You develop a SQL Server Integration Services (SSIS) package that imports SQL Azure data into a data warehouse every night. The SQL Azure data contains many misspellings and variations of abbreviation

Setting the Exhaustive property to True forces the transformation to compare every input row against every row in the reference table, which would degrade performance significantly - explicitly ruled out by the requirement.

Decreasing the maximum number of matches per lookup controls how many candidate matches are returned per row but does not raise the quality bar for what qualifies as a match, so it does not reduce incorrect matches.

The similarity threshold in the SSIS Fuzzy Lookup transformation controls the minimum similarity score (0 to 1) a candidate match must achieve to be returned. Increasing it from 0.50 to 0.85 means only strings that are 85% or more similar to a reference value will be accepted, directly reducing false positives. This change improves accuracy without enabling the Exhaustive property, which would scan every index row and severely degrade performance on a large reference table.

Increasing the maximum number of matches per lookup returns more candidates per row, which would introduce more potential incorrect matches rather than fewer.