If a friend of yours has been victimized by ransomware that destroys backup environments, wipes out clusters of servers and locks down data with quantum assets recovery ransom demands then the odds are very high they will have lost their data forever. Even with solid backups it could take weeks or months to get back in business. Quantum has solutions for protecting and recovering data across the entire lifecycle, from backup environments through to post-attack recovery.
The first part of this article reviews research performed to date on quantum-enhanced versions of three major problem-solving techniques used in financial applications: stochastic modeling (Section 5.3.1), optimization (Section 6.3.2) and machine learning (Section 7.3.2). We then introduce financial use cases that are projected to lend themselves to a quantum computing approach.
Quantum Asset Recovery: Unlocking the Secrets of Lost Wealth
Financial institutions must be able to analyze large matrices in order to manage their business risk, optimize the capital structure of their assets and operations, and engage with customers more specifically and effectively. Many of these calculations are time-consuming and require the use of approximations. Quantum algorithms are expected to significantly speed up these computationally intensive and time-consuming components of financial analysis.