Ant International has launched Falcon Time-Series Transformer (TST) AI Model 2.0, its newest TST model to deliver more accurate forecasting in real-world FX risk management for cross-border payments. The FalconTST 2.0 model is said to demonstrate State-of-the-Art (SOTA) performance on the Mean Absolute Scaled Error (Metric), one of the most critical metrics used to evaluate time-series models.
The model scored a 0.666 MASE score and is said to surpass other TST foundational models from global tech-leading companies.
Traditional forecasting systems build separate models for different tasks. The FalsonTST model learns common patterns like cycles, trends, sudden shifts, and seasonality from data like finance, energy, and retail. Despite being different industries, there are often commonalities in their underlying temporal structures.
Jiang-Ming Yang, Chief Innovation Officer, Ant International, shared,
“Large language models have shown how AI can understand and generate information. FalconTST is about another capability that businesses increasingly need: understanding how the world changes over time, and anticipating what comes next.”
Kelvin Li, General Manager of Platform Tech and Senior Vice President, Ant International, added,
“FalconTST helps global businesses — including our own — manage complex cash flow and FX exposure, so they can manage cross-border transactions with greater confidence. With FalconTST 1.0, clients saw real operational value and cost savings from better forecasting.”
FalconTST was first deployed internally at Ant International to manage cash flow and FX exposure on an hourly, daily, and weekly basis.
It was later integrated by banks like Barclays, Citi, Deutsche Bank and Standard Chartered into their respective hedging models, with the aim of improving cash flow forecasting and FX liquidity management capabilities.
More industry applications are expected for FalconTST 2.0, including demand forecasting for supply chain management for e-commerce platforms and predictive operations management for the aviation industry.
Featured image edited by Fintech News Hong Kong based on an image by rezaazmy on Magnific
