Digital banks: Are you into the most innovative technology of 2022?
And if you’re not into, maybe now is the time to start thinking about quantum computing. You can do a fresh start reading my previous article where I talk about why we have to consider quantum computing a must in 2022 tech stack.
I know there are many people, like me, who are very enthusiastic about the possibilities of quantum computing in digital banks. So, let’s dive into.
Picking up where I left off, today I’ll focus on 3 financial applications where you can make a differential service to your clients using quantum computing advantages:
- Options pricing.
- Portfolio optimization.
- Fraud detection.
Options Pricing
In american options, we might want to forecast the best price in which we can buy/sell the underlying asset. This could be modeled as a one day at a time evaluation and in each one, evaluate if in that day and price, it’s the best time to sell/buy the underlying asset.
Because this includes a dynamic programming problem where exists different stopping times this can be generally simulated using least-squares Monte Carlo method (LSM).
The biggest downside here is that as stopping times increase, it also does the computing time. So, what can we do when we need a boost in our processing speed? Yes, quantum computing!
Different quantum approaches on this method have resulted in a quadratic speedup in the runtime compared to the classical LSM algorithm.
Quantum computing might also be applied on European/Asian options, where a well-known model called the Black-Scholes formula, can take advantage of Quantum Computing and also have consequently an exponential speedup in processing time.
Think about it, with this processing power, you could provide an almost immediate option pricing to your clients.
Portfolio Optimization
While Option Pricing may be solved with stochastic modeling such as Monte Carlo method, the best selection of assets for your portfolio could be modeled as an optimization problem.
In this case, we have a set of assets and we want to select a subset of them which give us the best return taking into account our risk aversion.
Modern portfolio theory solves this problem using Markowitz model which can be solved in a Classical Computer, but, with a higher set of data you’ll end up with a higher calculation time. So, for this case, we have a lot of implementations demonstrating that Quantum computing is remarkably fast solving optimization problems.
Furthermore, there is a quantum computer designed with an specific technology called Quantum Annealing which performs optimization tasks extremely fast, even more than others quantum computers. You could give it a shot through Amazon Braket services which provides a 24x7 availability to use this quantum computer.
With this in mind, you might provide a faster tool to your clients and let them choose a set of assets and give them almost instantly the best portfolio for them.
Fraud detection
Residing in the core of the financial industry, we will found an essential process: fraud detection.
Nowadays, fraud detection is a big responsability in every Technology and Data Analysis area of any digital bank. They tend to use machine learning and artifical intelligence technics to provide automatic detection of frauds anomalys.
Commonly, they may use a subset of machine learning technics called unsupervised deep learning. But, when these technics start to use big chunks of data, they start to slow down their processing time.
Here is where Quantum Computing come handly, with quantum implementations of these technics such as k-means, PCA or boltzmann machines.
With a bigger power of processing, fraud detection could take customer experience to the next level avoiding any time consuming manual fraud detection by replacing it with automatic detection powered by quantum advantages.
More quantum financial services
As part of a team responsible of a wide range of financial services in Ualá, every day I get in touch with different bussiness units where I see a lot of opportunities for quantum computing application.
That’s why, in this article, I tried to reach different aspects of financial services, so it provides a wide-open view of quantum computing capabilities no matter which digital bank you are into.
But this is not all in quantum financial services, there is more areas where you can exploit quantum technology, such as:
- Asset Pricing.
- Collateralized debt obligations.
- Creditworthiness.
- Implied Volatility.
- Optimal Arbitrage.
- Risk Modeling.
- Swap Netting.
With this wide range of use cases, are you ready to take your digital bank to the quantum computing level?
