This course covers Data Gaps & Estimation Risk, which involves assessing the risks that arise from missing, outdated, incomplete, estimated, or otherwise unreliable information used in the evaluation of distressed borrowers within the Distressed & Structured Asset Credit (ARD) credit workflow. It focuses on determining how information deficiencies may affect credit assessment accuracy, restructuring decisions, recovery planning, valuation outcomes, and overall risk evaluation. The course emphasizes structured execution and governance practices that support objective information validation, estimation review, risk identification, and informed decision-making for distressed credit exposures. It evaluates key dimensions such as risks arising from missing, outdated, or estimated information, along with information completeness, with each requiring independent validation and documented rationale before any credit action is finalized. It is distinct from broader portfolio diversification strategy, as it focuses specifically on structured identification, data quality assessment, estimation risk evaluation, escalation management, and breach response related to information uncertainty, reporting limitations, analytical assumptions, and decision-making reliability, while portfolio diversification strategy addresses wider portfolio allocation, concentration management, sector balancing, and enterprise-level risk optimization with separate evidence standards, ownership, and approval authority. Within Information Reliability & Data Integrity, the credit analyst executes the assessment, completes documentation, and flags exceptions for manager review within Distressed & Structured Asset Credit (ARD) credit files, shaping escalation scope and operational priorities.