On Client and Transaction Identification and Matching Problems

This document discusses problems with identifying clients and matching transactions, and proposes solutions using modified Damerau-Levenshtein and edit distance algorithms. It presents an approach involving comparing attributes across client and transaction tables, determining attribute similarity probabilities and weights, and calculating a total probability for matching. Thresholds would be set at 94% for identification and 54% for similarity. The algorithm would be tailored for specific problems and regions. Evaluation and future improvements are also discussed.