The impacts of quantum computing on insurance

February 2021 The impacts of quantum computing on insurance, 2021

Contents

From theory to reality

The (not so) basics of quantum computing

Applications

Quantum computing’s threat to cyber security

The quantum landscape

Insurance impacts – navigating the quantum realm

Moving forward From theory to reality The impacts of quantum computing on insurance, 2021

Quantum computers within reach Insight

Quantum computing harnesses the quantum mechanical Quantum computing has been around as a theoretical properties of very small objects, such as superposition and concept since the 1980s, but has only progressed to a In the field of quantum computing, the point at entanglement, to solve problems that are beyond the tangible reality more recently, with major developments which a programmable quantum device can reach of classical computing. There is a limit to how much and breakthroughs in hardware and software capabilities.3 perform a task that a classical computer more powerful our current computers can become. In 1994, Peter Shor introduced the first ever useful cannot perform in a feasible timescale, is Moore’s Law, which sees computing power double roughly quantum algorithm, which if implemented, could break referred to as quantum supremacy. every two years, is nearing its limit, due to physical commonly used encryption schemes such as RSA. Shor’s constraints involved in the further miniaturisation of algorithm, capable of solving mathematical problems In October 2019, Google achieved quantum transistor chips. Additionally, the speedup in computing underpinning many current cryptograms, which are supremacy for the first time in history. They offered by parallelization is limited by Amdahl’s law.1 impossibly difficult to solve using classical computing, is claimed that their 54-qubit processor, Therefore, solving and optimising multi-variable, real-world what ignited widespread interest in actually building the Sycamore, performed a task in 200 seconds, problems that necessitate the manipulation of large hardware that could support such algorithms.4 However, which would have taken a state-of-the-art datasets, requires an entirely new paradigm. only in 2019, with Google reaching quantum supremacy, supercomputer 10,000 years.6 was it shown that a quantum computer could actually Unlike classical computers, which require a two-fold solve a specific problem faster than a classical computer. increase in transistors to double in power, quantum IBM has since disputed Google’s claim of computers double in power by the mere addition of one Quantum computing today is more of an engineering quantum supremacy, by suggesting that an qubit - a quantum bit.2 This means, quantum computers problem than a theoretical one. The current development improved supercomputing technique could have the potential to deliver significant benefits to many state of quantum computing technology is comparable to theoretically perform the task in just 2.5 days industries by solving those optimisation, simulation and when classical computers were still using vacuum tubes, (yet a proof of this theoretical technique machine learning problems, which would otherwise take before their switch to transistors.5 Complex hardware remains to be seen). The clash between classical computers timescales ranging from 1000s of challenges and a shortage of talent in software these two giants is indicative of the fierce years to the lifetime of the universe. However, this development, means that a fully-fledged, commercially competition in the private sector to gain increase in computational power might turn out to be a available quantum computer might still be more than a dominance in this exciting new field.7 double edged sword – encryption systems that safeguard decade away. Nevertheless, the opportunity for most of our digital communications, and are designed to businesses to take advantage of quantum capabilities Regardless of IBM’s challenge, and despite be computationally intractable to crack using classical through API based cloud offerings, and discover which of the fact that the task that Sycamore computing, are potentially vulnerable to the speedups their needs quantum computers could eventually serve, is performed has no real-world application, offered by quantum algorithms. already within reach. Google’s achievement remains ground- breaking and has brought the reality of quantum computing within closer reach. Source: (1) Chojecki, 2019 (2) IBM Institute for Business Value, 2019 (3) McKinsey Quarterly, 2020 (4) Deloitte University Press, 2017 (5) RAND Corporation, 2020 (6) Arute, 2019 (7) Nature, 2019 The (not so) basics of quantum computing The impacts of quantum computing on insurance, 2021

The power of qubits In classical computing, data is represented by binary states of 1s or 0s, called bits. All our emails, images and videos on a computer are essentially a sequence of these ones and zeros. Superposition Entanglement The building blocks of a quantum computer are called quantum bits, or qubits for short. Unlike Classical bits, qubits can simultaneously be in a state of 1 ------and 0 or any probabilistic combination of the two. The ability to be in two states at the same time is The value of classical bits are kept well separated. However, qubits can interact with one another to create entangled states. When an operation called superposition and is what allows quantum Classical bits are discrete and can is carried out on one qubit, it has an instantaneous impact on other computers to run a vast number of calculations at only be in one of two states: 1 or 0. qubits it’s entangled with. This is what exponentially increases the information density in many quantum operations. Referred to by Einstein once. 1 Repeated calculations on the same 0 as ‘”spooky action at a distance”3, entanglement can happen over any input of bits will always give the length of distance. exact same output, due to their Classical computers solve problems sequentially deterministic nature. (one step at a time) and the bits on a transistor chip are constructed in a way to avoid interference Quantum Two unentangled qubits with one another. However, when the value of one ------qubit changes, it can affect the value of other Qubits entangled by e.g. Qubits can have an infinite number qubits regardless of their distance, through a Laser operation of a laser. The of values between 1 and 0. These ? ? two qubits now exist in an process called entanglement. Superposition and superposition values of 1 and 0 can ? ? 1 indeterminate single entanglement are what allow quantum computers be negative, positive or complex and quantum state to achieve exponential speedups 1 are represented by a point on a Bloch sphere2. ? ? Entanglement can happen Qubits can be represented by any two-state Answers given by quantum ? ? over any distance 80% computers are probabilistic in quantum mechanical system that can be nature. When a qubit in manipulated electronically. The up and down 20% superposition is measured, the vast The measurement of one states of an electron’s spin or the horizontal and amount of information it carries 1 qubit breaks the vertical polarizations of light photons amongst cannot be captured. The quantum entanglement and causes state collapses to a discrete value of the qubit to collapse into other systems (superconducting circuits, quantum 0 1 or 0 on observation, with an Measurement one of the states 1 or 0. dots, ions, etc.) can be used to represent the 1s 0 associated probability. This means of one qubit When one qubit is and 0s that are needed to realize qubits.1 that computations on a quantum measured, the value of the computer would need to be repeated 0 other qubit is also instantly many times to converge on the 1 0 revealed. answer with the highest probability.

Source: (1) Accenture Labs, 2017 (2) Boston Consulting Group, 2018 (3) Simonite, 2018 The impacts of quantum computing on insurance, 2021

How much faster are quantum computers? In addition to superposition and entanglement, which allow quantum computers to carry out calculations simultaneously, many quantum algorithms are also based on the idea of interference. The probability Exponential (significant) speedup – e.g. Shor’s algorithm amplitudes of different quantum states can interfere to Multiplying two prime numbers (e.g. 3×5 ), regardless of their size, is a trivial task. However, it turns out that the reverse of this, finding the prime either strengthen or weaken the probability of solutions factors of a number, is not so trivial. In fact, the difficulty of prime factorisation for very large numbers, is the basis of many common encryption standards, such as RSA, which secure most of our communications over the internet. Classical computers work through problems sequentially, which by cancelling out paths that lead to wrong answers and means that the complexity of prime factorisation can grow exponentially, the larger the number is. However, quantum computers tackle operations amplifying those that lead to correct ones. The aim of concurrently, which means the time it takes to find the prime factors of a very large number only grows linearly, as in the case of Shor’s algorithm for quantum algorithms are to amplify correct answers to prime factorisation. Where it would take a classical computer 300 trillion years to break an RSA-2048 bit encryption key, it would take a 4,099 qubit 4 near certainty and settle on a probabilistically correct quantum computer, only 10 seconds! This has significant cyber security implications. As a result of this potential threat, there has been significant research into trying to find new cryptosystems, which are not vulnerable to quantum computers (post-quantum cryptography). solution.1 For quantum algorithms, unlike classical ones, an increase in the size of a computational task A near term application of the exponential speedup offered by quantum computers is in the chemicals and pharmaceuticals industry. The difficulty in doesn’t linearly increase the time required to tackle it. simulating the interactions between molecules grows exponentially as they grow in size (similar to prime factorization).5 Quantum computers could be A quantum computer with 푛 qubits can conduct used to simulate molecular reactions in a feasible time, which would streamline the process of creating new medicines and materials. calculations on 2 inputs at once. All these properties contribute to the extra power and speed-advantages offered by quantum computing.2 “Where it would take a classical computer 300 trillion years to break an RSA-2048 bit Two examples of quantum algorithms which offer encryption key, it would take a 4,099 qubit quantum computer, only 10 seconds!” exponential and quadratic speedups in solving well- known computational problems, are Shor’s algorithm and Grover’s algorithm, respectively. Peter Shor Quadratic (moderate) speedup – e.g. Grover’s algorithm came up with his algorithm for prime factorisation when The time it takes to search through an unordered list, also increases exponentially with the size of the problem. This is sometimes referred to as the he was at AT&Ts Bell Labs in 1994. Two years later at ‘phonebook’ problem. If a classical computer had to find someone’s name in a phonebook, based on their number, it would need to go through the list of Bell Labs, Lov Grover proposed an algorithm for unordered phone numbers one by one, which at maximum would take as many steps as there are entries in the list (the last entry might be the number searching through unstructured databases.3 The we want). Quantum computing can offer a moderate speedup to this problem. Grover’s algorithm is one of the best known techniques that can offer a potential speedups offered by these two algorithms quadratic speed advantage in search algorithms for unstructured databases. Where it would take a classical computer 푁 steps to look through a list, Grover’s algorithm could do this in 푁 steps.6 This means, for a list with a billion entries, Grover's algorithm could find the answer in only 31,623 steps! was one of the major motivations behind efforts to actually build quantum computers, which at the time However, since the speedup offered is only quadratic in nature (e.g. if a task takes 16 hours using a classical computer it would take roughly 4 hours were (and still to some extent remain) hypothetical using a quantum one), it might not always justify the expense of using a quantum computer. Still, one area this might be advantageous in, is machine devices. learning (ML). Currently, GPUs with parallel processing and specialized graphics are used to tackle unstructured search queries. However, a market of more that $20 billion in ML applications of quantum computing and replacement of GPUs is likely to emerge by 2030.7

Source: (1) Boston Consulting Group, 2018 (2) McKinsey Quarterly, 2020 (3) Deloitte University Press, 2017 (4) QuintessenceLabs, 2019 (5) Boston Consulting Group Henderson Institute, 2018 (6) Deloitte Insights, 2019 (7) Boston Consulting Group Henderson Institute, 2018 The impacts of quantum computing on insurance, 2021

Qubits are extremely sensitive to noise. The slightest So why don’t we have quantum interaction with their environment can cause them to fall out of superposition and lose the information they were carrying, before they have been fully utilised. The computers yet? disappearance of a qubit’s quantum properties is called decoherence.

