekly intervals. The goal is to help clients reduce unnecessary hedging and risk-premium costs.Unlike generative AI models like GPT, the TST focuses on core financial operations such as trading and transaction processing.🔗 Source: South China Morning Post🧠 Food for thought1️⃣ Financial AI’s divergent paths: Beyond generative modelsAnt International’s Time-Series Transformer represents a specialized AI approach that addresses fundamentally different needs than general-purpose LLMs like ChatGPT.While most financial institutions are focused on implementing generative AI, these models have largely remained at the periphery of core financial operations, with the Financial Stability Board noting they’re primarily used for customer interactions and regulatory compliance 1.Quantitative finance experts have recognized this limitation, with research showing that LLMs—despite their vast language capabilities—aren’t optimally designed for the numerical prediction tasks central to trading and risk management 2.This division in AI development reflects broader industry trends, where 85% of CFOs see AI as a means to improve efficiency, yet 61% of finance teams have yet to implement meaningful AI solutions. This suggests a gap between general AI capabilities and specialized financial needs 3.The evolution from basic AI applications to specialized models like Ant’s TST reflects the growing understanding that different domains require purpose-built AI architectures rather than adapting general-purpose models.2️⃣ Time-series models address finance’s prediction-centric coreAnt’s focus on time-series prediction directly targets the fundamental quantitative challenges of financial services that generative AI has struggled to address.Financial institutions have been applying AI to optimize capital allocation and enhance trading analysis for years, but these applications have required specialized models designed specifically for numerical data processing rather than text generation 1.Recent research on AI in quantitative investment highlights how time-series models are particularly valuable for predicting market movements and automating trading decisions—precisely the use case Ant International is targeting 4.The practical value of such specialized models is evident in their application areas: while LLMs excel at document analysis and customer service, financial institutions implementing AI for trading strategies and risk management consistently rely on specialized numerical prediction models 5.This explains why Ant describes its technology as potentially “foundational” for financial services—it addresses the prediction-centric core of finance rather than the communication and documentation aspects where generative AI currently excels.Recent Ant International developments

👩‍🍳 How we use AI at Tech in Asia, thoughtfully and responsibly.🧔‍♂️ A friendly human may check it before it goes live. More news hereAnt Digital Technologies launched its AI-powered fintech solutions at the Dubai FinTech Summit on May 13, 2025. This marked the company’s first global introduction of its product suite, including Agentar, Zoloz, and mPaaS.Agentar offers zero-code and low-code AI tools for building applications like customer service agents and risk monitoring systems.Zoloz is a digital identity solution used by over 100 million users in Southeast and South Asia.MPaaS, built on Alipay’s infrastructure, supports high-performance mobile app development.The company has partnered with over 300 entities and offers more than 80 solutions to 10,000 industrial clients.🔗 Source: Ant Digital Technologies🧠 Food for thought1️⃣ AI in finance has evolved from experimental to essentialThe arrival of Ant Digital Technologies’ AI suite represents the culmination of decades of technological evolution in financial services.Early AI applications in finance date back to the 1950s with basic automation in accounting, followed by expert systems in the 1980s like Protrader for market predictions and PlanPower for financial planning 1.By 1993, we saw the FinCEN Artificial Intelligence System analyzing 200,000 transactions weekly to detect money laundering, successfully identifying $1 billion in potential cases 1.Today’s AI financial applications have progressed dramatically beyond these early systems, with J.P. Morgan’s COIN platform demonstrating the efficiency leap by analyzing 12,000 credit agreements in seconds, work that previously took 360,000 human hours 2.This evolution reflects broader industry trends, with AI-driven financial solutions projected to reach $32 billion in Q1 2025, reflecting a 65% year-over-year increase 3.Ant’s Agentar platform enters a mature market where 98% of CEOs now believe AI offers immediate business benefits. However, implementation remains challenging, with 61% of CFOs still not having deployed AI solutions 4, 5.2️⃣ Financial inclusion emerges as a key driver for AI investmentAnt’s emphasis on inclusion aligns with an industry-wide trend of using AI to expand financial access to previously underserved populations.Companies like Lendbuzz are pioneering AI-powered risk analysis specifically designed to provide credit to the “credit invisible”—customers who lack traditional credit histories but may still be creditworthy 6.This approach addresses a significant market opportunity while serving a social purpose, creating financial products for people who were previously excluded from formal financial systems.The expansion of ZOLOZ’s e-KYC solutions to serve over 100 million users across Southeast and South Asia demonstrates how AI-powered identification systems can overcome significant barriers to financial inclusion in developing markets [original article].AI’s impact extends beyond credit to financial advice, with intelligent advisory services becoming accessible to middle-class clients at significantly reduced costs compared to traditional human advisors 3.This trend represents a fundamental shift in financial services accessibility, using technology to address the traditional trade-off between personalization and affordability that previously limited access to quality financial services

French fintech Spendesk, a platform for spend management and procurement, has partnered with AI infrastructure startup Dust to roll out tailored, secure AI assistants across its organisation. The initiative aims to unify internal AI usage, enhance productivity, and maintain strong compliance with European and UK data regulations.Enterprises are increasingly turning to automation tools to remain competitive. Dust specialises in enterprise-ready AI agents built on top of secure integrations with workplace tools such as Slack, Notion, and Intercom.Spendesk, which counts SoundCloud, Gousto, and SumUp among its customers, had already embraced AI in various internal functions, from sales and customer support to accounting automation. But when it sought to scale AI usage across departments, it found itself grappling with fragmented adoption. Different teams were experimenting with disconnected tools, leading to data security concerns and inconsistent usage patterns.“It’s impossible to use Spendesk without interacting with AI. We’ve implemented no fewer than 15 AI-powered features since 2017, predicting and pre-filling more than 2 million accounting fields each month,” said Rodolphe Ardant, Founder of Spendesk.“As UK businesses continue to navigate an evolving regulatory and economic landscape, secure AI adoption has never been more crucial