The finals of the `2026 AFAC Financial Intelligence Innovation Competition` recently concluded. Out of the 46 teams that made it through, 24 in the “Challenge Group” and 6 in the “Startup Group” advanced to the next round. This competition created a platform for dialogue among policies, academia, industry, and capital through “conferences, exhibitions, and competitions,” aiming to address challenges related to scenarios, capital, and compliance in the implementation of AI finance. At the technical level, although the capabilities of large models have improved, there are still limitations due to幻觉 issues; financial core transaction decisions still rely on traditional models. The general Frontier Model and specialized Agent continue to evolve simultaneously, with industry focusing more on the commercial verifiability in real-world scenarios. Judges pointed out that while the entry threshold for startups has decreased, the business threshold has increased. Investors no longer prefer “grand narratives” but prefer mature projects that can improve industry efficiency. On the policy level, the 2026 Government Work Report for the first time proposed “creating a new form of intelligent economy,” treating financial intelligence as an essential task for a strong financial sector, with the goal of bridging the digital divide and embracing the super cycle of technology and industry.
Ant GroupBeijing Zhiyuan Artificial Intelligence Research InstituteFudan UniversityPuyue ChinaRelay FundSEE FundTsinghua UniversityTuring Intelligence Research Institute
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Ant Group1
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Beijing Zhiyuan Artificial Intelligence Research Institute1
The finals of the `2026 AFAC Financial Intelligence Innovation Competition` recently concluded. Among the 46 shortlisted teams, 24 “Challenge Group” teams and 6 “Startup Group” teams stood out. This year’s competition adopted a dual-track format, creating an ecological platform for dialogue among policies, academia, industry, and capital through “conferences, exhibitions, and competitions,” aiming to address challenges in AI finance implementation related to scenarios, capital, and compliance. At the technical level, large model capabilities continue to improve but are limited by issues such as hallucinations; core financial transaction decisions still rely heavily on traditional models. In terms of applications, general Frontier Models and specialized Agents are evolving simultaneously, with industries now focusing more on the commercial verifiability in real-world scenarios. Review experts generally noted that while the entry barrier is low, the business barrier has increased. Investors no longer pay for “grand narratives” but prefer mature projects that can improve industry efficiency. On the policy level, the 2026 Government Work Report for the first time proposed “creating a new form of intelligent economy.” Financial intelligence has become an essential task for a strong financial sector, aiming to bridge the digital divide and help capture the super cycle of technology and industry.