At the core of modern banking is high-end computational power that enables efficient processing of complex financial data. When banks need to process billions of transactions daily, verify customer details and address risk factors, it’s not unlikely to ask a question: “How do banks handle such complex tasks at a fast speed?”, “Are supercomputers used in banks?”.
The answer lies in the complex computational process banks use. Let’s find the answer in this article.
Defining Supercomputers and Their Capabilities
Supercomputers are specially designed machines for performing highly advanced computations, simulation and modelling. From scientific research to modelling the cosmos, a supercomputer can make all complex tasks seamless, at a very high speed measured in floating-point operations per second (FLOPS).
They are mainly used in engineering, scientific research, and other sectors that need accurate and high-speed processing. At the core of this massive machine is parallel processing that allows supercomputers to process multiple computational tasks across thousands of processors at once.
Two of the most powerful supercomputers are El Capitan and Aurora. El Capitan features a processing speed of 1.742 exaflops, equivalent to 1.742 quintillion (10^18) FLOPS. On the other hand, Aurora, an exascale, can process over one quintillion tasks at a time at a speed of 180 petaFLOPS which would be around the speed of Summit.
Mostly used for scientific purposes, these machines require:
- Massive power supply systems
- Cooling processes
- Specialised facilities for installation and maintenance
Needless to mention, the computational power of these supercomputers is enormous and they can handle such complex tasks you can never imagine your traditional computer to perform ever.
But, do these massive machines have any use in the banking sector?
Banks don’t use supercomputers for their regular operations. Instead, they take a hybrid approach, using advanced high-performance computing (HPC) processes for their business-critical analytics tasks, such as threat detection, and mainframes for their core operations.
The Evolution of Computing in Banks: From Mainframes to High-Performance Computing
Since the mainstream computing process has been developed, the banking system has evolved radically. It all started with mainframes that transformed the banking system. Let’s have a quick glimpse of the evolution of computing in banks.
The Mainframe Era
Banks have been using mainframes since the 1960s. These highly powerful and reliable computers are the backbone of the banking system handling the high-volume transaction processes like credit card transactions. According to recent data, 92 of the top 100 banks globally still have mainframes for their core operations.
Why have mainframes been persisting for so long? The answer is the security, reliability and processing capabilities they offer. These specially designed computers can manage thousands of users and millions of transactions all at once and without any fail! When financial institutions like banks need non-negotiable uptime, using mainframes for core operations has been standing as a strategic imperative.
The Transition to High-Performance Computing
Banks striving to streamline their business operations are fast moving their workloads to High-performance computing (HPC) systems from mainframes. In a report published in 2023, Forbes found over 80% of banks planning to move some of their workloads from mainframe to cloud-powered HPCs, a jump from 30% previously. This is not a complete shift of workload, rather a hybrid approach that combines the use of both mainframe and HPC systems in banking operations.
These systems have gained momentum among financial institutions like banks since the early 2010s, when risk management and big data analytics came into the mainstream in the global marketplace.
HPC systems are widely used in applications like:
- Fraud detection
- Regulatory compliance
- Algorithmic trading
Even though you can’t classify these systems as supercomputers, they are machines with advanced computational power compared to typical enterprise-grade servers.
Practical Applications: How Banks Utilise Supercomputing Technology
As we have said, banks don’t use supercomputing in their daily operations. Supercomputers are usually for scientific purposes. However, you will find most banks using high-performance computing systems to streamline their processes. Let’s elaborate on the applications of HPC systems in banking operations:
Risk Assessment and Management
Advanced computing systems are great at running advanced risk models to evaluate the risks associated with credit, market and financial operations. These tools implement Monte Carlo simulations, a computational technique that uses repeated random sampling, to assess the likelihood of different results based on a wide number of probable cases. It thus helps track down potential threats and vulnerabilities.
Fraud Detection and Prevention
With high-end computing systems in place, it becomes easier for banks to use advanced machine learning algorithms and assess transaction patterns in real-time. Thus, they can efficiently find out any suspicious or fraudulent activities.
High-Frequency Trading
Another notable application of high-performance computing in banking is algorithmic and high-frequency trading. With these systems in place, financial institutions can efficiently analyse market dynamics and make data-driven decisions, faster than any human!
This speed has caused a boom in the global high-frequency trading market. It is expected to hit a staggering 74.35 billion by 2032 at a CAGR of 15.1%, up from $20.97 billion in 2023.
Most recently, a team of future-focused scientists used supercomputing power to optimise codes and transform the financial market analysis process. Researchers reported these findings to be highly beneficial in transforming the design and implementation processes of trading algorithms.
Big Data Analytics
Banks need to collect and process a massive volume of structured and unstructured data from multiple sources daily. Thus, they can better evaluate market dynamics and trends to identify business opportunities and offer personalised banking experiences to their users. Using HPCs to power AI and ML analytics systems makes the process seamless and more accurate, facilitating data-based and on-time decision-making.
Comparing Technologies: Mainframes vs. Supercomputers in Financial Institutions
Mainframes: The Banking Bedrock
Banks still use mainframes for:
- Handling high voluminous input/output banking operations
- Processing transactions reliably
- Enabling regulatory compliance
- Enabling backward compatibility with legacy tools
The excellent reliability, performance, security and scalability mainframes offer have made them staple in the banking sector, despite many predictions of their demise.
High-Performance Computing Systems: The Analytical Powerhouses
High-performance computing systems are great at:
- Processing thousands of datasets simultaneously
- Modelling complex mathematical computations
- Performing data analytics and helping design ML applications
The Broader Spectrum: Where Supercomputers Are Mainly Used
As we know, banks typically don’t use supercomputers. But where are these highly powerful machines used?
Scientific Research
Supercomputers were developed to facilitate scientific research. They have applications in:
- Genomics
- Climate modelling
- Physics simulation
- Developing complex engineering designs
Government and Defence
The powerful processing and computational power of supercomputers play a critical role in facilitating the tasks in the government and defence sector. They widely use these massive powerhouses for complex simulation, data analysis and bringing new technologies to life. For example:
- Government agencies use supercomputers for:
- Cosmic modelling
- Understanding the pattern of climate change
- Statistical analysis for economic forecasting
- The defence sector uses supercomputers to:
- Design and validate powerful weapons
- Strengthen their defence mechanism
Energy Sector
These machines are also used in the energy sector to:
- Simulate nuclear reactors in nuclear power plants
- Optimise power grids
The Quantum Frontier: Banking’s Next Computing Revolution
While yet to come to the mainstream, it’s predicted that quantum computing is the next superpower that would revolutionise banking systems. Research is ongoing to develop real-life applications of quantum computing in banking.
Many top-tier financial institutions, like JP Morgan and HSBC, are already investing in developing in-house quantum computing teams to transform their banking operations.
The Future of Supercomputing in Banking and Beyond
To sum up, that day is not a long way off when the boundaries between supercomputing and financial operations would blur making banking more reliable, prompter, accurate and transformed. Operations like algorithmic trading, risk assessment, threat detection, etc., would be more efficiently done and double down the capabilities of mainframe systems.
While banks don’t typically operate true supercomputers in the traditional sense, the financial sector continues to push the boundaries of computational capability. High-performance computing systems power critical functions like risk assessment, fraud detection, and algorithmic trading, complementing the reliable transaction processing of mainframe systems.
