The Iran Venture Capital Association organized a two-session training workshop on credit risk management, focusing on credit assessment, on September 24 and October 1. Attended by CEOs, executives, and specialists from the Association’s member companies, the workshop aimed to introduce the fundamentals of credit assessment, examine the challenges of evaluating the creditworthiness of innovative businesses, and present methods and tools for managing credit risk.
The first session was led by Dr. Sabeti, a risk management expert and member of risk committees at banks and financial institutions. He introduced the fundamental principles of credit assessment and examined the challenges of achieving accurate credit evaluations in processes such as loan approvals and the issuance of guarantees.
The second session, held on October 1, featured managers and specialists from Iran Credit Scoring Company. It covered credit assessment mechanisms, credit risk management, the evaluation of innovative businesses, responsible artificial intelligence (AI), and how organizations can utilize credit assessment services.
During the session, Milad Rahimi-Moghaddam, Director of Innovation and Product Development at Iran Credit Scoring Company, explained the process of transforming credit data into actionable information for decision-making. He outlined how the process begins with data collection and integration, followed by feature engineering, modeling, and the calculation of credit scores and ratings. These steps ultimately lead to the generation of reports that support risk assessment, decision-making, and ongoing risk monitoring. He also highlighted the role of credit assessment in gaining a better understanding of applicants, enabling data-driven decisions, and identifying and monitoring credit risks.
Another segment of the workshop addressed the challenges of assessing the creditworthiness of knowledge-based companies and startups. Mahmoud Yadegari, Director of Artificial Intelligence and Data Science at Iran Credit Scoring Company, explained that a limited financial or borrowing history does not necessarily indicate poor creditworthiness for an innovative business. He identified the use of alternative data, supplementary risk assessment indicators, and the analysis of relevant credit relationships as approaches that can provide a more accurate understanding of these companies’ credit profiles.
The workshop also explored credit assessment within the framework of responsible AI. Beyond the predictive accuracy of credit scoring models, key considerations included explainability, fairness, transparency, robustness, privacy protection, regulatory compliance, and human oversight. These factors were discussed as essential considerations when applying AI-driven models to credit decision-making.
In the final segment, Sara Ashough, Director of Marketing and Business Development at Iran Credit Scoring Company, introduced the company’s services and products. She presented various credit reports covering individuals, legal entities, and checks, along with supplementary risk management products. She also explained how organizations can access credit assessment services through a dedicated business portal and an Application Programming Interface (API).
Overall, the workshop was designed to provide participants with a comprehensive understanding of how credit data can be transformed into financial decisions and how credit assessment can improve decision-making quality and credit risk management.
بدون دیدگاه