Decoherence means qubits are highly unstable and after about 50 microseconds become prone to errors.1 Therefore, controlling qubits and their operations is very difficult. Error-correcting algorithms and the Insight addition of more qubits are ways in which these errors The phase of quantum can be mitigated. However, around 1000 physical development we are currently in, qubits are required to create just 1 fault-tolerant and is referred to as NISQ (noisy error corrected qubit, known as a logical qubit. intermediate-scale quantum). In this era of development, quantum 50 microseconds - 273 1000 to 3000 Roughly 200 logical qubits and hence 200,000 physical chips will be limited to roughly qubits are needed for most commercial applications of 50-100 qubits, and although they The period of time qubits can store The kind of temperatures Number of physical quantum computing.2 The large number of physical will be able to outperform information before they decay qubits need to be kept at qubits required to create qubits needed for error correction, drastically increases classical computers in certain to maintain their quantum 1 error-corrected logical tasks, the noise in their state qubit 7 the overhead required to carry out meaningful operations (quantum gates) will calculations. limit the size of quantum circuits and operations that can be performed reliably.5 Calculations Since the slightest vibration or interaction with the will need to take place on a environment can cause a qubit to collapse out of selection of coherent qubits and superposition and into a classical state, qubits need to allow for some degree of errors. The calculations will also need operate in a vacuum environment, be magnetically to be completed in as few steps isolated and kept in temperatures near absolute zero.3 as possible, before gate At absolute zero (0 Kelvins or -273.15 degrees (operation) errors and Celsius), all atoms stop moving, which allows for better decoherence set in. < 1 nanotesla 1000s of Kgs $ Billions control over otherwise volatile qubits. The most The progress made in quantum The strength of field achieved after The weight of quantum computing The cost of a universal, computing in the next decade is common quantum chips in operation today are kept at magnetically shielding qubits - hardware. The large cooling fault-tolerant quantum unlikely to involve error around 15 millikelvins (0.015 K), well below the 4 K systems and the many wires and correction, unless some major qubits can be disrupted by the computer 4 temperature of interstellar space. The systems breakthrough is made in this slightest magnetic field. This is apparatus needed to electrically required for this cooling are extremely costly and can field. Therefore, research and approximately 50,000 time less communicate with individual qubits, weigh as much as a small car. As a result, it’s very trials are likely to be done using strong than the Earth’s magnetic mean these devices can weigh as hard to modulate and scale quantum computers when NISQ devices. field 6 much as a car such large mainframes are required.

Source: (1) Deloitte University Press, 2017 (2) Deloitte Insights, 2019 (3) McKinsey Global Institute, 2016 (4) Deloitte Insights, 2019 (5) Preskill, 2018 (6) D-Wave Systems, 2016 (7) Boston Consulting Group Henderson Institute, 2018 Applications The impacts of quantum computing on insurance, 2021

What types of problem can a The answer a quantum computer provides is quantum computer solve? probabilistic and making sense of this is a challenge. Unlike classical computers, quantum computers don’t offer a single answer. Instead they provide a narrow The types of problems quantum computing is best suited to solve include: optimization, simulation and range of possibilities and the same calculation can machine learning. yield different answers each time it’s carried out. Therefore, quantum computations need to be repeated many times before they converge on the most Optimization problems exist in almost every industry and normally include finding the most efficient path or probable answer. way of solving some problem, which can save costs and increase efficiency. For example, supply chains in many businesses could benefit from optimisation as there are many variables at play, such as costs, routes, variation of products, clients and so on.2 The number of options in such multi-variable problems can For this reason, quantum computing is not the best Optimisation grow rapidly, which is why the speedups offered by quantum computing are well suited to solve these problems. For example, Grover’s algorithm could be used for optimization problems, where millions of solution to all problems and will most likely form part of solutions would have to be tested sequentially through a trial and error process otherwise. Optimisation a hybrid solution with classical computers, rather than examples include, but are not limited to: portfolio optimisation, fault analysis for building stronger planes entirely replacing them. Where narrowing down the and ships, network design, oil well optimisation, creating new materials, traffic flow optimisation, optimising answers to a problem or simulating vastly complex battery designs, parking and e-charging search for autonomous vehicles, etc. systems, proves an essential part of an approach, a quantum computer is likely to be used. For example, Quantum computers can be used to simulate complex systems and processes such as the interaction optimising delivery routes for a company can be an between atoms and molecules. The difficulty in simulating such interactions grows exponentially with the extremely complex task. In this scenario, a quantum size of the problem, meaning it’s impossible for classical computers to accurately represent such systems. computer could be used to find a subset of the most Richard Feynman, who was one of the early theorists of a quantum computer, said "Nature isn't classical, Simulation dammit, and if you want to make a simulation of nature, you'd better make it quantum mechanical.“3 In fact, efficient routes (the most time consuming part of the simulating quantum systems for their use in the field of physics, was one of Feynman’s main motivations problem), and then a classical computer could give a behind his work on quantum computing. Examples of simulations that quantum computers can generate, definitive answer in choosing the best route amongst include: simulating enzyme and protein reactions for drug development, quantum chemistry, Monte Carlo them.1 simulations for risk profiling, traffic simulation, simulating weather systems, etc.

The large size of quantum computing mainframes and Machine learning (ML) is dependent on both sampling and optimisation techniques. Sampling problems the specialised environments in which qubits need to involve selecting a subset (sample) from a population, which best represents the general characteristics of be kept means that quantum computers are unlikely to that population. As qubits are inherently probabilistic, it makes it much easier for a quantum computer to 4 ever replace our desktop PCs or mobile phones. generate random samples. In ML, sampling can be used to create better training data, which is what the Machine Learning ML algorithms essentially learn from. Therefore, the higher the quality of this training set, the more accurate Additionally, the large costs associated with building and powerful the ML capabilities will be. Many ML algorithms are eventually used to solve optimisation these devices means that they are only likely to be problems, which as discussed, can be greatly improved by quantum computing. Examples of applications used when a High Performance Computer cannot include: accelerating the arrival of driverless vehicles, improving fraud detection, better detection of solve the problem in a reasonable time. abnormalities on medical scans, and generally any application ML can be used for.

Source: (1) Accenture Labs, 2017 (2) Boston Consulting Group, 2020 (3) Gil, 2016 (4) Accenture Labs, 2017 The impacts of quantum computing on insurance, 2021

Quantum computing has the potential to revolutionise personalised and precision medicines, improve protein folding predictions, accelerate genomics and streamline Biopharma and life science the process of drug development. An example of this power lies in the ability to simulate enzymes. Enzymes applications can catalyse a wide variety of biochemical interactions and target cells very precisely. Harnessing the power of enzymes and other proteins can lead to new and personalised drug discoveries. However, to do this, we 31% of life science organizations planned to begin evaluating quantum need to able to model their molecular structure and computing in 2020 and 39% percent are either planning an evaluation in 2021 interactions. This involves simulating the interaction of or to place quantum computing on their radar.6 each individual electron and nuclei with one other, as well Insight as the quantum mechanical effects that occur on the sub- The impact of quantum computing on the biopharma industry is one of the most promising amongst all of quantum In September of 2017, IBM computing’s potential applications. Since the interaction of molecules with one another is itself a quantum process, atomic level. This becomes exponentially harder the simulated the largest molecule quantum computers can deliver significant benefits to molecular simulations with relatively low resources. Where it larger a molecule is. Using a classical computer, it is at the time, Beryllium hydride would take a classical computer as many bits as there are atoms in the universe (1082 bits or one-hundred thousand practically impossible to simulate structures like enzymes (BeH2), using a quantum quadrillion vigintillion bits) to simulate the 41 atom penicillin molecule, it would only take a quantum computer 286 3 computer. Even though this 3 qubits. We can expect to see hybrid quantum-classical approaches to simulating molecular structures by 2025.7 which are made up of 1000s of molecules. Therefore, to atom molecule was simple develop new medicines, scientists are forced to actually enough for a classical computer Hardware/end-to-end providers driving biopharma applications of quantum computing include Google, IBM, to model, it lay the foundations create molecules in the lab using synthetic chemistry. Honeywell, D-Wave, Xanadu and Rigetti. Specialist software providers in this field include ProteinQure for the simulation of more They then physically test these molecules to discover (collaborating with AstraZeneca),8 ApexQubit, GTN, 1Qbit (in collaboration with Accenture Labs to speedup the complex structures. In the discovery of drugs for neurological diseases like Parkinson’s),9 Menten AI (has received funding to design a peptide their properties and see how they behave. However, August of 2020, Google to fight COVID-19),10 Zapata Computing and Qulab. There are also a host of companies that are using high these tests don’t always go as planned and the molecules performed the largest quantum performing classical computers for ‘quantum inspired’ approaches, alongside machine learning.11 These include simulation to date using 12 often do not behave as expected, which means more Microsoft, Silicon Therapeutics, XtalPi, Cloud Pharmaceuticals (in collaboration with GSK),12 Atomwise, qubits form its Sycamore chip - trials and tests need to be carried out. Unfortunately, each Turbine, and Benevolent AI. All this activity will hopefully speedup and improve the surprisingly inefficient process of a “Hartree-Fock simulation of synthesising molecules. Commenting on the inefficiency of this part of the drug development pipeline, Denis cycle of testing is expensive and lengthy, which is one of diazene isomerization”.4 the primary reasons why developing new drugs takes so Farnosov, the founder and CEO of ApexQubit said, “Just imagine if we plan to invent a new space rocket and needed to physically build and then launch in order to see how different components work together in the ship”.13 long.1 In the future, quantum simulations could be used to model novel coronaviruses and Current inefficiency of the drug development cycle14: As the interactions of molecules and atoms with each their treatments much faster, other is itself a quantum process, quantum computers are saving many lives and well suited to simulating molecules. Quantum computers resources. Kuano, a start-up 10-15 The time it takes from detecting a founded in 2020, which uses > $2bn The cost of bringing a new can consider all possible interactions at once and come to medicine to market. years new disease to launching a quantum and AI solutions to medicine to combat it. the lowest energy state of a molecule, representing how it screen and develop new drugs, interacts. Therefore, they would be able to model the has joined the COVID-19 High structure and interactions of enzymes and many other Performance Computing (HPC) Consortium to help discover Of drugs that make it to clinical trials, molecules in just hours, which would drastically shorten fail in the first phase of testing. Less drugs that can combat COVID- 90% 97% Of cancer drugs fail in the life cycle of drug development and open the door to 19.5 than 10% of all medicines that enter clinical trials. creating more personalised and targeted therapies. It is clinical trials, make it to market. estimated that quantum simulations could be worth $20 billion in the pharmaceuticals industry by 2030. 2 Source: (1) McKinsey Quarterly, 2020 (2) Boston Consulting Group Henderson Institute, 2018 (3) IBM News Room, 2017 (4) Science, 2020 (5) Kuano, 2020 (6) QED-C, 2020 (7) Boston Consulting Group, 2019 (8) Businesswire, 2020 (9) Newsroom.accenture.com, 2017 (10) Biopharmatrend.com, 2020 (11) ) Boston Consulting Group, 2019 (12) Biopharmatrend.com, 2020 (13) The Quantum Daily, 2020. Apexqubit (14) Innovatorsunder35, 2018 The impacts of quantum computing on insurance, 2021

