量子計算技術與金融業

量子計算是一種基於量子力學原理的計算技術,能在同一時間處理多種可能性,極大提升計算速度和效率。傳統電腦需要數百萬年完成的運算,量子計算可能在數分鐘內完成。隨著技術領先國家在量子計算領域的突破,這項技術正逐漸從理論走向實用化,並預計在不久的將來對各行各業產生重大影響,尤其是對依賴計算的金融業。 

金融業高度依賴複雜的數學模型進行風險評估、投資組合優化及市場定價,而量子計算能快速解決傳統電腦難以處理的問題。例如,它能高效計算金融衍生品的價格模型、模擬市場波動並優化高維度投資策略。此外,量子計算能對海量市場數據進行即時分析,提取模式並預測市場走勢,為交易提供更精準的數據。同時,它能顯著提升演算法交易的效率,幫助機構在短時間內搶佔市場先機。對資產管理而言,量子計算能快速處理多變量的資產組合,找到收益與風險的最佳平衡點,協助投資者實現資本增值。  

然而,科技的風險與機遇並存,量子計算也不例外。最大挑戰是傳統加密技術的脆弱性。目前金融機構廣泛採用的加密技術基於數學計算的複雜性,而量子計算能快速破解這些技術。一旦攻擊者利用量子計算破解加密密鑰,金融交易、用戶隱私與系統安全將面臨重大威脅。此外,金融業處理大量敏感數據,如客戶身份、交易記錄和資金流動,若量子計算被惡意使用,可能導致數據洩露或交易遭操控。  

一項模擬測試顯示,擁有足夠強大量子電腦的攻擊者可在數分鐘內破解2048位RSA加密技術,從而竊取交易數據或篡改支付內容。這表明量子計算可能引發高額資金損失、影響客戶信任甚至引發系統性金融危機。因此,金融機構需提前採取措施應對量子計算的潛在威脅。  

應對量子計算帶來的風險,金融機構應採取以下措施:首先,逐步替換現有的加密技術,採用抗量子加密演算法,這些技術不依賴傳統數學難題,能有效抵禦量子計算的威脅。其次,實施分層次的安全策略,包括數據分段加密、即時威脅偵測和縱深防禦,即便某一層加密被攻擊,仍能限制損害範圍,確保系統安全。最後,模擬量子攻擊場景並測試新型加密方案的有效性,確保在量子計算普及後能迅速切換到量子安全技術。  

總之,量子計算的興起為金融業帶來了巨大的機遇,但也伴隨著資訊安全的挑戰。傳統加密技術失效和數據隱私威脅是金融機構面臨的主要風險。然而,透過部署後量子加密技術和強化多層次防禦機制,金融業可有效降低量子計算的潛在風險。在量子時代真正來臨前,提前佈局是確保金融系統穩定、安全的關鍵。 

尹展軒 
Senior IT Consultant

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Secure, Reliable, High-performing digital systems

At Ringus Solution Enterprise Limited, we know that in today’s digital-first world, two things matter more than ever: security and performance. That’s why our Technical Services Team focuses on helping businesses protect their systems from cyber threats and ensure their applications run smoothly under all conditions.Security breaches can be devastating—leading to data loss, reputational damage, and costly downtime. Our Technical Services Team specializes in technical security assessments that help businesses stay one step ahead of potential threats. We don’t just run automated scans and call it a day. Instead, we take a comprehensive approach that includes in-depth vulnerability assessments, hands-on penetration testing, and detailed security configuration reviews. Our goal is to uncover vulnerabilities before malicious actors do, and to provide clear, actionable recommendations to strengthen your system's defenses.We also understand that a secure system must also be a high-performing one. That’s why we provide application performance testing as a core part of our services. Whether you're launching a new platform or scaling an existing one, we help ensure your application can handle the pressure. Our team conducts rigorous load and stress testing to simulate real-world usage, analyzes response times and throughput, and identifies bottlenecks that could slow down your users. We also assess scalability—so your systems grow as your business grows.What sets our team apart is our commitment to delivering not just technical reports, but real solutions. We translate complex findings into practical recommendations, empowering your business to take action quickly and confidently. With a team of experienced cybersecurity specialists and performance engineers, we combine technical expertise with a deep understanding of business needs.At Ringus, our mission is clear: help our clients build secure, reliable, and high-performing digital systems. If you're looking to strengthen your defenses or optimize your application performance, our Technical Services Team is ready to support you with precision, professionalism, and a proactive approach.

AI Management Standard

At Ringus, we believe that responsible AI adoption is not just a trend—it’s a necessity. With AI transforming industries, leading organizations / entities like NIST, ISO/IEC, HK DPO, the EU, and the UK ICO have published critical guidance / frameworks / standards to ensure AI is ethical, transparent, and risk-aware.Key Best Practice / Standard for AI Deployment and Governance:👉 UK ICO Guidance on AI and Data Protection and AI and Data Protection Risk Toolkit – A reference guidance and toolkit to help businesses avoid privacy violations and bias in AI systems.👉NIST AI Risk Management Framework (AI RMF 1.0) – A structured approach to manage risks to individuals, organizations, and society associated with AI.👉EU AI Act (2024) and Relevant Guideline / Codes of Practice (Under Drafting) – A legal requirement that sets out a clear set of risk-based rules for AI systems and general-purpose AI models. Relevant guideline and Codes of Practice are under development to provide guidance on compliance of regulation.👉Ethical Artificial Intelligence Framework and Hong Kong Generative Artificial Intelligence Technical and Application Guideline  –  A framework that provide practical guidance on embedding ethical principles into AI adoption, focusing on fairness, transparency, and accountability.👉ISO/IEC 42001:2023 – The first global AI management standard, which provide a comprehensive, certifiable framework to establish, implement, maintain, and continually improve trustworthy AI management systems for ensuring responsible, ethical, and secure AI development and deployment.Why Compliance Matters✅ Builds Trust – Customers and regulators demand transparent and fair AI.✅ Reduces Legal Risks – Non-compliance with frameworks like the EU AI Act can lead to heavy fines.✅ Prevents Reputation Damage – AI failures, such as AI bias and privacy breaches, can harm your brand permanently.We help businesses integrate AI responsibly—aligning with global standards and requirements to minimize risks and maximize trust. Feel free to connect with our team for actionable insights on secure and ethical technology adoption.