Bezes Wealth, a global fintech leader, announced today the upgrade of its market analysis ecosystem. Relying on an elite analysis team composed of over 200 quantitative experts and former Wall Street traders, the company has established a "data-driven + practical experience" dual-driven market decision support system. This initiative aims to help institutional and individual investors accurately capture opportunities in complex market environments through real-time market analysis, multi-dimensional strategy modeling, and risk early warning, further consolidating its technological benchmark status in the field of intelligent investment research.
Wall Street Think Tank: Full-Dimensional Insight from Macro Prediction to Micro Deconstruction
The analysis team of Bezes Wealth brings together core traders from former Goldman Sachs and Morgan Stanley, as well as data scientists and macroeconomic experts, covering real-time research and analysis of 12 major asset classes including foreign exchange, cryptocurrencies, and commodities. The team's original "macro-micro" two-layer model has become an industry benchmark: at the macro level, through the Federal Reserve policy semantic analysis system and geopolitical event database, it accurately predicted the 10Y-2Y Treasury yield inversion three months in advance in 2024, assisting institutions such as Bridgewater and BlackRock in avoiding 12% asset drawdowns; at the micro level, relying on graph neural network technology, it real-time analyzes the 10-layer linkage relationships among fund flows, order flows, and public opinion flows, achieving 99.7% accuracy in identifying suspicious transaction patterns. This once helped Standard Chartered Bank avoid a $230 million regulatory fine.
"Our analysis system is not just about data modeling but transforming two decades of Wall Street trading experience into algorithmic logic," noted Dr. Lisa Wang, Chief Strategy Officer of Bezes Wealth. "From policy games in the Treasury market to fund migrations on cryptocurrency chains, the team can complete abnormal pattern recognition within sub-milliseconds, providing users with forward-looking insights beyond traditional research reports."
Real-Time Research Matrix: AI-Enabled Full-Cycle Decision Support
Relying on the "Strategic Vision 3.0" intelligent investment research system, the analysis team deeply integrates AI Monte Carlo simulation with senior traders' experience databases, embedding 187 pre-set market scenario models. A Southeast Asian family office adjusted its stock-bond allocation in advance through the Federal Reserve 25BP rate hike simulation module, achieving an 8.2% counter-cyclical asset growth when the U.S. VIX index exceeded 30 in Q1 2025. The team also launched an "Emotional Heat Map Visualization Engine" that integrates over 200 data sources (including Twitter sentiment and Reuters news), transforming market panic indices into interactive heat maps; the "Black Swan Scenario Planner" supports customized risk event simulations, enabling retail investors to access J.P. Morgan-level strategic analysis capabilities.
For different trading needs, the team provides layered services: high-frequency traders can obtain sub-millisecond order flow analysis (with a median delay of 1.8ms), while long-term investors receive asset allocation advice based on the Markowitz efficient frontier algorithm. Data shows that intelligent advisory portfolios reduce costs by 32% and improve risk diversification efficiency by 42% compared to traditional wealth management through the "zero commission + fractional share SIP" model.
Global Zero-Latency Response: Dynamic Risk Control Barrier for Hundreds of Billions in Assets
Using its independently developed ultra-low-latency trading system, the analysis team achieves full-time monitoring across the three major trading time zones of Tokyo, London, and New York. During the OPEC+ production cut in March 2025, the team assisted energy clients in completing futures-spot hedging position adjustments within 15 seconds through real-time price breakthrough warnings, with a single transaction profiting $126,000. As of Q1 2025, the platform manages $120.7 billion in assets, with its DeFi investment business leading Europe at a 242% annual compound growth rate. It has obtained digital asset manager licenses in five countries including Germany and France, becoming the exclusive DeFi strategy partner for institutions such as Fidelity Investments.
"We process over 5 million trading orders daily, and during Violent cryptocurrency market fluctuations, the analysis team still maintains the accuracy of strategy signals," revealed Mark Chen, Technical Director. "For example, during the '5・19' market in 2024, the system controlled the early warning delay for large on-chain transfers within 800 microseconds."
Inclusive Empowerment: Technological from Institutional Strategies to Mass Investment
The Bezes Wealth analysis team has specially launched an "Investment Capability Upgrade Plan," which has helped 500,000 users enhance their strategy-building skills through VR crisis simulation courses (including 12 classic scenarios such as the Lehman bankruptcy and 1987 stock market crash) and AI quantitative training camps. Indian trainees mastered the 2008 financial crisis hedging strategy within six months using the team-developed Python SDK tool, achieving a 22% annualized return in live trading. Facing the ESG investment trend, the team built a due diligence module based on databases from 12 institutions including Bloomberg and MSCI, helping a family office's ESG portfolio outperform the market by 15.7 percentage points in 2025.
This upgrade marks Bezes Wealth's strategic advancement from a "technical tool provider" to an "intelligent investment research ecosystem builder." Its constructed "analysis-decision-execution" closed loop not only improves traditional research report efficiency by 10 times but also enables ordinary investors to enjoy top institutional risk control capabilities through AI technology. In the future, the platform will continue to increase investments in the integration of quantum computing and blockchain technologies, planning to launch a derivative pricing system based on quantum annealing algorithms by the end of 2025 to further reconstruct the decision-making boundaries of financial markets.