Quantum computing (QC) could be used to streamline Quantum computing applications many carbon intensive process, contributing to the fight against climate change. NISQ devices in the next decade, comprising of about 50-150 qubits will be for tackling climate change capable of accurately simulating and analysing molecular reactions before needing to even synthesise a single molecule.1 This allows for the modelling and To produce ammonia-based fertiliser, the Haber- QC can help find new catalysts for splitting water Bosch process is used, which consumes 3-5% of molecules to produce hydrogen. Currently, creation of more efficient chemical catalysts that can all natural gas produced worldwide. However, using expensive platinum and methane (a green-house improve carbon intensive industrial processes such as bacteria to produce ammonia naturally, takes gas) are used in the process. Using more effective significantly less energy and QC could be used to catalysts in the synthesis of hydrogen, to produce those involved in the production of fertilizer, which accurately model the catalyst (e.g. the FeMoco hydrocarbons, could also lead to the development of accounts for 2% of global CO2 emissions!2 molecule) required to do this. Google’s CEO cheaper emission-free fuel in shipping, aviation and predicts that the Haber-Bosch process will be transportation and help solve the storage problem in obsolete in the next decade.4 renewable power systems.8 After the era of NISQ comes error-corrected quantum Fertiliser production Hydrogen production computing which will be capable of solving higher-level QC could help with the design of more efficient, The current ability of classical computers to model fluid optimisation problems. This can greatly streamline the denser batteries. This could increase the uptake of dynamics, used in the design of aircraft, cars and ships electric vehicles, which would help reduce CO2 is substandard. Drag and lift for aircraft could be better formulation of products and optimise the field of emissions. IBM and Daimler AG (Mercedes-Benz’s optimised using QC, which would reduce emissions. parent company) are working towards creating next- Airbus is looking at how QC can improve aircraft climb material science. Materials can be optimised to be generation lithium sulphur (Li-S) batteries that will last trajectory (important in short-haul flights), and how to stronger, lighter, cheaper and better insulators that longer and be cheaper than today’s batteries. To do improve wingbox design to optimize the weight that this they are using QC to model the molecules aircrafts can carry. Marine and aviation both account require less carbon and resources to be manufactured. required in the production of these Li-S fuel cells.5 for approximately 2% of global emissions9 and both More efficient batteries industries can benefit from these kinds of For example, stronger and lighter replacements for Fluid dynamics optimisations. energy-intensive materials such as aluminium and steel, can be used in the manufacturing of cars, ships, planes and buildings. The energy storage density of batteries Binding carbon from the atmosphere and at the Supply chains could also benefit from QC’s could also be optimised by utilising new materials, which source of its production, helps with reducing the optimisation capabilities as there are often many amount of CO2 in the atmosphere (carbon- variables at play, such as cost, routes, variation of might increase the uptake of renewables (e.g. solar capture). QC could be used to model better products, clients and so on. Improvements in catalysts which would make this process more supply chain optimisation offered by QC, coupled power) and electric cars. Additionally, quantum effective and lower its cost. Scalable negative- with driverless cars and more shared economy computing based ML could be used to optimise yields emission ‘direct-air capture’ solutions could also transportation trends, could significantly reduce be developed using these catalysts. 6 the carbon footprint of the transportation and decrease by-products in various industrial industry.10 Carbon capture processes. Supply chain optimisation

Volkswagen, in partnership with D-Wave, are Quantum computing can also generate great value and Cement production accounts for 5.5% of CO2 using QC to optimise traffic management systems. emissions globally. Polymer cements are This will allow for better traffic forecasts and allow reduce emissions by improving the design of systems stronger, more resistant to chemicals and have a taxis and public transport to more efficiently deploy involving fluid dynamics, such as cars, planes and lower carbon footprint than traditional cement. their services, reducing the waiting time for However, they are only used in a very limited customers. This will also avoid taxis and buses ships. The optimisation of supply chains and logistics number of fields because of the cost of producing from travelling long distances without passengers, them. QC could give us better solutions and which would help reduce the number of cars on for planning/routing or product distribution, as well as the formulations for creating this type of cement. 7 the road and thus the volume of CO2 emissions.11 optimisation of traffic systems could also reduce the Cement production Traffic flow optimisation carbon footprint of many industries.3

Source: (1) Boston Consulting Group, 2020 (2) Karma, 2020 (3)-(4) Boston Consulting Group, 2020 (5) IBM Research Blog, 2020 (6)-(10) Boston Consulting Group, 2020 (11) Volkswagenag.com, 2018 The impacts of quantum computing on insurance, 2021

Financial services applications

Dynamic portfolio Risk profiling and optimisation aggregation Quantum computing’s ability to accurately simulate risk scenarios, optimise portfolios and quickly sift through Portfolio optimization using Monte Carlo simulations can be greatly improved Amendments to regulations such as Basel III and Solvency II mean that money large unstructured datasets to train ML algorithms for with the arrival of quantum computing.3 Many players are already investing in managers and financial institutions need to simulate a much larger set of risk fraud detection and enhanced customer targeting, quantum research in this field, including Goldman Sachs, JP Morgan Chase scenarios, which increases the cost of compliance, especially if there are and Citigroup.4 penalties involved. Quantum computing can help test vast sets of risk- can deliver significant benefits to the financial services assessment scenarios with more accuracy, driving down the cost of risk profiling industry. The complexity of financial markets are increasing. This can be attributed to the and making it more efficient. The power of quantum computing could also allow increasing number of options available for money managers to invest their for real-time risk analysis and financial forecasting.7 money in, alongside the increasing pressures from regulators to be more Insurance companies in particular can benefit from the transparent and increased market volatility. Therefore, the number of variables The simulation of risk scenarios can also greatly contribute to the process of risk a money manager needs to consider when optimising their client’s portfolio aggregation for insurers. Additionally, quantum computing’s superior simulating ability of quantum computers to accurately simulate quickly stack up. Quantum computing can compute portfolios that are optimal capabilities can be used for accurate weather forecasting, which is of weather systems, to better manage catastrophe and over fewer rebalances compared to classical computing, which increases tremendous value to insurers.8 Both these applications can be utilised in real-time whether-related losses. The risk aggregation capabilities efficiency and cuts costs.5 Additionally, quantum computing based ML can risk analysis and forecasting. greatly enhance pattern recognition and clustering, which will allow for the of quantum computers can also enhance the aggregation of assets and investors in groups that are seemingly unrelated to underwriting function of insurers. the naked eye.

In May 2019, Willis Towers Watson announced their Customer targeting and Fraud detection collaboration with Microsoft to transform their risk product recommendation management and quantification offerings to insurance and financial services clients, using quantum Small to medium sized financial institutions often lose customers due to not A report from IBM estimates that “financial institutions are losing between USD computing.1 targeting them with personalised enough services and relevant products.6 It 10 billion and 40 billion in revenue a year due to fraud and poor data takes a classical computer an impractically long time to go through large data management practices.” Fraud detection using classical computing is very sets to find patterns and useful information about customer behaviour. This inaccurate and has an 80% false positive rate, which means financial institutions means financial institutions (and well as businesses in other industries) are such as banks are overly risk averse. As a result, it often takes banks as long as Allianz X, the digital investment branch of the Allianz missing the opportunity to better predict customer preferences and target them 12 weeks to onboard new customers due to the process of carrying out credit group, alongside RBS, have invested in the funding with more pre-emptive product suggestions and personalised services. Quantum checks. In a climate where 70% of banking is done online, banks risk losing round for the quantum computing start-up 1QBit.2 computing’s ability to efficiently and accurately analyse large datasets to find customers with such slow sign-on speeds.9 patterns and make projections using ML, could help target customers more effectively, increasing customer retention and satisfaction. The translation of Accurate fraud detection relies on pattern recognition and natural language classical datasets into quantum ones is one of the main barriers to achieving this. processing (NLP), which is carried out using neural networks (a type of ML algorithm). In finance and insurance, this can help detect patterns of fraud and automated attacks. Training neural networks on big data is very difficult using classical computers. However, quantum computing’s powerful speedups in searching through unstructured data, can greatly improve this process.

