Banking Evidence Extractor
Extracts and masks sensitive evidence from banking transcripts using regex and NLP for secure downstream LLM evaluation.
Banking Evidence Extractor parses banking call and chat transcripts to extract traceable conversational signals, turn structures, and metadata while strictly masking personally identifiable information (PII). Designed for intelligent quality assurance and audit workflows, it treats regex and NLP techniques as deterministic sensors that prepare sanitized, structured evidence payloads prior to semantic adjudication by large language models, ensuring strict compliance with financial data privacy standards.
주요 기능
01Decouples deterministic signal detection from semantic adjudication to minimize hallucinations
02Standardizes multi-turn dialogue inputs for automated banking quality monitoring
03Automatically masks sensitive PII to safeguard customer privacy and meet regulatory compliance
040 GitHub stars
05Generates traceable evidence snippets structured for downstream LLM evaluation
06Extracts conversational turns and metadata from banking transcripts using regex and NLP
사용 사례
01Auditing banking customer support transcripts while automatically redacting customer PII
02Preprocessing contact center logs for automated compliance and quality assurance pipelines
03Feeding sanitized, traceable evidence to LLM evaluators for dispute and claim adjudication