AI and data science have transformed credit risk analytics by enhancing accuracy, efficiency, and real-time decision-making capabilities. These technologies provide a more holistic and dynamic approach to risk management compared to traditional methods, enabling financial institutions to better manage risks, comply with regulations, and reduce operational costs.

Join us for a webinar to get insights into:

• Changing World of Credit Risk Analytics

  • Overview of traditional vs. modern approaches in credit risk management.
  • The importance of advanced analytics in the current financial landscape.
  • Key drivers for the adoption of new age platforms in credit risk analytics.

• Key Application Areas of Credit risk management

  • meeting regulatory requirements like Basel III/IV, IFRS 9, and stress testing.
  • enabling real-time risk analytics and decision-making
  • Continuous risk monitoring

• Advanced Analytics Techniques in Credit Risk

  • Deep dive into predictive analytics, and machine learning models to discuss how they enhance credit scoring and risk assessment.
  • Case studies on the successful application of AI and ML in credit decisions, reducing default rates, and managing portfolio risks.
  • The role of big data in credit risk: improving data collection, processing, and analysis.

• Exploring New Age Data Analytics Platforms

  • An overview of Newgen Low Code Data Science platform and the capabilities that makes data driven risk analytics possible.
  • Low code method of data analytics the brings all stakeholders, business heads credit policy owners, underwriters, and data scientists together to build data driven credit decisions.
  • Integrated model development, selection, deployment, monitoring, and governance to ensure to credit policy compliance.
  • Risk model repository and best practices for faster adoption.

 Agenda

• Introduction
• Revolutionizing Credit Risk Management: Harnessing the Power of Advanced Analytics and Modern Platforms
• Demo session
• Q&A and Conclusion