A brief history of quantum computing

The spark of quantum computing was struck by Richard Faynman. In 1981 at MIT, he presented the following quandary: classical computers cannot simulate the evolution of quantum systems in an efficient way. Thus, he proposed a basic model for a quantum computer that would be capable of such simulations. With this, he outlined the possibility to exponentially outpace classical computers. However, it took more than 10 years until a special algorithm was created to change the view on quantum computing, the Shor algorithm.

In 1994, Peter Shor developed his algorithm allowing quantum computers to efficiently factorize large integers exponentially quicker than the best classical algorithm on traditional machines. The latter takes millions of years to factor 300-digit numbers. Theoretically, the Shor algorithm is capable of breaking many of the cryptosystems used today. The possibility to break cryptosystems in hours rather than millions of years using quantum computers lit a fire of interest for quantum computing and its applications.

In 1996, Lov Grover invented a quantum database search algorithm that presented a quadratic speedup for a variety of problems. Any problem which had to be solved by random or brute-force search could now be done 4x faster.

In 1998, a working 2-qubit quantum computer was built and solved first quantum algorithms such as Grover’s algorithm. The race into a new era of computer power began and more and more applications were developed.

Twenty years later, in 2017, IBM presented the first commercially usable quantum computer, raising the race to another level.

A brief introduction into quantum computing

As classical computers are based on bits, a quantum computer is based on quantum bits, called qubits for short. Qubits are physically derived from small quantum objects, such as electrons or photons, where a pure quantum mechanical state such as the spin indicates the ones and zeros, as are used in classical computers.

Nevertheless, quantum computing is fundamentally different from classical computing. It is based on two laws in the quantum mechanical world: superposition and entanglement. A quantum superposition state of two pure states is a linear combination of these states with the coefficients representing the probability distribution of the pure states inherent in their quantum mechanical nature. Quantum entanglement describes the “entangled interaction” of qubits so that you cannot describe the state of two entangled qubits independently; if you measure one qubit, the measurement result of the other qubit is determined on the outset. Measurement results on qubits are still stochastic due to their quantum mechanical nature. These two effects in quantum computing, superposition and entanglement are responsible for the first step in the exponential speed boost provided by quantum computers.

The speed boost of quantum computing, in short, starts with a “spread” of all given pure states into superposition, so that every state is equally likely to appear. The second step is to “translate” the solution of the problem defined by a quantum mechanical algorithm into circuits using a set of qubits and quantum mechanical elementary gates. Additionally, oracles implement a Boolean function on a set of qubits representing the input of the problem. Final measurements on the set of qubits, with a high number of repetitions, provides a probability distribution as an interpretation of the final state being a superposition of all pure states of all involved qubits. The output of the quantum algorithm is a single pure combination of the set of qubits derived from the distribution; for example, one could take the combination with the highest frequency. Thus, quantum computing can only achieve a better performance compared to classical computers if an analysis of the quantum algorithm proves correct results and shows a lower complexity in the expected number of steps a set of gates and oracles needs to be applied. It’s all about the algorithms!

Quantum computing in financial services

Financial services are strongly dependent on IT because of the banks’ reliance on security and the necessity to deliver differentiated services in a very short timeframe. Quantum computing could, for instance, change the finance sector in the following areas:

Cybersecurity is one key word regarding emerging technologies. New technologies require and drive new methods of encryption. However, quantum computers implementing Shor’s algorithm are eligible to open up wide-scale and systematic breaches of security- and governance-related mechanisms using current cryptosystems. If the market participants do not properly anticipate and manage their crypto-mechanisms, such developments would be disastrous for them.

Another interesting topic in banking is algorithmic trading. Becoming proficient in running these algorithms combined with high-frequency trading may offer a significant advantage over competitors.

Identifying risks and calculating the impact of risks on business and revenue is one of the key tasks every bank and insurance company is facing. Conducting risk analyses using classical computers with long and often unpredictable processing times bogs down banks and insurance companies in the proper operation of their business. Deployed on risk calculations requiring a huge amount of data to be processed within a short time, the quantum computer can show its full potential.

New fraud detection techniques are based on pattern recognition algorithms as a possible part of the machine learning subject. For classical computers in the complex mathematical world the banking sector is operating in, this is time-consuming and needs a lot of computer power to process such algorithms. Using fast-learning algorithms based on quantum computers, fraudulent activity may be detected based on the huge big-data amount that was inconceivable using classical computers.

With the blockchain technology, a new hype of cryptocurrencies has arrived in the IT world in the last years. It is important to notice that the basic public-key/private-key encryption of the blockchain technology is not quantum-safe. In theory, with a quantum computer, it is easy to de-crypt public keys to determine their private keys and steal all de-crypted information. Analogously, quantum algorithms can de-crypt RSA-keys, the most common cryptography technique. If a bank is not quantum-ready when quantum computers are capable of de-crypting RSA-keys, we will witness the largest bank robberies in the history of mankind.

Technical issues with current quantum computers

Quantum computers are currently available on a small scale with a small number of qubits. To be competitive with classical system, quantum computers need to scale up. Although this issue has improved dramatically over the last decades, further progress in the development of quantum computers requires addressing other technical issues such as quantum error correction. It is fundamentally difficult to scale quantum computer chips because quantum information cannot be copied and subsystems are not independent, leading to design trade-offs that are global by nature. However, superconducting qubits are more and more showing the potential to overcome these hurdles and are starting to evolve as commercially usable in quantum computers.

Opportunities in quantum-ready businesses

Improving business may be achieved by increasing revenue, reducing costs or lowering investments in infrastructure. The past has shown that new technology in the digital era has an exponential impact on economic indicators: a 1% gain in product quality may lead to an exponential growth in the terms of revenue.

Early integrators of quantum computers into their IT structure will benefit even from a modest increase in computer speed and will reap the rewards. Rivals who fear the risk and wait until the market will push a change will have high entry barriers to match the same quality of services and products. This can lead to a decrease in market share.

Strategic partnerships can help businesses in adapting quantum technology into ordinary business processes and migrate smoothly into the quantum age. The cloud-based usage of quantum computers will improve and accelerate businesses and show their full potential whenever required.

Conclusion

Quantum computing will soon come into the state of quantum supremacy. When this will happen, banks and insurance companies should be quantum-ready and should have considered all necessary steps to include quantum computers smoothly into their ordinary business processes. Particularly regarding portfolio optimization, risk management and fraud detection, where immediate data feedback is required, quantum computer algorithms will be beneficial for existing structures. Quantum algorithms based on machine learning or artificial intelligence systems will strongly empower businesses by identifying trading opportunities and bidding strategies for advertisements to respond in the most efficient way to changes in consumer needs and changing markets. The hybrid between classical and quantum-driven software will enhance and improve the quality of products and services in the near-term. Quantum computing is here and many businesses need to start adapting and preparing to be quantum-ready.