This course is designed for Lending Managers, Heads of Departments, and senior staff who aim to enhance their credit-scored lending policies. Participants will learn to implement or improve lending strategies by combining automation and firsthand techniques effectively. They will also refresh their knowledge of lending principles to identify and avoid common mistakes or systemic issues. Through practical insights, case studies, and interactive discussions, the course equips participants with the skills to optimize lending processes and ensure robust, error-free credit systems. Target Audience Heads or Managers in lending and recoveries. All senior and support staff involved in lending and recoveries. Heads and Managers of consumer/personal finance. Heads and Managers in risk and compliance. All senior and support staff involved in consumer/personal finance. Lending Managers/Managers. Compliance & risk staff. Inspection/Audit staff. Anyone with an interest or responsibility for consumer/personal lending and recoveries. Course Objectives By the end of the program, participants will be able to: Explain the origins, principles, and context of consumer credit. Define the role of the Risk Sector and understand the credit policies framework. Conduct Individual Customer Assessments using relevant criteria and data. Describe the purpose and processes involved in Credit Scoring. Identify and utilize key Data and Databases for credit decision-making. Apply Application Scorecards to evaluate creditworthiness. Evaluate scorecard performance to assess accuracy and effectiveness. Use financial forecasting and Basel Rating Models to evaluate risk. Develop and implement effective Credit Strategies for new applications. Discuss strategic applications of scoring in risk management. What data can be confirmed? The Essence of Lending – Sustainable Free Cash Flow. The Role of Collateral. Willingness versus Ability. Terms, Clauses, and Pricing. Using Historic Data. When would a model be appropriate and why? Using Historic Data and the Impact of COVID-19. Case Study – Cash Flows. Case Study – 5 C’s. Module Four: Introduction to Credit Scoring What is credit scoring? Build your credit score and realize the scoring techniques. Score CARD Definition. Score Card Types. 3 Ways to Build Score Card. Why is credit scoring used? Business Context. Integration of Credit Scoring. What would be the input data set? Limitation of Credit Scoring. Relationship to Risk Appetite. Manual Interventions and the Requirements. Outputs versus Outcomes. Case Study – Vision. Module Five: Data and Databases The Nature of Data – Quality and Quantity. Historic Nature of Data. The Impact of COVID-19 on Data. Generic Data Sources. Application Form Data. Record Keeping and Legal Requirements. Credit Reference Data. Uses of Financial Data. Module Eight: Financial Forecasting and Basel Rating Models Forecasting bad debts. Model applications and limitations. Developing EAD, PD, and LGD models. Validation. Module Nine: New Application Credit Strategies Strategy setting. Accept-reject cut-off. Setting product facilities/conditions. Policy rules, referrals, and overrides. Types of referrals. Scoring or making manual decisions. Population stability. Cross-selling. Early redemption. Cost of management. Monitoring new applications. Measuring the impact of overrides. Module Ten: Model Validation The obligations. Sampling. What works in practice? – Model governance life-cycle key steps. Changing the model. Case Study – Credit Risk Models.