Raghavendra's famous result from 2008 fully characterizes the inapproximability of every maximum constraint satisfaction problem (Max-CSP). However, the result inherently loses perfect completeness.

Paper: Michael Saks and Rahul Santhanam, "Circuit Lower Bounds from NP-Hardness of MCSP Under Turing Reductions"
https://drops.dagstuhl.de/opus/volltexte/2020/12578/

"Paper: Yuchen Zhang, John C Duchi, Michael I Jordan, Martin J Wainwright, Information-theoretic lower bounds for distributed statistical estimation with communication constraints"

Over the past few decades, probabilistic models have become an important tool for under-standing risks and decision making in practical financial systems.