Digital Credit Risk Management Training Course

Introduction

This intensive 5-day training course provides a comprehensive and practical exploration of digital credit risk management, equipping financial professionals with the advanced knowledge and tools necessary to navigate the unique complexities of online and automated lending. The rapid expansion of digital credit, from instant loans to Buy Now, Pay Later (BNPL) and peer-to-peer (P2P) platforms, introduces novel risk factors and demands sophisticated approaches to credit assessment, fraud prevention, and portfolio monitoring. This program will delve into the latest methodologies for leveraging big data, artificial intelligence, and machine learning to build robust risk frameworks, ensuring sustainable growth and profitability in the digital lending ecosystem.

The course goes beyond theoretical concepts, focusing on real-world case studies, hands-on exercises, and the strategic implications of technology-driven risk management. Through practical applications and discussions of evolving regulatory landscapes and industry best practices, attendees will learn to assess creditworthiness using alternative data, implement dynamic risk pricing, identify and mitigate digital fraud, and optimize collection strategies for digital portfolios. Whether you are a risk manager, credit analyst, data scientist, product manager, or a digital lending executive, this program offers an unparalleled opportunity to master the essential skills for effectively managing credit risk in the digital age, safeguarding your institution against potential losses and capitalizing on innovative lending opportunities.

Duration: 5 days

Target Audience:

  • Credit Risk Managers and Analysts
  • Digital Lending Product Managers
  • Data Scientists and Quantitative Analysts in Finance
  • Fintech Founders and Risk Specialists
  • Collections and Recovery Managers
  • Compliance Officers and Internal Auditors
  • Business Strategists in Digital Finance
  • IT Professionals supporting Lending Systems

Objectives:

  • To provide a comprehensive understanding of credit risk unique to digital lending models.
  • To equip participants with advanced analytical techniques for digital credit assessment using traditional and alternative data.
  • To understand the role of AI/ML in automating credit decisions and enhancing risk prediction.
  • To develop proficiency in designing and implementing robust fraud prevention and portfolio monitoring systems for digital credit.
  • To explore the regulatory challenges and best practices in digital credit risk management.

Course Modules:

Introduction

  • Defining digital credit risk and its distinct characteristics compared to traditional credit risk.
  • The evolving landscape of digital lending models (P2P, BNPL, online lenders, embedded finance).
  • Key drivers of digital credit risk: speed of decision, alternative data, fraud sophistication.
  • The imperative for advanced risk management in the digital lending era.
  • Overview of the course objectives and module structure.

Digital Credit Scoring and Underwriting

  • Traditional credit scoring limitations for digital lending (e.g., thin-file customers).
  • Leveraging alternative data for credit assessment: transactional data, behavioral data, digital footprint.
  • Psychometric analysis and social network analysis in credit decisions.
  • Artificial Intelligence (AI) and Machine Learning (ML) algorithms for instant underwriting.
  • Building and validating predictive credit models using digital data.

Fraud Prevention and Detection

  • Common fraud typologies in digital lending: synthetic identity, application fraud, account takeover.
  • Technologies for fraud detection: device fingerprinting, IP analysis, biometric authentication.
  • Network analysis and anomaly detection for identifying suspicious patterns.
  • Real-time fraud scoring and automated fraud alerts.
  • Building a multi-layered fraud prevention strategy.

Portfolio Monitoring and Early Warning Systems

  • Key performance indicators (KPIs) for digital credit portfolios (e.g., approval rates, default rates, collection efficiency).
  • Real-time portfolio analytics and dashboards.
  • Early warning indicators for potential defaults and delinquencies.
  • Predictive analytics for segmenting high-risk borrowers.
  • Strategies for proactive engagement with at-risk customers.

Dynamic Risk Pricing and Limit Management

  • Developing dynamic pricing models based on granular risk assessment.
  • Adjusting interest rates and loan terms in real-time.
  • Setting and adjusting credit limits based on behavioral data and performance.
  • Strategies for risk-based capital allocation in digital lending portfolios.
  • Optimizing risk-adjusted returns for digital credit products.

Collections and Recovery in Digital Lending

  • Automated communication strategies for collections (SMS, email, in-app notifications).
  • Behavioral economics in digital collections messaging.
  • Segmentation of delinquent borrowers for tailored collection approaches.
  • Leveraging data to optimize collection timing and channels.
  • Legal and ethical considerations in digital collections.

Regulatory and Ethical Considerations

  • Evolving regulations for digital credit risk management (e.g., fair lending, responsible AI).
  • Data privacy and security compliance (e.g., GDPR, CCPA) for alternative data.
  • Explainable AI (XAI) and model transparency requirements for credit decisions.
  • Preventing algorithmic bias and ensuring fairness in digital lending.
  • Consumer protection and recourse mechanisms in digital credit.

Strategic Integration and Future Trends

  • Integrating digital credit risk management into the broader enterprise risk management (ERM) framework.
  • Building a risk-aware culture in digital lending organizations.
  • The role of blockchain and Decentralized Finance (DeFi) in future credit risk.
  • Impact of open banking and embedded finance on credit risk models.
  • Continuous learning and adaptation to new digital lending innovations.

CERTIFICATION

  • Upon successful completion of this training, participants will be issued with Macskills Training and Development Institute Certificate

TRAINING VENUE

  • Training will be held at Macskills Training Centre. We also tailor make the training upon request at different locations across the world.

AIRPORT PICK UP AND ACCOMMODATION

  • Airport pick up and accommodation is arranged upon request

TERMS OF PAYMENT

Payment should be made to Macskills Development Institute bank account before the start of the training and receipts sent to info@macskillsdevelopment.com

 

Digital Credit Risk Management Training Course in Brunei Darussalam
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