This course covers Alternative Data Usage Risk, which involves assessing the risks associated with using alternative data sources in credit evaluation and decision-making within the Agri & Rural Commercial Credit credit workflow. It focuses on evaluating the reliability, accuracy, relevance, and potential limitations of non-traditional data sources such as mobile transaction records, satellite imagery, digital payment histories, social data, utility payments, and other alternative information used to supplement conventional credit assessment. The course emphasizes structured execution and governance practices that support responsible data usage, risk identification, validation controls, and informed lending decisions while maintaining credit quality and regulatory compliance. It evaluates key dimensions such as misrepresentation risk, sector risk assessment, collateral evaluation, and the sustainability of rural and agri-enterprise lending, 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 reliability assessment, escalation management, and breach response related to alternative information sources, data quality concerns, fraud risks, borrower evaluation accuracy, and credit decision integrity within individual lending relationships, 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 Fraud, Misrepresentation & Data Quality, the credit manager validates team-level analysis, approves case recommendations, and manages segment-level exposure within Agri & Rural Commercial Credit, shaping escalation scope and operational priorities.