Source: (1) Willis Towers Watson, 2019 (2) Finextra Research, 2017 (3) Atos, 2018 (4) Modelomni, 2020 (5)-(7) IBM Institute for Business Value, 2019 (8) Singularity Hub, 2017 (9) IBM Institute for Business Value, 2019 The quantum landscape The impacts of quantum computing on insurance, 2021

The current state of quantum computing development is akin to when classical computers were still using vacuum tubes, before Competing technologies their transition to silicon transistors. Competing qubit technologies are in a race to prove themselves the most viable option for a universal quantum computer – that is a quantum computer capable of tackling all quantum problems. Qubit technologies

Error correction remains one of the most resource intensive and The most popular universal quantum computing architecture today uses superconducting qubits. These are two-level energy systems that use miniature costly parts of producing a universal quantum computer. loops of superconducting wire, cooled to near absolute zero.5 They are the most studied qubit technology so far and used by industry giants such as Significant development in this field, could see a workable Google, IBM, Intel, Rigetti and Alibaba. Superconducting qubits benefit from fast gate (operation) times compared to other qubit technologies. However, quantum computer hit the market as soon as 2028-2030. the challenges facing quantum computers made from these types of qubits are the costs associated with their cryogenic cooling as well as their fast Microsoft are currently working on a technology that aims to have decoherence times. Their short-lived nature means that for each logical qubit of this kind, 1000s of physical qubits are required for error-correction (the a 1:1 logical to physical qubit ratio.1 largest superconducting chip today, Google’s Sycamore chip, has only 72 physical qubits). Millions of physical qubits would be required for universal quantum computing.6

Despite the array of qubit technologies currently in development, A popular alternative to superconducting qubits is to use individual ions trapped in electromagnetic fields (trapped ions). The isolation of individual atoms the majority of quantum computing end-users will not have to increases their decoherence time, creating more stable and less error-prone qubits. IonQ, Alpine Quantum Technologies and Honeywell are pursuing worry about committing to a particular qubit implementation when this type of technology. Despite producing higher quality qubits and capable of operating at room temperature, trapped ion qubits are not as popular or wanting to access quantum computing capabilities. This is developed as their superconducting counterparts. 7 This is because they rely on a less mature technology for production, compared to the already because most users will access quantum computers via APIs standardised and well known semiconductor technology used for superconducting qubits. Even though trapped ions don’t need to be cryogenically cooled, 8 through the cloud. Cloud offerings allow the high costs involved in they still require an ultra-high vacuum to operate in. building, running and maintaining quantum computing hardware to be distributed amongst many users, making it a more There are also a host of other more nascent qubit technologies in development, which if successfully implemented, might prove to be easier to manufacture accessible and affordable technology across the board. Many at scale compared to superconducting qubits or trapped ions. These include photonic qubits, silicon-based qubits, spin qubits, diamond qubits and neutral 9 firms are already offering access to their quantum computing atoms. VCs have been increasingly investing in these alternative hardware solutions since around 2017. Another potentially ground-breaking qubit implementation comes in the form of topological qubits, which Microsoft have been researching for several years now. Presently only theoretical, hardware via the cloud. These services include IBM Q topological qubits based on the exotic Majorana quasiparticle, promise to deliver unparalleled low error rates of 1 part per million (or even per billion)! These Experience by IBM, Leap by D-Wave, Cirque by Google, Forest qubits could truly change the game and greatly accelerate the arrival of a universal quantum computer.10 by Rigetti and Aliyun by Alibaba.2 Amazon Web Services and Microsoft Azure have also joined the Quantum Computing as a Last but not least, is an altogether different approach to quantum computing, called quantum annealing, most notably pursued by the Canadian firm D- Service (QCaaS) space by offering users access to a range of Wave. D-Wave are the first company to build and sell a full-scale quantum-based computer, called a quantum annealer. It is generally accepted that D- quantum technologies via the cloud.3 Wave’s machine can’t technically be classified as a quantum computer since it is not a general-purpose machine. It’s instead designed to specifically solve optimisation problems (by finding the global minimum in a given energy landscape). D-Wave’s quantum annealers are based on a special type of superconducting qubit that also need to be cooled to temperatures near absolute zero.11 Cloud offerings of quantum computing increases accessibility and familiarity and allows users to investigate potential applications 12 starting today. This will likely increase adoption and demand in Number of qubit development projects at universities, government labs and public/private companies (as of Sept 2020) the longer-term. Not having to own the quantum computing hardware also means that companies won’t have to worry about Superconducting Trapped ion Photonic Spin Cold Diamond Topological Annealing the VHS vs. Betamax risk when choosing between different qubit technologies to invest millions in!4 25 20 21 19 10 7 7 7

Source: (1) Boston Consulting Group Henderson Institute, 2018 (2) Boston Consulting Group, 2018 (3) McKinsey Quarterly, 2020 (4) Quantum London, 2020 (5) Nature, 2020 (6) The Quantum Daily, 2020. TQD Exclusive (7) Boston Consulting Group, 2018 (8) The Quantum Daily, 2020. TQD Exclusive (9) Nature, 2020 (10),(11) Boston Consulting Group, 2018 (12) Quantum Computing Report, 2020. A Tour Through the Quantum Ecosystem The impacts of quantum computing on insurance, 2021

An exciting global quantum computing ecosystem has emerged in the last decade, off the back of increasing public and private investments into quantum technologies. More than $700 million has been invested in over 60 The quantum computing ecosystem different quantum technology companies globally, from 2012 to 2018 (the true volume of investments is almost certainly higher with many deals kept secret).1 The trend in private investments has been steadily increasing over the decade, with firms receiving at least $450 million in 2017 and 2018, compared to only $104 million in 2015 and 2016. Players involved in developing quantum hardware have received the majority of VC investment to Key players in different layers of the quantum computing technology date. Nonetheless, firms specialising in quantum software raised more than A blooming ecosystem stack $110 million between 2012 and 2018, despite their software not delivering any real-life benefits as of yet. These firms, which are often selling software Over the recent years, a vibrant ecosystem has for hardware that has not yet fully matured, are primarily attracting clients in developed around quantum computing technology. This ecosystem consists of academic institutions, fields such as the aerospace industry, which often plans years ahead, the a host of public and private companies, from tech Software and services End-to-end providers Hardware providers biopharma industry, which expects to see real applications in the next few giants to start-ups, involved in bringing the providers years or those in the financial industry, where small competitive advantages hardware and software to market, VCs who want can translate to huge gains. According to Yianni Gamvros, the head of to invest in this technology and clients who are Zapata Computing Intel business development at the quantum software company, QC Ware, “This beginning their quantum journey by identifying Quantum Circuits Aliro Technologies seems like a small investment to get ready for another potentially disruptive problems quantum computing can solve and IBM ColdQuanta force”.2 conducting preliminary experiments with the help QxBranch of consultants in the field. Google Bleximo BosonQ Historically, North America has dominated the top spot in attracting private The key players involved in developing the Microsoft investment in quantum technologies. However, the heavy commercialisation technology itself can be broadly separated into IonQ three categories: QC Ware of hardware and software technology in China, which can be seen through Rigetti Computing BraneCell AppliedQubit their intense activity in patent filings, puts this top spot in question. Between Hardware providers 2012 and 2017, more than 43% of quantum technology patents originated D-Wave Alpine Quantum form China.3 Additionally, China has overtaken the US in the number of Providers of quantum computing hardware. This Cambridge Quantum Technologies scientific papers published in the field since 2013.4 includes the array of qubits needed for Computing Honeywell Oxford Ionics calculations, control systems and the components Avanetix involved in error correction. Origin Quantum Computing Quantum Circuits The geographic distribution of private investment in quantum technologies 1QBit Software and services providers mirrors research hotspots around the world and shows that the US, China, A*Quantum Alibaba Delft Circuits UK, Canada and Australia are leading the way. Public funding in quantum Providers that offer an interface for users to QuTech technologies has also been a major driver of its growth over the years. The Quantum Computing Quantum Machines USA, Canada, UK, EU, Netherlands, Germany, China, Russia, South Korea, translate classical problems into a quantum Inc Atom Computing computing readable format and vice versa. These Agnostiq Japan, Australia, Singapore, India, Israel and France have collectively players provide quantum computing functionality Xanadu 5 kiutra contributed $22 billion to national public initiatives (as of September 2020). through APIs via the cloud. Many software ApexQubit Alice&Bob China leads in public funding with a $10 billion quantum programme, $3 providers also offer consulting services to help Amazon billion of which is dedicated to quantum computing.6 firms identify quantum computing use cases and Beit QuiX strategies.

In 2013, the UK government announced the National Quantum Technology End-to-end providers Programme which included £270m funding for research and outreach. £120m of this was put into the creation of four “Quantum Hubs” around the country, Hardware providers who also offer cloud-based For a more comprehensive list of various players across the quantum computing technology stack and including the National Quantum Information Technologies (NQIT) computing opensource software platforms with a varying level 7 of access to their hardware.9 more information about each player, visit the Quantum Computing Report website at: hub, headed by the University of Oxford. A further £153m was invested in https://quantumcomputingreport.com/privatestartup/ 10 2019 in the second phase of funding.8

Sources: (1) Boston Consulting Group, 2018 (2) ,(3) Nature, 2020 (4) Atos Ascent Thought Leadership, 2016 (5) Qureca, 2020 (6) Boston Consulting Group, 2018 (7) Atos Ascent Thought Leadership, 2016 (8) Qureca, 2020 (9) Boston Consulting Group, 2018 (10) Quantum Computing Report, 2020. Private/Startup Companies The impacts of quantum computing on insurance, 2021

