In episode 100 of The Quantum Computing Podcast, Lucas and Luna explore how quantum algorithms are beginning to challenge classical financial models that have stood for decades. They focus on a specific case: the use of quantum Monte Carlo methods for portfolio optimization at JPMorgan Chase's quantum research lab. Lucas explains why quantum computers could price complex derivatives and simulate risk in minutes instead of days, and Luna questions when this will move from experimental to practical. The hosts also discuss a recent paper from D-Wave Systems showing a quantum annealer beating classical solvers on a credit card fraud detection problem. No hype—just a concrete look at where quantum finance stands today.

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