How AI and quantum technologies are transforming the financial industry
  • The financial services’ vast well of data and communications means the industry both benefits and is vulnerable to harm by artificial intelligence (AI).
  • Fusing AI and quantum technologies (AQ) will enable fast data analytics while vastly improving cybersecurity – a game changer for the financial industry.
  • Integrating AQ technologies still requires groundwork, including research, talent and infrastructure, as well as vigilance around regulatory and ethical considerations.

By Colin Bell and Jack Hidary

Artificial intelligence (AI) drives significant change in the financial services industry faster than many other sectors. The financial sector’s high density of data and communications makes it ripe for both improvement and attack by AI tools. Even greater transformation in this sector is now coming with the fusion of AI and quantum technologies.

The synergy of these two powerful forces, abbreviated to AQ, will reshape the financial landscape and raise the bar for innovation and security. Institutional investors holding shares in financial institutions increasingly demand reduced risk and greater growth from their portfolio – leveraging quantum and AI technologies is key to unlocking this upside.

In recent years, AI has started to revolutionize the financial industry in ways we could only have dreamed of in the past. Machine learning algorithms can now analyze vast data sets in real time, providing deeper insights into market trends, risk assessments and customer behaviour. AI-driven tools have streamlined operations, improved customer service and enhanced investment decision-making.

AI in finance is not limited to large language models; other essential AI tools still need to be widely discussed and are critical to financial applications. These include knowledge graphs, bayesian learning, AI simulation and time series analysis. Expect to hear more about these AI tools in the near term.
Like any technological paradigm shift, the AI and quantum era brings challenges and tangible benefits. AI and quantum tech are potent challenges to cybersecurity in the financial sector. Hackers are already using AI to develop more effective spearfishing tactics, analyze files containing customer data, mimic customer voices and activate fraudulent transactions using these fake voices. Banks must adopt a zero-trust strategy to protect all their assets as external security perimeters are no longer sufficient.

Financial institutions are also preparing for when large-scale quantum computers with powerful error correction have the potential to crack the asymmetric encryption methods used as the bedrock of communications for the banking industry. That day is still some years away but HSBC and other leading banks are taking proactive steps to modernize cryptography management, including implementing crypto-agility and migrating to post-quantum cryptography to secure infrastructure, financial assets, intellectual property and customer information. Financial institutions should begin the discovery process today to lay the groundwork for this lengthy, complex transition.

Alongside post-quantum cryptography migration, financial organizations can begin exploring quantum key distribution, strengthening their cybersecurity posture in the quantum era. Quantum key distribution leverages the unique properties of quantum mechanics to provide ultra-secure communication channels, ensuring the confidentiality and integrity of sensitive financial information in an age of evolving cyber threats. It can be combined with post-quantum cryptography to protect critical assets or links where defence in depth is required.

The AI and quantum revolution is here

Today’s accelerated hardware, such as NVIDIA’s graphics processing units (GPUs), pair together quantum-inspired algorithms with artificial intelligence to unlock powerful capabilities for financial institutions, including:
  • Risk mitigation: Risk assessment is a cornerstone of the financial industry. Applying quantum-inspired algorithms and AI can accelerate the evaluation of market conditions and portfolio risks. These tools can simulate many more dimensions than often-used Monte Carlo tools – the traditional sampling used in algorithmic decision-making. More comprehensive risk assessments lead to better decision-making and risk management.
  • Fraud detection: In the cat-and-mouse game of fraud detection, quantum machine learning models can improve learning quality to capture criminal or fraudulent transactions better. That means better protection for customers and their assets and reduced operational risk for financial institutions.
  • Portfolio optimization: The heart of investment lies in portfolio optimization. Quantum-inspired algorithms can help financial experts optimize diversification and asset allocation, enhancing the performance and stability of portfolios. This results in better returns and risk management for our clients.
All these tools combined yield a financial institution with greater visibility to tail risks and a higher return on equity. Shareholders of large public financial institutions are demanding more of their portfolio companies and implementing smart programmes with AQ could help meet these expectations.
Integrating AQ technologies requires investment in research, talent and infrastructure. Our industry must also be vigilant about regulatory and ethical considerations surrounding AI and quantum technologies, including thoughtfully implementing quantum-resistant technologies as part of a hybrid cryptographic environment to ensure continued compliance and eliminate biases from the data used to train AI models.
As we step into the future of finance, embracing quantum and AI technologies is no longer optional but necessary. The pioneers who lead this transformative journey will set new standards for efficiency, security and innovation as we advance into the quantum era




Leave a reply

Please enter your comment!
Please enter your name here