For practical applications of quantum computing, we need processors with enough qubits to run the applications and The future of quantum development algorithms that can solve the mathematical problems behind them. Given a Moore’s Law rate of development in the number of qubits, without any improvement to error correction, the quantum applications market is estimated to reach $2 billion by 2035, and more than $260 billion by IEEE standards for quantum computing nomenclature and benchmarks 2050. With improvements to error correction, this is likely to rise to $60 billion by 2035 and $295 billion by 2050 (for Whilst the quantum computing industry is growing at a rapid pace, with many different qubit reference, the global computing market today is worth Insight architectures in development and a growing ecosystem consisting of students, academics, $800 billion).1 hardware and software developers, engineers, clients from a broad range of industries and Universal quantum computers are still investors, it lacks a cohesive framework of communication. The nomenclature and benchmarking at least a decade away. However, standards across the industry are fragmented, making it difficult for various players to Once a certain level of technical viability is reached and many investors are expecting to see communicate effectively. the appropriate quantum algorithms to solve industry returns on their capital much sooner problems are developed, the adoption of quantum than that. Some VCs are hoping that a computing is likely to take on an s-curve pattern. For technological breakthrough will make In an effort to build a common communication framework, the Institute of Electrical and a general purpose quantum machine applications where quantum computing can deliver a Electronics Engineers (IEEE) announced the IEEE P7130™ — Standard for Quantum Computing possible in the next 5-10 years, whilst Definitions project in August 2017. This project aims to standardise nomenclature and significant speed advantage, there could be 70% adoption others believe that industry applicable terminology across the industry in the hope of reducing confusion and making it a more applications will be found for NISQ-era in 5 years, similar to the trend of GPU adoption for ML accessible space to the various players. This is an ongoing project which will update terminology devices in the next few years. There applications. For moderate speedups, there could be 50% as progress in made in the field.5 2 are also those that are hedging their adoption in 15 years. bets on the start-up or firm they are investing in, making enough progress At the same time, better benchmarks and metrics are needed to measure quantum computing that someone else buys them out. Executives would be wise to track key developments in progress. It’s important that these metrics and benchmarks account for the differences in the quantum computing technologies so that they are ready to However, if these quantum various underpinning technologies. The IEEE P7131™ - Standard for Quantum Computing put together a quantum team when meaningful investments don’t turn around a profit Performance Metrics & Performance Benchmarking project was launched in 2018 to address this applications are on the horizon. The indicators of soon enough, there is a danger of a very challenge. This standard aims to define technology agnostic metrics and come up with development to look out for include: the number of qubits quantum winter dampening the standardised benchmarking across the industry. This will allow different quantum computing that can coherently be involved in calculations (around 150 current buzz around this technology. technologies to be benchmarked against each other as well as against classical computers.6 Akin to the phenomenon of AI winters, Some current benchmarks in use include the quantum volume metric by IBM, implementations of are needed for quantum simulations), performance a quantum winter describes a waning Shor’s and Grover’s algorithms, randomized benchmarking and gate-set tomography. benchmarks of different algorithms on different qubit interest in quantum computing from architectures, the demonstration of quantum advantage investors and the public, following a (when a quantum computer can perform a useful task failure of the industry to deliver on However, there is also a potential danger in establishing metrics and benchmarks too early. their promise of practical applications Simplistic benchmarks could halt innovation as hardware and software developers become which a classical computer is incapable of performing in a in the near-future. This would halt the wholly occupied with trying to perform highly against a particular metric, that might not even take reasonable time), development of error-resistant progress of the field as the money 7 technologies such as topological qubits and the successful coming in from investors starts to dry into consideration the limitations or properties of their technology. Therefore, careful implementation of error correction in other qubit up.4 consideration must be given to the field of benchmarking and metrics research, as it will ultimately define the progress of quantum technologies. architectures.3

Source: (1),(2):Boston Consulting Group Henderson Institute, 2018 (3) Boston Consulting Group, 2018 (4) Nature, 2020 (5) Standards.ieee.org, 2017 (6) Standards.ieee.org. 2018 (7) Blume-Kohout, Robin J., Young, Kevin., 2019 Quantum computing’s threat to cyber security The impacts of quantum computing on insurance, 2021

Encryption is used to securely transfer information between Demystifying encryption - How do we two parties. A key is used to mathematically scramble information into an incoherent format (ciphertext), that hides the true meaning of the communication from any secure our communications? eavesdroppers. Another key can then be used to decrypt the information into its original format by the intended recipient. The study of encrypting and decrypting messages is referred Asymmetric cryptography to as cryptography. The two main ways keys are exchanged Two separate keys are used for encrypting and decrypting: one is private and one is public. Alice wants to send Bob a private message, over an in cryptography are via public-key (or asymmetric-key) and insecure public channel. To make sure no one can intercept her message to Bob, she needs to encrypt it. To do this, Alice needs Bob to generate a public key using his own private key. Bob generates a public key and broadcasts it for anyone to access. Alice then uses Bob’s public key to convert 1 symmetric-key schemes. InsightInsight her message into an unreadable ciphertext. This then allows Alice to exchange her message with Bob securely, as an eavesdropper wouldn’t be able to make sense of the message even if they intercepted it. Bob then decrypts Alice’s message using his private key pair, which only he has access to, and which is mathematically linked to the public key. WhenThe we phase talk about ofkeys quantumin Public-key cryptography (PKC): A public key available to cryptography,development we we are are referring currently to in, Even through the public and private keys are mathematically related, and it is theoretically possible to derive the private key from the public one, the anyone is used to encrypt information, and a mathematically ais string referred ofdata, to as whichNISQ when(noisy mathematical procedure behind doing so (e.g. finding the prime factors of a very large number) is extremely difficult and technically unfeasible using 6 linked private key pair, which only the intended recipient of the pluggedintermediate-scale into an accompanying quantum). In a classical computer. However, obtaining the public key using the private key is trivial (e.g. multiplying two prime numbers). message has access to, is used to decrypt the information. algorithm,this era of can development, either encrypt quantum or Bob exchanges his public key by broadcasting it decrypt some piece of This type of encryption allows secure transactions and chips will be limited to roughly information.50-100 qubits, The and althoughsecurity they of communications to take place on open networks such as the encryptionwill be systems able to depends outperform on internet. Applications include, checking emails, online banking, theclassical mathematical computers complexity in certain of editing information on the cloud and the majority of other breakingtasks, the these noise keys. in The their Bob Hello X$%f Hello Alice computationaloperations (quantum power required gates) towill exchanges that take place over the internet. Common friend Decrypted using M#rt Encrypted using friend breaklimit the cryptographic size of quantum keys circuits used 2 Bob’s private key Bob’s public key examples of PKC schemes are RSA and Diffie-Hellman. today,and operations in a feasible that time, can is be beyondperformed the capability reliably. ofCalculations classical computers.will need to However,take place on the a Symmetric cryptography Symmetric-key cryptography: The same key is used to speedupsselection of offered coherent by qubits quantum and encrypt and decrypt information. The key needs to be computing,allow for some threaten degree to of break errors. The same private key is used for encrypting and decrypting. Again, Alice wants to send Bob a private message, over an insecure public channel. To make sure theseThe keys. calculations will also need no one can intercept her message to Bob, she needs to encrypt it. To do this, Alice and Bob securely exchange a private key with one another. This can be exchanged securely between the two parties. This can either done physically (e.g. Bob meets Alice in person ahead of time, to give her a private key) or PKC can be used to exchange the key. Alice then scrambles her be done physically or using a secure method such as PKC. to be completed in as few steps message using the private key and securely sends it to Bob. Bob can then decrypt the message using the same private key. PKC,as possible, symmetric beforecryptography gate This type of encryption’s safety depends on the safety of and(operation) hash functions errors are often and The security of this method depends on the security of exchanging the private key. The fact that two users have access to the same key makes it less secure 3 exchanging the private key. used in conjunction with one as it increases the chance of an adversary getting hold of this key. However, symmetric encryption is faster to implement that asymmetric encryption, which decoherence set in. is why it is a preferred method when large amounts of data need to be secured. another to secure data. For example,The progress PKC made can be in used quantum to Another important group of cryptographic schemes are hash distributecomputing symmetric in the next keys decade and is Bob securely exchanges his private key with Alice functions. Hash functions are a one-way process that reduce thenunlikely a hash to function involve can error be data to a unique fixed size text (a hash). The smallest change applied,correction, to upkeep unless the some integrity major breakthrough is made in this to the encrypted data will alter the hash and generate an of the data or information exchanged.field. Therefore, However, research these and entirely new hash function. Therefore, hash functions are used threetrials schemes are likely are to not be alldone equally using Bob Hello X$%f Hello Alice to maintain the integrity of data and to confirm nothing has vulnerableNISQ devices. to quantum friend Decrypted using M#rt Encrypted using friend been tampered with (used in blockchain technology).4 computing.5 the same private the private key key

Source: (1) Atos Ascent Thought Leadership, 2016 (2) Hudson Institute, 2019 (3) Atos Ascent Thought Leadership, 2016 (4)-(6) RAND Corporation, 2020 The impacts of quantum computing on insurance, 2021

The security of most online transactions and data held by Quantum computing’s threat to cyber organisations, is based on the intractability of solving the mathematical problems that underpin cryptosystems. Examples include the difficulty of prime factorising large security - now and in the future numbers or solving discrete logarithm problems as in the case of many PKC protocols such as Rivest-Shamir-Adleman (RSA), Diffie-Hellman, digital signature algorithms (DSA) Two types of attack and elliptical curve cryptography (ECC).1 When a breach of security does occur, it’s normally down to the poor The capability of Shor’s algorithm to break public-key cryptosystems such as RSA and ECC, in just seconds, threatens to undermine today’s implementation of cybersecurity protocols and frameworks. encryption protocols and put the security of our communications at risk. However, this isn’t a threat that materialises only after universal, fault- This allows adversaries to steal or manipulate data by finding tolerant quantum computing becomes available. The eventuality of quantum computing means that our communications and data are under a way to bypass the encryption systems in place, exploiting threat, right now! Adversaries are capable of intercepting communication channels today to steal data, which they can later decrypt with the advent of a powerful enough quantum computer. This means, the threat from quantum computing is two fold: cyber attacks both in real-time and digital or human vulnerabilities instead. retrospectively.

