Financial modeling systems have an essential part to play in enabling informed decision-making and predicting the future as accurately as possible. However, many of these systems haven’t met financial services firms’ requirements or expectations: this can be because of human errors, flawed assumptions, complex models and a lack of proper documentation and validation.
This has led to a slowdown in finance technology progress: Gartner has found that as many as 69% of transformation projects in the sector aren’t meeting progress targets, and 30% aren’t delivering the benefits expected of them. However, photonic quantum computing is now emerging to break down those barriers to progress.
In this blog, we’ll explore the key ways in which financial modeling is held back, and how photonic quantum computing is enabling optimization, risk reduction and better security.
Perhaps the main problem that has affected financial modeling systems has been that they are too static, and aren’t always capable of reacting to variables and changing events.
The ‘Monte Carlo’ simulation, often used in corporate finance, options pricing and portfolio management, is a good example of this. It involves random samples of data being fed into a simulation over and over again to simulate different scenarios, and use those insights to form the strategy for the best way forward. Where it falls down, however, is that these simulations can’t take into account any wider financial circumstances that may affect performance, such as recessions and bear markets.
Other complexities that can make good modeling difficult include an inability to incorporate non-linear relationships and complex market dynamics, and difficulties processing high-dimensional data.
The recent global market volatility, generated by the trade tariffs imposed by the Trump administration, have highlighted the need for stronger and more agile financial modeling. This type of incident can cause major financial losses for traders and undermine investor confidence, especially if finance firms aren’t able to respond quickly and effectively.
This is where real-time, algorithm-based risk controls can make a huge difference, providing an extra level of protection and insight to guide trading activity in real time. When sudden economic shocks or ‘flash crashes’ take place, they can ensure trades or other activities that could expose the firm or their investors to risk or loss can be prevented.
However, as with other financial models, there are some technical barriers that have made this kind of risk control difficult to implement. These include:
|
High latency that prevents true real-time analysis when market conditions are evolving rapidly |
|
Approximation errors that lead to substantial deviations between predicted and actual market behaviors |
|
Poor integration of alternative data sources, limiting the depth and relevance of the insights and predictions generated |
Photonic quantum computing stands at the very forefront of current technological development, but it won’t be long until it becomes more commonplace in a variety of sectors, including finance.
These computers work by processing information using light particle-based, two-digit qubits (quantum bits) instead of traditional single-digit bits. This enables exponentially faster processing and problem solving for even the most complex of data and statistical challenges, as well as enabling dramatic improvements in scalability and energy efficiency.
Finance firms have already begun to explore photonic quantum computing, and it is proving to be transformative in several key use cases:
From our experience helping finance firms with photonic quantum computing, the best way forward is a clear five-step process:
Early adopters of this technology have encountered some headwinds. Photonic quantum computing still has lots more potential to be explored, so finance firms should be careful and patient in selecting the right use cases, with a clear cost-benefit advantage of deploying the technology to specific financial applications.
This is why targeted pilot projects with clear success metrics can deliver a solid foundation and proof-of-concept for photonic quantum computing, and can pave the way for gradual expansion over time. But to make even these happen, finance firms need access to highly specialized quantum expertise, and reliable partnerships with hardware providers, researchers and industry consortiums alike.
Accessing all of this can be expensive, difficult and time-consuming in-house, meaning a partnership with a quantum and finance technology expert like Ciklum is your best way forward. Get in touch with us today to find out more and discuss your specifics.