Top 5 insurance quantum computing use cases
January 30, 2018 4:26 PM
Quantum computing in insurance
With all the hype around artificial intelligence’s potential as a differentiator in insurance, the emerging technology is still limited by organizations’ wide-scale use of binary computing—a two-number coding system leveraging the digits 0 and 1 as on and off switches to instruct computers on when to perform complex functions.
Quantum computing can help address these impediments, according to a new Novarica executive report, “Quantum Computing and Insurance: Overview and Potential Players,” by speeding up computing power through qubits—a two-state quantum mechanical system where two possibilities can be true at once. Study authors Mitch Wein and Tom Kramer offer the following five insurance use cases for quantum computing.
Quantum computing can help address these impediments, according to a new Novarica executive report, “Quantum Computing and Insurance: Overview and Potential Players,” by speeding up computing power through qubits—a two-state quantum mechanical system where two possibilities can be true at once. Study authors Mitch Wein and Tom Kramer offer the following five insurance use cases for quantum computing.
Artificial intelligence
Artificial intelligence and deep learning have emerged as key drivers in improving insurance due to their focus on making machines faster and more effective than humans. However, “computational speed limitations still exist and contemporary computing still manipulates data via binary-bit strings. While AI can yield speed improvements through automation and removal of the human element, it does not fundamentally change the nature of classical computing. Quantum technology directly addresses speed limitations of binary computing," the authors say.
Risk modeling
Insurers’ statistical risk modeling is limited by the lack of computing horsepower needed to run iterations. Running cases one at a time also limits the number of possible outcomes that can be obtained for a specific risk, Novarica says. The solution is to tether modified R and quantum computing to run as actuarial models for enhanced pricing and risk pooling precision.
“These models can be more efficiently applied with big and internal data; actuaries can run simulations using quantum-based R modeling [a statistical computing language] at higher speed and volume to create more defined risk pools,: according to the study.
“These models can be more efficiently applied with big and internal data; actuaries can run simulations using quantum-based R modeling [a statistical computing language] at higher speed and volume to create more defined risk pools,: according to the study.
Core systems
In the near term, core systems will not be largely impacted by quantum technology. Further down the road, however, carriers should expect core systems to develop pre-integration links through web services to external quantum capabilities. By the year 2030, Novarica expects core systems to be rewritten in a quantum language.
“Carriers should consider the life of new core systems packages against current forecasts for quantum capabilities in their decision-making. Likewise, vendors should begin thinking about incorporating quantum into their plans for enhancements to current systems to avoid a lag," Novarica says.
“Carriers should consider the life of new core systems packages against current forecasts for quantum capabilities in their decision-making. Likewise, vendors should begin thinking about incorporating quantum into their plans for enhancements to current systems to avoid a lag," Novarica says.
Data transfer
The adoption of photon teleportation—or data transfers using quantum methods specifically from one quantum particle to another—will enable quicker, more secure information transfer over long distances, especially if satellites are used as an intermediary, according to the study.
“Due to quantum entanglement, it is theoretically impossible to intercept quantum information in transit without detection. This has potential implications for preventing large-scale data breaches; it will also enable faster and more secure data transfer for insurers that use offshore resources for data storage and analysis," Novarica says.
“Due to quantum entanglement, it is theoretically impossible to intercept quantum information in transit without detection. This has potential implications for preventing large-scale data breaches; it will also enable faster and more secure data transfer for insurers that use offshore resources for data storage and analysis," Novarica says.
Data security
Insurance data is predominantly secured via prime number encryption, an approach that has been effective up until now, Novarica says. Using binary computation to determine the specific two-factor combination is time prohibitive as each combination must be assessed individually. Qubit computing, however, will assess all factor combinations simultaneously and “render prime number encryption obsolete," the study concludes.