The difference with quantum computing adversaries is that they will be able to attack the very encryption system itself, thus adding another layer to the cyber vulnerabilities that – Quantum attacks in real-time already exist.2 Quantum computing can be used to break One of the biggest cyber threats real-time quantum computing attacks on encryption schemes pose, is the undermining of identity authentication public-key cryptography (using Shor’s algorithm), and digital signatures. This allows adversaries to pose as anyone and compromise the safety of any network. This type of attack could go significantly weaken symmetric cryptosystems (using unnoticed for months, allowing many fake banking transactions and wide scale distribution of malware to take place.4 These attacks are only Grover’s algorithm) and undermine the digital signature possible in real-time, when adversaries have access to quantum computing capabilities (either the hardware itself or via the cloud). Side-channel schemes used to authenticate blockchain transactions. The attacks also become a possibility with advances in quantum technology. This could for example include, an adversary freezing a stolen credit 5 lengths of private keys have already needed to be increased card to a temperature where the laws of quantum physics take hold, and then querying information from it in superposition. over the years, to make them safe against the continuously It would take an approximately 2,000 qubit, fully fault-tolerant quantum computer to break PKC schemes such as 1,024-bit RSA or 256-bit ECC. improving power of supercomputers. However, the development of such a device is still more than a decade away.6

Quantum computing doesn’t equally affect all cryptosystems and can only provide significant speedups in cracking PKC. – Retroactive attacks Symmetric encryption protocols can be made safe by just increasing the size of their keys, as quantum computing can Retroactive quantum attacks are where an adversary harvests data now, and holds onto this encrypted information for about 10+ years, in the only offer a modest speedup against breaking these hope of being able to decrypt it when a cryptographically relevant quantum computer is available. However, this type of attack only poses a schemes. For those interested, the type of computational genuine threat to information that needs to be kept secret for a long time. For example, the harvesting of personal credit card numbers don’t problems quantum computing can easily solve are called really matter as they are likely to expire by the time they are decrypted. However, government and military secrets, Intellectual Property, trade bounded-error quantum polynomial time (BQP) problems. secrets and some personal videos and messages might need to remain secure for more than 20-30 years.7 Retroactive attacks mean that our They cannot solve NP problems efficiently but still provide a data is already under threat by quantum computing. Data stolen closer to when fault-tolerant quantum computing is available is the most quadratic speedup.3 valuable and at risk. This is why it is important to take measures now to combat the threat of retroactive quantum attacks. One solution is to migrate to encryption schemes that are secure against quantum algorithms (post-quantum cryptography), as soon as possible.

Source: (1) Wallden, 2019 (2) RAND Corporation, 2020 (3) Wallden, 2019 (4) RAND Corporation, 2020 (5) Wallden, 2019 (6) Hudson Institute, 2019 (7) RAND Corporation, 2020 The impacts of quantum computing on insurance, 2021

Post-quantum cryptography (PQC) refers to classical algorithms (normally public-key algorithms) that are secure against quantum computers. PQC relies on the hardness of mathematical problems Post-quantum cryptography (often in the NP category) that quantum computing algorithms can’t solve in a feasible time. These include hash-based, code- based, lattice-based, multivariate and symmetric-key cryptography.1 Standardisation of post-quantum cryptography schemes Only major developments or an entirely new architecture in fault tolerant quantum computing, expected to emerge around 2035, There is a need for standardisation in the field of PQC. For a long time, would pose a threat to current cryptography. However, the threat Insight governments were complacent and did not raise awareness about the threat of of retroactive attacks and the amount of time it would take to quantum computing to current cryptosystems. Instead, researches interested in develop, standardise and adopt PQC protocols (most likely As well as PQC, which is a classical solution to quantum-proofing cybersecurity were independently coming up with PQC algorithms and the PQC decades), means that governments are looking to implement PQC communications, there exist other approaches too, such as space was unstandardized and full of untested cryptosystems. Finally, in 2016, Quantum Key Distribution (QKD). QKD is a quantum solution to a standards much before 2035.2 GCHQ have already started the US National Institution for Standards and Technology (NIST) started a quantum problem. It provides a method for exchanging symmetric project of collating and testing the best post-quantum public-key cryptographic researching post-quantum security3 and the NSA plans to move to keys over a public channel, without having to rely on PKC. QKD protocols. NIST are looking to have a standardised set of PQC schemes quantum secure standards in the near future.4 Current estimates takes advantage of the properties of quantum systems published between 2022-2024, after which, a widespread transition to using these for the number of qubits a quantum computer requires to break themselves to establish security. The very act of observing a quantum system will change its state and so any eavesdropper in new protocols should begin.7 It’s important that the final number of PQC PKC schemes, are based on Shor’s algorithm. However, Shor’s the process of key transmission can be detected (and the key algorithms standardised by NIST are kept to an absolute minimum, to avoid a algorithm hasn’t been shown to be optimal at prime factorisation. discarded). The information in QKD can be encrypted in the fragmentation of approach. Therefore, a sudden breakthrough in quantum algorithms that polarization and axis of a photon, before it is transmitted. The allow this to be done faster (e.g. using variational quantum sender and receiver can then publicly share part of the encrypted message, and if they differ, they know there has been a breach. To comprehensively test PQC schemes, it is essential to find the fastest quantum factoring), could bring the timeline of a quantum computer capable QKD signals can be transmitted via optical fibres or wirelessly. algorithms capable of breaking cryptographic keys, and then increase PQC key of breaking encryption much closer. Consequently, the risk The two primary methods of QKD transmission are via closed lengths in conjunction with this. It’s important that PQC schemes eventually management approach to quantum computing needs to be QKD secure networks and via nano quantum satellites. adopted are not susceptible to merely moderate speedups offered by more probabilistic and should consider high impact, low-probability powerful quantum algorithms discovered in the future. However, most PQC QKD solutions are already commercially available and it is a hot events as well as longer-term threats. The timeline for threats area of research, including participation from the NSA and GCHQ. schemes suggested so far, such as post-quantum digital signature schemes, posed by quantum computing should be constantly monitored and The UK Quantum Communications Hub is currently building a often have private/public key or signature sizes that are too large, making them reassessed. national QKD network which is set to be completed in the next five inefficient to use. In certain fields, where security is the top priority (e.g. defence, years. China plan to have constructed both a fibre QKD network financial markets, etc.), an inefficient but secure post-quantum cryptosystem is connecting Beijing to Shanghai, and a quantum satellite. In the not a problem. However, in other industries and particularly for personal use, Grover’s algorithm threatens to weaken symmetric encryptions quantum race, China are leading in patent submissions for QKD cryptographic inefficiencies (public-key size, key generation speed, encryption and quantum cryptography, whilst the USA are leading in patents and decryption speed, signature length) are unlikely to be tolerated, and a less and hash functions only modestly. Therefore, the length of for quantum computing hardware and sensors.6 symmetric keys need to be doubled and the length of hash secure but more efficient protocol would be preferred. Investigation into finding efficient but secure cryptographic systems is an active field of research.8 There functions increased by 50% to counteract the threat. Although, Implementing QKD or PQC algorithms is no easy task and might are currently no PQC digital signature schemes that offer both short signatures there also needs to be a consideration for the scalability and require large-scale and even national co-operation and standardisation. PQC is less secure than QKD as it only relies on and short key sizes.9 practicality of decrypting and encrypting using very long keys. the difficulty of solving a mathematical problem, for which Luckily, there is mathematical evidence (albeit not rigorous proof) increases in computational speed and new algorithms are a that Grover’s algorithm offers the maximum speedup for a threat. QKD is a safer option but requires the installation of optical computer to perform a search algorithm.5 This means that PQC fibre networks and infrastructure. Businesses should decide which option to choose based on a quantum assessment. schemes that can withstand Grover’s algorithm, are likely to be secure against any further quantum developments too.

Source: (1) Wallden, 2019 (2) RAND Corporation, 2020 (3) Atos Ascent Thought Leadership, 2016 (4) Ars Technica, 2015 (5) RAND Corporation, 2020 (6) Atos Ascent Thought Leadership, 2016 (7) Blockchain Research Institute, 2017 (8) Wallden, 2019 (9) Blockchain Research Institute, 2017 The impacts of quantum computing on insurance, 2021

Case study: The quantum threat to

The blockchain is a public, decentralised distributed ledger of transactions (not necessarily blockchain always financial) in which trust is established collectively by a peer-to-peer computer network. How the blockchain works The blockchain consists of blocks of transactions, each connected to the previous block via some Blockchain transactions have two stages. First is the transaction itself, e.g. sending money to someone, and the second stage is the validation of this transaction. The linking mechanism, such as the hash of the block validation stage of blockchain transactions consists of nodes in the network validating a group of transactions into a ‘block’. Transactions on the blockchain are time before. stamped and digitally signed. To digitally sign a transaction, a user will use the private key within their digital wallet, to create a public key pair which is distributed to the whole network. The network can then validate the transaction as they know that the public key could have only been generated by the person holding the private key pair. The digital signature that authenticates blockchain transactions uses PKC schemes, which are When majority of nodes agree on the authenticity of a block, it becomes validated and is added to the blockchain (using a hash key). This is usually based on a proof- of-work (PoW) principle that requires solving some mathematically hard problem, such as inverting a hash function. The first person to validate the block often gets a vulnerable to quantum computing. The further reward (a new coin in the case of Bitcoin), and so there is an incentive for nodes/users to verify transactions. If an adversary could solve the proof of work of a ‘double validation and immutability of blockchain data is spend’ (spending the same coin twice), faster than the rest of the nodes in the network, the blockchain would verify this as it would be the longest chain. However, based on hash functions, which are significantly quantum computing only offers a quadratic speed up to solving proof-of-works and so increasing the key length of hash functions and symmetric keys counteracts this threat. On the other hand, the digital signature that authenticates blockchain transactions, uses PKC schemes which are vulnerable to quantum computing speedups. weakened by quantum computers. This makes the forging of transactions and the misdirecting of funds possible. Other security mechanisms of some blockchains, such as a variant of zero-knowledge proofs called zk-SNARKs, which act to provide anonymity to the users, are also not quantum-safe. This means, years worth of all blockchain data could become suddenly deanonymized with the advent of fault-tolerant quantum computing.2 A possible future scenario that could unfold when universal fault-tolerant quantum computing Quantum-proofing the blockchain becomes available, is that companies who have not quantum-proofed their blockchain, will face The most important security aspects of blockchain relate to its immutability and the impossibility of double spending. There are two approaches that can be taken to reputational and financial damage. An adversary quantum-proofing blockchains. Either only future blocks that are added can be made quantum-secure, or all previous and future blocks could be secured (which would capable of breaking 2048-bit RSA numbers or ECC be useful for existing chains such as Bitcoin). The former is much easier and more cost-effective. The RSA and EC-DSA digital signatures would just need to be traded for PQC algorithms. The downside of many of these algorithms is the often large increase in key size and computational time needed to implement them. EC-DSA, the encryption, using Shor’s algorithm, will be able to scheme used in the Bitcoin blockchain today, is 71 bytes on average. In contrast, PQC digital signature schemes are at least 6 times larger. The most promising PQC forge digital signatures on the blockchain and algorithms for blockchain are Quantum Random Number Generators (QRNGs). QKD as well as other quantum-based technologies, that won’t be available for years misdirect funds to chosen accounts. Additionally, to come, might also help in quantum-proofing the blockchain. These include quantum authentication, quantum money, and quantum fingerprints. Grover’s algorithm which can weaken hash functions, will allow adversaries to rewrite historic Nevertheless, even in a future where the blockchain is quantum-proofed, an asymmetry in the number of users who have access to quantum computing, could still records and create fake transactions. pose a threat to the PoW principle and make double spending possible. This can happen if quantum adversaries (who in this scenario are the only ones with access to quantum computers) are able to validate transactions on average faster than everyone else, and so can double spend money without anyone noticing. The PoW for bitcoin currently takes about 10 minutes and the difficulty of it is increased as time goes by, since more powerful computers join the network. A fault-resistant quantum computer using Grover’s algorithm can solve this PoW in about one minute. This means an adversary with a quantum computer can double spend and rewrite the Institutions that use blockchain as a ledger to blockchain history by creating a fork that grows much faster than the original chain, becoming the longer of the two over time and being validating by the rest of the validate financial transactions, IoT devices that use network. This can essentially erase all previous transactions. Even if those with access to quantum computing decided not to double spend, they would still have a blockchain for micropayments and the recording of better chance at solving PoWs than others, which could lead to a concentration of power. Therefore, search functions shouldn’t form the solution to solving blockchain- safe PoWs, as Grover’s algorithm provides a speed up for this type of problem. state health data, will all be compromised in this future scenario.1 Making blockchains that are already in existence quantum-secure, requires no one to use a public key twice or for wallets that have already done so to transfer their funds to another wallet with PQC encryption. This is because a quantum computer can use the already revealed public key to find the private key and manipulate the funds in that wallet. Implementing PQC for historic blocks can be logistically difficult to do.3

