As financial technology continuously evolves in today’s AI era, a growing number of initiatives are dedicated to cultivating the next generation of AI talent. One such program, the AFAC Financial Intelligence Competition – launched by Ant Group in collaboration with leading universities such as Peking University, Nanyang Technological University in Singapore, the University of Hong Kong – is gaining traction as a major platform integrating AI with real-world financial use cases.
Now in its third year, the AFAC (short for Advanced Fintech AI Competition) is inviting university students and researchers worldwide to solve actual problems faced by the finance industry.
“This competition stands out because it bridges vertical industry challenges with academic training,” said Dawei Cheng, associate professor at the School of Electronics and Information Engineering at Tongji University, a long-term partner in the competition. “Students aren’t just doing simulated exercises; they’re applying what they’ve learned to real-world problems faced by companies like Ant.”
Unlike typical hackathons or startup pitch competition, AFAC presents curated problem sets sourced directly from corporate pain points, then invites teams to develop AI-driven solutions. To connect scholars even more with the industry, Cheng expects the winners could get the opportunity to test their algorithms with the original challenge setters, potentially leading to real-world deployment.
“There’s potential to take student-developed algorithms through A/B testing in enterprise environments,” Cheng said. “That’s how we close the last mile between research and application.”
Co-organized with top universities, the annual competition is now open for registration, offering two distinct tracks tailored to technical and entrepreneurial participants. The challenge is designed to strengthen cross-disciplinary innovation in AI, financial services, and broader industrial applications.
This year’s themes again highlight its dual focus on AI innovations and financial services. Participants in the Developer Track or Startup Track, tackle real-world scenarios and technical challenges sourced from financial services sector – offering a lens into how AI is being embedded in industry applications. This year’s topics reflect broader shifts in digital finance:
- Forecasting subscription and redemption cycles for funds
In the highly active wealth management sector, predicting investor behavior over long periods is vital for managing liquidity. This task mirrors challenges faced by asset managers globally, especially in volatile markets. - Cross-validating insurance policies from multiple data sources
With the insurance industry undergoing rapid digital transformation, ensuring consistency across disparate systems and formats is key to minimizing fraud and operational risk – a universal challenge for insurers. - Optimizing long-chain reasoning in financial decision-making
As AI tools increasingly support investment and credit decisions, compressing complex logical reasoning chains without losing accuracy could improve both automation and explainability – an area where regulatory interest is growing worldwide. - Generating multimodal financial reports with AI agents
By integrating text, tables, and charts, AI-generated financial reports aim to accelerate analyst workflows. This reflects a trend seen globally in applying generative AI to augment knowledge work in capital markets.
Meanwhile, the Startup Track invites university-based entrepreneurs to explore how AI can unlock new use cases at the intersection of finance and emerging industries. Participants are asked to propose AI-driven business solutions across four forward-looking themes – each aligned with current global fintech trends:
- Enhancing productivity in financial services
This theme encourages innovations that automate knowledge work or enhance digital productivity. Globally, this area has drawn strong VC interest, with startups building AI copilots for fields from legal tech to financial modeling. - Promoting inclusive finance
This direction aligns with global efforts to expand financial services access through technology, especially for underbanked populations. Solutions might include credit scoring with alternative data, micro-insurance platforms, or AI-powered financial literacy tools – all seen as high-impact areas in emerging markets. - Advancing financial data utilization
With increasing attention to data-driven finance, this theme invites startups to explore how AI can extract, summarize, or augment structured and unstructured financial data. Use cases include AI-generated insights from earnings calls, ESG disclosures, or real-time transaction data. - Supporting elderly financial services
As aging populations become a demographic concern across Asia and Europe, fintech solutions tailored to seniors are drawing attention. This might include voice-based interfaces for banking, AI-driven fraud alerts, or personalized retirement planning tools – a niche but growing market.
This track emphasizes not only working prototypes, but also business viability. Participants must submit both demos and commercialization plans. Cheng emphasized that Ant’s deep roots in both AI model development and finance give the competition a strong applied focus.
While asked about how AI has changed the industry and their lives, Cheng and his student recognize both the advantages and limitations of generative AI. Zhu, a senior majoring in computer science at Tongji University and a first time AFAC participant, said that tools like ChatGPT and other AI models are changing how students learn, but not replacing the fundamentals.
“AI improves efficiency in coding and debugging,” Zhu said, “but it doesn’t replace core thinking. It helps us learn faster, not skip the process.”
He advocates that the ideal talent in this field should have both deep technical expertise and wide interdisciplinary understanding. “Some of our strongest AFAC teams have dual degrees in computer science and finance, or some even with management. Those combinations are what allows them to really solve complex, domain-specific problems.”
As the global AI and fintech landscape evolves, Cheng believes competition like AFAC also point to a shift in how universities and tech companies co-innovate. For example, by exposing participants to challenges sourced directly from Ant Group’s financial ecosystem, AFAC offers a rare opportunity for participants to gain real insight into AI-fintech fusion.
The AFAC competition is also a key part of the 2025 Inclusion·Conference on the Bund, a major platform for showcasing cutting-edge AI applications in financial services. Finalists will present their solutions on the Bund stage in Shanghai, where top awards will be given in front of global industry leaders. With global talent participating this year, the competition aims to provide a platform for international collaboration, experimentation, and career-building in one of the world’s most dynamic digital finance markets.
