This course covers Repeated Restructuring Signals, which involve assessing recurring requests for loan restructuring, repayment modifications, tenure extensions, moratoriums, or other credit accommodation measures that may indicate persistent borrower stress within Credit Monitoring & Portfolio Surveillance workflows. It focuses on identifying patterns where borrowers repeatedly require restructuring support, suggesting underlying weaknesses in cash flow generation, business performance, financial stability, or repayment capacity. The course examines how monitoring repeated restructuring activity supports the early identification of deteriorating credit quality, elevated default risk, and potential transition toward non-performing asset status, enabling proactive portfolio risk management and timely escalation. It evaluates key dimensions such as control lapses, early warning signal identification, risk trend analysis, and proactive portfolio risk management, with each requiring independent validation and documented rationale before any credit action is finalized. Particular emphasis is placed on restructuring history analysis, borrower viability assessment, repayment sustainability evaluation, trend monitoring, exception identification, and governance oversight of accounts displaying recurring restructuring patterns. It is distinct from a portfolio restructuring mechanism, as it focuses specifically on identifying and assessing repeated restructuring activity as an early warning indicator within existing exposures, rather than the broader strategic framework used to design and implement restructuring programs across a portfolio. Within Early Warning Signal Identification, the senior credit leader sets portfolio limits, governs exception criteria, and drives strategic alignment across the Credit Monitoring & Portfolio Surveillance function, shaping escalation scope, risk priorities, and portfolio management decisions through effective monitoring of repeated restructuring signals and emerging borrower risk conditions.