Source: (1)-(3) Blockchain Research Institute, 2017 The impacts of quantum computing on insurance, 2021

In assessing whether we should be worried about the threat of quantum computing to cyber security, we need to ask three key Should we be worried? questions:

1. How soon are quantum computers capable of breaking current encryption schemes likely to be developed? The barriers to PQC adoption and the need for crypto-agility 2. How quickly are PQC algorithms likely to be standardised? Even though quantum computers with thousands of qubits capable of breaking current encryption protocols are about 15 years away, businesses and governments 3. How quickly is PQC likely to be adopted? need to start thinking about quantum security now. This is because quantum attacks can happen retroactively, and it takes time to create, standardise and implement, safe solutions. NIST has called for two rounds of PQC submissions to consider in its final list of standardised schemes. Most institutions and other standardisation agencies, are in anticipation of the results of NIST, which are likely to come out between 2022 and 2024. After the standardised list is published by The relationship between the above three timelines determines the NIST, the various algorithms suggested will go through years of rigorous testing by the cryptography community, to make sure they are safe. Executives should then threat level posed by quantum computing. The RAND Corporation be on the look out to decide when it is the right time to start investing in some of these new protocols. The testing phase of the PQC schemes can take years. If and have attempted to shed some light on these questions, by enlisting when a flaw is found, all the effort put into it developing that solution becomes obsolete. A quantum attack was found against a lattice-based scheme developed in 2007, called Soliloquy, by its creators, which meant this cryptogram had to be abandoned. expert elicitation. They expect, quantum computers capable of breaking cryptographic protocols to be available between 2033- 2035. This means quantum computing is not the end of encryption in Implementation of PQC or any new cryptographic standard can be a very expensive and lengthy process. Therefore, many firms that conduct a cost-benefit analysis, decide that using outdated cryptosystems is preferable to spending the money on new software and hardware. For example, NIST standardised SHA-2, a new the near future. Although, some experts believe that both much standard for cryptographic hash functions, in 2002. However, 35% of websites were found to still be using certificates with an older standard as late as November earlier and later developments are possible. A very small minority 2016. Many businesses, particularly those in the financial services industry, have a reliance on legacy hardware/software and an inability to quickly implement new don’t believe a cryptographically relevant quantum computer will encryption standards. Additionally, companies like to wait until their hardware has served its time before changing it out. It’s thought that the perception of “high ever be created, whilst others think major developments mean we switching costs” and the lack of urgency felt by many companies, means that adoption of new PQC standards would only take place when absolutely necessary and when all the old devices and software become obsolete. This means, new, non-PQC hardware installed closer to the time of fault-tolerant quantum computing, could could have such a device as soon as 2023. The variation in create some serious vulnerabilities. IoT devices, aircrafts and vehicles might be the slowest to adopt PQC, as they are examples of long-lived products. It is expected predictions about when fault-tolerant quantum computing will be that the adoption of PQC standards might take around 25 years! possible, means a flexible approach should be taken to managing the risks posed by this technology. Another barrier to successful PQC implementation is that many large organisations don’t have an adequate inventory of their PKI (public-key infrastructure - a framework for linking individuals to public keys for digital authentication), and all the potentially vulnerable nodes in their system (especially where there are third party agreements with other vendors). For PQC implementation to be successful, all nodes of a network need to be protected, which can be a mammoth task. Other Despite this, RAND assess the threat of quantum computing to barriers to implementing PQC include, hardware and software having set key or signature lengths that are incompatible with PQC, and the general inflexibility of our security systems to be imminent, considering the time it takes some hardware to handle other encryption schemes. The difficulty in transitioning to new cryptographic systems, including the cost of changing software and hardware, has spurred on the call for what is called cryptographic agility – the ability to implement new cryptosystems quickly, without the need to significantly to standardise and implement solutions. Experts believe that an change the existing hardware and infrastructure in place. almost complete adoption of PQC for technology businesses and governments in the UK and US (i.e. adopted by more than 95% of It is likely that the standardisation of PQC precedes the availability of cryptographically relevant quantum computing by almost a decade. In this scenario, even if organisations) will take place in the mid 2030s. If the implementation most players adopt PQC standards before the threat from quantum computing materialises, there will still be a minority who don’t (there is bound to be some old of PQC doesn’t take place before encryption-breaking quantum equipment or processes that get forgotten and neglected in the transition to PQC). This could cause problems as it increases the surface area of attack against those computers are available, this could be devastating.1 players which share a network with these vulnerable nodes. A cyber security framework published by NIST in 2018, recommends that organisations take into account supply chain risk management (managing PKC risks in the whole supply chain including third party vendors). Companies should consider transitioning to a non-PKC encryption system where the risk to their whole network is compromised by an unagile node. PQC schemes and government led approaches are already underway in countries like the USA and the UK, to ensure that NIST plan to make their efforts and standardisations global and so will need to be in contact with the International Organisation for Standardisation (ISO) to make quantum computing doesn’t turn out to be the disaster it is capable this happen. However, the global effort to transition to PQC standards is expected to take decades, which is potentially far longer than the time available for the task. of becoming. This is why thinking about quantum security now is so important. The process of transitioning to PQC may even be an opportunity to become more cryptographically agile in general, and could lead to a safer security system, regardless of whether the risk from quantum computing materialises or not. 2

Source: (1), (2) RAND Corporation, 2020 Insurance impacts – navigating the quantum realm The impacts of quantum computing on insurance, 2021

There are many insurance lines of business that will be impacted by the Insurance lines of business affected emergence of quantum computing. However, the largest potential impact arises from the cyber security risks posed by cryptographically relevant quantum computers. Cyber risks by their nature can have an influence on many lines of insurance business and practically all industries. In a scenario where the cryptographic threat from quantum computing Systemic cyber risk precedes the full adoption of PQC or other quantum-secure protocols, the world and the insurance industry face a systemic cyber risk that can affect everything from the security of our text messages to state guarded Sate sponsored cyber attacks using a quantum computer could be used to break RSA and forge digital signatures. This would allow secrets and access to military codes. adversaries access to private and public networks where they could spread malware to dismantle critical infrastructure. Falsified information could be spread using the accounts of high profile figures. Unsolicited access to weaponry and nuclear codes could be used to wreak havoc. Classified data held by the military could be decrypted and all operations, whether on land, in sea or in space would be vulnerable as global Quantum computing also exacerbates the risk faced by AI technology, networks would be compromised (systemic political risk impact). since quantum computing will improve ML capabilities, leading to a broader adoption of ML and AI solutions and products in all industries. Other nefarious adversaries, including fraudulent employees (fidelity risk), could access or alter personal, legal, operational or financial data. The impacts of AI on insurance are further discussed in the Lloyd’s report The PKI, used to distribute private keys and digital authentication certificates in military agencies and many large organisations including Taking control: AI and insurance.1 The following are few examples of financial institutions, would come under attack. This would allow the forgery of common assess cards (CAC) which are required to access insurance lines of business that can be impacted by quantum computing: classified networks and data.2 Trade secrets and IP could be stolen (some nation states already use IP attacks as part of their economic strategy). The security behind robots and IoT devices, which are likely to be employed on a wider scale due to AI improvements offered by - Product liability and product recall: Liability arises from AI-based machinery quantum computing, would be compromised. This would allow large scale supply chain disruptions ((contingent) business interruption). and products making a mistake. Whilst the risk of AI malfunction increases Autonomous vehicles could be hacked to divert their path and cause accidents (third-party motor liability). 3D printers and manufacturing once more AI reliant products enter the market as a result of improved ML machinery connected to the internet could be tampered with, leading to large scale product liability and product recall claims. The blockchain capabilities, quantum computing will also most likely improve the accuracy of technology underpinning cryptocurrencies could be manipulated to alter or forge transactions and double spend money. The privacy of civilian AI as larger data sets can be processed to train ML algorithms. Therefore, the messages, photos and medical data would also be compromised. Insurance institutions might be particularly targeted as they hold vast product liability and product recall risk landscape of robots and AI products will amounts of sensitive policyholder data, resulting in hefty GDPR fines. be changed with the emergence of quantum computing. As a result, quantum computing could pose one of the largest scale systemic risks in history. With the ever increasing interconnectedness of - Third-party motor liability: The liability complications arising from accidents systems and our reliance on digital communications, a technology capable of breaking the very encryption system behind our cyber security involving autonomous vehicles will become a reality sooner than expected, protocols would have implications that affect every aspect of our lives, from state security, to the privacy of our text messages. with ML based quantum computing accelerating the arrival of driverless cars.

