Ant International currently deploys the Falcon TST AI Model to forecast cashflow and FX exposure with more than 90% accuracy
Ant International, a leading global digital payment, digitisation, and financial technology provider, has released its proprietary Falcon TST (Time-Series Transformer) AI model, the industry-first Mixture of Experts architecture-based big data model with multiple patch tokenizers, supported by up to 2.5 billion parameters. The model has also achieved state-of-the-art zero-shot results on well-acknowledged long-term forecasting benchmarks, such as absolute mean error rates.
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Deployed internally at Ant International to manage cashflow and FX exposure on an hourly, daily and weekly basis, Falcon TST has achieved accuracy rates of over 90%, and cut the company’s FX costs by up to 60%.
Ant International also collaborated with various industry partners to deploy the model in different use cases, such as in helping businesses mitigate FX cost and volatility, as well as to support airlines in offering more stable, competitive pricing to their customers. With the Airports Council International World’s report estimating that global air travel is expected to reach almost 10 billion passengers in 20251, these applications of AI have the potential to translate to significant cost savings for consumers globally.
Extending the impact of AI-powered forecasting across industries
The model also enables businesses to make various other time-series forecasts, such as weather patterns, calendar events, financial market fluctuations, cross-border traffic data, and more.
“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, Ant International.
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