SOC 2 PI1.1: Processing Integrity - Completeness, Accuracy, and Timeliness Objectives

Document processing specifications for every critical system and service. For each one, define the expected inputs (data formats, validation rules, acceptable ranges), the processing logic (transformations, calculations, business rules), the expected outputs (formats, delivery mechanisms, quality standards), and timeliness requirements (processing windows, SLAs, maximum acceptable latency).

Define data quality dimensions and what they mean for each type of data you process. Spell out what completeness, accuracy, validity, consistency, and timeliness look like in concrete, testable terms. Create validation rules: required fields must not be null, financial calculations must balance, dates must fall within valid ranges, cross-system data must reconcile.

Share these specifications with the people who need them. Give internal teams the full technical detail. Give customers clear product documentation, API documentation, and service descriptions that explain what processing is performed and what to expect. Make sure marketing materials actually reflect what your systems do.

Implement input validation that enforces your quality requirements at the point of data entry or receipt. This includes field-level checks (type, format, range), record-level checks (required fields, business rule compliance), and batch-level checks (expected record counts, control totals, header/trailer validation).

Maintain system documentation that traces the processing flow from input to output. Data flow diagrams, process maps, and technical specifications all work. The critical part is keeping them current when processing logic changes - stale documentation is worse than no documentation because it creates false confidence.

Track processing quality metrics: error rates, rejection rates, processing timeliness, data quality scores. Report them to management and use them to spot problems before customers do.