A parser reads the text of a CV, often from a PDF or Word file, and maps it into fields: employer, job title, start and end dates, skills, education and contact details. The output feeds search, filters and scoring in an applicant tracking system. Parsers can struggle with tables, columns, graphics and unusual date formats, so a strong candidate with a heavily designed CV may be captured incompletely.
Parsing errors quietly shape who gets noticed, because downstream search and ranking only see what was extracted. Teams screening at volume benefit from checking a sample of parsed records against the original files, letting candidates correct their details and making sure reviewers can always open the source CV. Scoring that reads the full document, rather than parsed keywords alone, is less sensitive to formatting.