- Political risks: The power of quantum computing could lead to the creation of better deep fakes, be used to better distribute online propaganda and fake Information at news and take advantage of human behaviour for social engineering. This Credit card details Private messages risk from e-commerce Cloud computing Classified access codes cryptocurrencies Intellectual property increased capability to instigate political unrest can lead to more protests, and accounts to nuclear plants and weaponry followed by government backlash, which would have an impact on business cryptographically interruption and property damage. relevant quantum computing - Property damage: The expensive hardware and control systems employed in Juvenile criminal records State secrets and Computer aided designs Trade secrets emails Online banking Genetic information quantum computing mainframes will increase the property risk profile. communications (CAD) for 3D printing and medical history

Source: (1) Lloyd’s, 2019 (2) Lindsay, 2020 The impacts of quantum computing on insurance, 2021

Business opportunities for insurers

“The quantum computing hardware and software market is growing fast, and “The quantum threat to cybersecurity is an example of could be worth more than $50 billion by 2030” a self-denying prophesy: the more credible the threat narrative, the more concerted the effort to counter it”.1 The cyber threat posed by quantum computing has Business opportunities spurred an international effort to quantum-secure encryption protocols. This provides insurers the The quantum threat to cybersecurity has incited a concentrated effort from governments and research institutions to make sure this threat never opportunity to offer risk management services to many materialises. Therefore, the systemic cyber threat posed by quantum computing, acts as a catalyst for improving cyber security standards and business. Insurers can help promote crypto-agility increasing crypto-agility across all industries. This provides the insurance sector with the following opportunities: within organisations, in an effort to mitigate the cyber - Opportunity to work directly with various clients to provide risk management services. This includes identifying vulnerable nodes in the cyber risk of quantum computing. They can also promote the security infrastructure of clients and helping them build an inventory of PKC protocols that need to be eventually replaced with PQC schemes. education of quantum threats within organisations to This would help industries address the quantum threat to cybersecurity before the arrival of cryptographically relevant quantum computing. better ready risk managers for a timely transition to - By leading in this space, insurers will be able to gain the expertise and knowledge required to guide their policyholders to a more resilient, PQC protocols and quantum-agile cyber security cryptographically-agile future, thereby thwarting the potential for a systemic cyber threat in the ecosystems they operate within. By avoiding a frameworks. systemic cyber catastrophe, insurers also ensure that they will be able to continue providing insurance products to policyholders.

Even though quantum computers capable of breaking current encryption schemes are still about 15 years The quantum computing hardware and software market is growing fast, and could be worth more than $50 billion by 2030.2 This is a substantial away, we can expect to see industry applications of emerging market with new and unknown risks, that offers insures the opportunity to provide innovative insurance products and services to quantum technology developers, distributors and adopters. The development of Quantum Computing as a Service (QCaaS) via the cloud, will also expand the quantum computing emerge in the next 5 years. This opportunity for SMEs to adopt quantum computing solutions. This growth offers insurers the opportunity to: provides insurers with opportunities to offer bespoke services and products to the emerging array of - provide a new host of quantum hardware/software start-ups and companies with insurance to meet their needs. For example, companies offering companies involved in the development, deployment quantum applications such as algorithms for enhancing risk modelling, weather prediction or fraud detection, might wish to ensure against their algorithms making incorrect decisions and affecting clients, by purchasing specialised professional indemnity or cyber products. Hardware and adoption of quantum hardware and software. developers may wish to purchase property insurance against damage to their expensive equipment.

- provide insurance and create new lines of business off the back of industries that will be spearheaded with the arrival of quantum computing (e.g. autonomous vehicles, electric cars, renewable energies, material science, patient specific drug development and therapies).

- provide innovative products and solutions to developers and adopters of QCaaS via the cloud, which is likely to be the most common way in which most companies access quantum computers. Many start-ups that have come through the Lloyd’s Lab offering innovative solutions to emerging risks. Parametrix, a Cohort 4 start-up, offer insurance for external service downtime such as cloud outages, helping to close the protection gap in business interruption. The emergence of the QCaaS sector would offer business opportunities for such Insurtechs.

Source: (1) Lindsay, 2020 (2) Boston Consulting Group Henderson Institute, 2018 The impacts of quantum computing on insurance, 2021

Operational benefits to insurers

Operational benefits to insurers: The ground-breaking computational power offered by quantum computing can deliver significant operational benefits to insurers. - The ever increasing deployment of IoT devices and sensors in various environments, has led to a boom in the volume and Munich Re transferred quantum computing from veracity of data available to insurers. Quantum computing is well placed to process this large amount of data, which the HOLD-level (placed there in 2016 and 2017), enables a much greater understanding of risk and offers opportunities for improved pricing and risk models within the to the ASSESS stage in 2018 (where it still underwriting process. There are also opportunities to collaborate with clients to share risk relevant data for creating better remains). products.

- The ability to accurately simulate weather systems delivers significant improvements to catastrophe modelling (used in property insurance), benefiting the process of pricing, reserving and setting policy limits. The modelling of other aggregate risk such as supply chain interruption, liability risks or cyber, could also benefit from quantum computing 20% capabilities - Improved customer relationship management (CRM). Quantum computing can more accurately target customers and predict their preferences based on customer behaviour data. This can enhance customer satisfaction and retention by . targeting policyholders with more pre-emptive insurance products and service recommendations . of organizations will be budgeting for quantum - Improved natural language processing (NLP) capabilities could lead to better fraud detection, market insights, trend computing applications by 2023, compared to analysis and predictive analytics models. less than 1% in 2018.1 Nature’s analysis of LinkedIn data showed that “21 banks and - Automation of the claims function in real-time using rapid data flow from smart devices, which reduces costs and drives insurance companies in the US and Europe have efficiency hired more than 115 people with quantum 2 expertise as of June 2020.” Insurers who are proactive in investing in quantum solutions as they start to emerge, can gain a significant competitive edge based on the variety of operational benefits quantum computing offers to insurers. Additionally, the accessibility of QCaaS via the cloud is likely to produce Killer Apps for the insurance sector, which increases the opportunity costs associated with insurers not investing in quantum solutions.

Source: (1) Munich Re, 2019 (2) Nature, 2020 Moving forward The impacts of quantum computing on insurance, 2021

Moving forward – six actions you could take

There are six actions insurers can take to increase their preparedness in dealing with the potential cyber risks from cryptographically relevant quantum computing and the opportunity costs involved in not adopting quantum solutions and Killer Apps fast enough. Developing a quantum strategy today will help insurers become cryptographically- agile, and well placed to start building quantum solutions as soon as the opportunity arises. Quantum computing is likely to have a significant impact on the insurance industry between 2025 and 2035.

Include the risk from quantum computing in their organisational risk assessment from 2020 onwards, Identify which quantum applications would best suit your future needs 2 and develop five year roadmaps of how to plan for the impacts of quantum computing 1 - Assess the potential opportunity cost of not adopting quantum computing applications

- Educate risk managers and executives on quantum computing applications and threats, to better help - Decide which quantum computing solution and provider best suits your needs (insurers will not need to them manage risks invest in multimillion dollar quantum computing hardware. QCaaS will offer organisations the opportunity to rent quantum computing capabilities via the cloud, for specific tasks they need). 1 - Keep up to date with latest quantum computing and PQC developments 4 Source: (1) Novarica, 2019

Implement PQC protocols as soon as rigorous testing of the algorithms has taken place Identify staffing needs 3

- keepup to datewith PQC standards - Quantum talent is not readily available and is unlikely to be able to service the inevitable surge in - Following the standardisation of PQC algorithms by NIST (circa 2022-2024), insurers might want to demand. Therefore, it’s a good idea to either start thinking about hiring and building a quantum team in consider implementing PQC protocols, as soon as they have been through rigorous testing. Waiting the near-future, or upskilling existing technically-skilled employees. to implement these protocols after they have been sufficiently tested, protects against potential - Building a quantum team early on means you will be able to take advantage of quantum applications as flaws that might exist in the algorithms, which could hinder the organisation in becoming secure soon as they become available, providing you with a competitive edge. against quantum attacks. 5 . 2 - Keep an inventory of all the places within the company that public keys are used, as these schemes will have to be migrated to PQC solutions in the future.

Make sure that communication about the cyber threat of quantum computing to decision-makers in Develop crypto-agility your organisation as well as to policyholders, finds a balance between exaggeration and complete dismissal. - Become agile in seamlessly transitioning between cryptographic protocols to best prepare for a swift transition to the safest PQC schemes, when available. - The uncertain timeline for the development of a cryptographically relevant quantum computer, makes it - Modernise all existing protocols in PKI, in a way that permits easy transition to PQC protocols easy to dismiss the threat it poses altogether. However, not taking this threat seriously enough could have devastating effects on the whole of society. - All that will happen if the cyber threat from quantum computing does not materialise, is that we will have 3 6 ended up with more cryptographically-agile security frameworks that will help to protect us against future cyber attacks.

Source: (1) – (3) Novarica, 2019 The impacts of quantum computing on insurance, 2021 Contacts Acknowledgements About Lloyd’s The following people were consulted or commented on earlier drafts of Lloyd's is the world's specialist insurance and reinsurance Lloyd’s contacts the report; we would like to thank them all for their contributions: market. Under our globally trusted name, we act as the Dr. Trevor Maynard market's custodian. Backed by diverse global capital and Head of Innovation excellent financial ratings, Lloyd's works with a global Members of the Quantum London group Operations network to grow the insured world –building resilience of – With special thanks to Paolo Cuomo & Emanuele Colonnella local communities and strengthening global economic Lloyd’s of London growth. T: +44 (0) 20 7327 6141 E: [email protected] With expertise earned over centuries, Lloyd's is the foundation of the insurance industry and the future of it. Led by expert underwriters and brokers who cover more than 200 territories, the Lloyd’s market develops the Author essential, complex and critical insurance needed to underwrite human progress. Anahita Zardoshti Insurance Graduate About Quantum London Innovation Team Quantum London are a group of professionals from different Lloyd's of London industries who are interested in understanding the business T: +44 (0) 207 327 5829 implications of quantum computing. This community was set E: [email protected] up to help ‘non-technical’ business professionals understand what quantum technology might mean for their industry, and over what timelines it might have an impact. The impacts of quantum computing on insurance, 2021 Bibliography

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