The morning keynote of the "Global FinTech & Smart Wealth Innovation Summit" was dominated by Ms. Xu Danyi, Senior Wealth-Management Advisor at Hangzhou Enniu Network Technology Co., Ltd. (51 Credit Card). In her first public outing of the two technologies, Xu presented the “Intelligent Wealth-Management Recommendation System Based on Customer Persona v1.0” and the “Multi-Dimensional Data-Driven Asset Allocation Optimization Platform v1.0”, then spent the rest of the session in closed-door talks with executives from banks, securities houses, insurers and fintech firms on deployment and partnership models—triggering an on-site “cooperation rush”.

More than 300 practitioners from across China gathered for the summit, whose theme was “The New Data-Driven Landscape of Wealth Management”. Speaking in the plenary segment, Xu used the title “From Client Understanding to Asset Allocation: End-to-End Intelligent Practice” to dissect two bottlenecks in digital transformation—low precision in personalised recommendations and weak dynamic optimisation of asset allocation. “These pain-points hurt client experience and cap industry-wide efficiency,” she argued.

(Ms. Xu Danyi at the event)

During the live demo, Xu Danyi opened with a step-by-step walkthrough of how the Intelligent Wealth-Management Recommendation System Based on Customer Persona v1.0 operates. Using a real anonymised case, she showed how the engine ingests financial status, spending behaviour, risk appetite and investment goals to build a multi-layered customer persona, then auto-generates a tailored product shortlist in seconds. The giant screen rendered the persona-building and recommendation pipeline in real time, prompting dozens of delegates to snap pictures. A product director from a major commercial bank remarked afterwards that the system’s micro-segmentation capability could finally solve the long-standing mismatch between high-net-worth clients and suitable products.

She then switched to the asset-allocation platform. Where the recommender answers “what to buy”, the platform answers “how and how long to hold”. By fusing macro data, sector trends, market-volatility indicators and risk-return profiles of multiple asset classes, it produces dynamic re-balancing proposals and refreshes them whenever markets or client circumstances shift. A live replay showed the engine re-optimising a client portfolio in under five seconds; the speed drew audible interest from institutional delegates.

Beyond the tech demo, she also used coffee breaks and networking slots to proactively discuss commercial roll-out pathways for the two solutions with prospective partners. Organisers disclosed that at least three institutions signed letters of intent the same day, including the private-banking arm of a nationwide bank and a leading online brokerage. Representatives said the two tools together “close the loop from insight to execution” and could lift both operational efficiency and client stickiness.

In his closing remarks, one industry expert noted that the two releases are “not isolated utilities but parts of an integrated service stack—precision at the front, optimisation at the back”. The host committee echoed that scalable, deployable innovations like these are exactly what the sector needs now.

After the session Xu told reporters: “We want technology to bring financial planning closer to every client’s real needs, while keeping portfolios tuned to market moves and life-stage changes. This is as much a service-mindset shift as a tech upgrade.” She added that the next R&D cycle will focus on cross-institutional data pipes and international-market adaptability to widen the application footprint.

With packed Q&A queues and same-day MOUs, the double launch has lifted Xu’s industry profile and furnished a fresh case study for the deep integration of fintech and wealth management. If rolled out at scale, the tools promise a simultaneous jump in service efficiency and client experience.