Ant International — best known for powering global fintech and payment networks — has unveiled Falcon TST (Time-Series Transformer), a new AI forecasting model designed to tackle one of the toughest problems in finance and operations: making accurate predictions from complex, fast-moving data.

The Falcon TST model is no ordinary AI. It’s the industry’s first Mixture of Experts (MoE) architecture-based time-series model with multiple patch tokenizers, pushing the boundaries of data prediction with a scale of up to 2.5 billion parameters. In plain English: it’s a powerhouse built to handle massive data streams and extract predictive insights that traditional models simply can’t.

AI That Sees Around Corners

Already in internal use at Ant International, Falcon TST manages cashflow and foreign exchange (FX) exposure on hourly, daily, and weekly cycles. The results? Over 90% accuracy and a reduction in FX costs by up to 60% — a striking example of how deep learning and big data can translate directly into financial efficiency.

But Ant isn’t keeping this tech to itself. The company is working with industry partners to apply Falcon TST in real-world scenarios, helping businesses hedge against FX volatility and airlines stabilize ticket pricing amid unpredictable market swings.

That’s no small feat. With the Airports Council International projecting nearly 10 billion air travelers in 2025, even a small boost in pricing accuracy could mean significant global cost savings — both for carriers and consumers.

Beyond Finance: Forecasting Everything, Everywhere

While Falcon TST’s origins are in fintech, its applications stretch much further. Time-series forecasting is a backbone of countless industries, and Ant’s model can be used to predict everything from weather and logistics data to market trends and traffic flows.

By tackling long-term forecasting benchmarks and setting state-of-the-art zero-shot results (meaning it performs well even without task-specific training), Falcon TST signals a leap forward in AI generalization — a goal every major AI lab has been chasing.

Opening the Gates to Collaboration

In a rare move for a global fintech giant, Ant International is open-sourcing Falcon TST, inviting the global AI research community to build upon its foundations.

“By open-sourcing our proven Falcon TST model, we aim to advance the field through global collaboration — inviting scientists worldwide to contribute real-world feedback and accelerate innovation in time series learning,” said Jiang-Ming Yang, Chief Innovation Officer at Ant International.

That openness could be key to keeping Ant at the forefront of AI in finance — especially as rivals like Stripe, Mastercard, and JPMorgan Chase invest heavily in their own predictive modeling systems.

The Broader View: AI’s Forecasting Frontier

Falcon TST underscores a major trend in fintech and enterprise AI: the convergence of predictive intelligence and operational decision-making. As global markets become more volatile and data-rich, companies are betting that smarter forecasting — driven by large-scale AI — could mean the difference between thriving and surviving.

If Falcon TST continues to deliver on its early promise, Ant International may not just be predicting the future — it could be shaping how the world prepares for it.