Heuristic Matching uses an algorithm (often based on Machine Learning or historical “rules of thumb”) to generate or eliminate matches faster than classical deterministic methods. Heuristic matching may be tuned to particular datasets to reduce both false-positive and false-negative matches. It may also be used as part of a broader match process to tune matching to particular use cases or business requirements.