Loan Participations, CECL, Stress Testing, Loan Modeling for Banks and Credit Unions

Santa Fe, NM  |   (505) 490-6094  |

Retail Lending Analytics

Deep Future Analytics and Spring Milestone present...
Retail Lending Analytics: IFRS 9, Stress Testing, Pricing, Profitability, and Model Risk Management

Managing risks and improving profits in a world of uncertainties

Course Overview

Retail lending has changed dramatically in the last couple of decades. Machine Learning and AI bring new capabilities, regulations like IFRS 9 require model enhancements, and all models receive much greater audit scrutiny. Reliance on weak, out-dated models can create portfolio disasters. Managing a retail loan portfolio successfully depends on properly developing, validating, deploying, and integrating a wide range of models and new technologies.

Who will benefit?

This course is for analysts, managers, and credit professionals who are involved in model development, validation, or model risk management. Although the course covers the development and use of sophisticated analytical techniques, it is intended for portfolio managers, financial analysts, credit policy professionals, and statistical analysts. Anyone with decisionmaking responsibility in this field will benefit. Discussions will minimize mathematical derivations, instead emphasizing intuitive understanding, use of available algorithms, and best practices in application and implementation.

You will:
  • Learn the fundamentals of retail lending analytics.
  • Gain an understanding for when these methods can be used reliably, when they fail, and how to use new methods to succeed.
  • Obtain a deep understanding of the drivers of credit risk, and how various models capture some, or all, of these drivers.
  • Learn how to leverage the latest techniques in machine learning with an eye to successful validation and regulatory examination.
  • Acquire best practices for building models for IFRS 9, stress testing,

Le Meridien, 2 Jalan Stesen Sentral, Kuala Lumpur Sentral, KL 50470 Malaysia


Joseph L. Breeden Ph.D., Chief Executive Officer, Deep Future Analytics

Dr. Breeden has 25 years of experience in financial services and is a recognized leader in the industry. At DFA, he is directly involved in research into new modeling techniques and products. He co-founded Strategic Analytics in 1999, where he led the design of advanced analytic solutions including the invention of Dual-time Dynamics.

Dr. Breeden has created models through the 1995 Mexican peso crisis, the 1997 Asian economic crisis, the 2001 global recession, the 2003 Hong Kong SARS recession, and the 2007–2009 U.S. mortgage crisis and global financial crisis. These crises have provided Dr. Breeden with a rare perspective on crisis management and the analytics needs of executives for strategic decision-making. Dr. Breeden’s own models were successful throughout the U.S. mortgage crisis and warned of problems as early as the beginning of 2006.

His book Reinventing Retail Lending Analytics: Forecasting, Stress Testing, Capital, and Scoring for a World of Crises was published by Riskbooks in 2010. He currently serves as associate editor for the Journal of Risk Model Validation and the Journal of Risk Model Validation.


You should be comfortable with the basics of retail lending in at least one area and have some familiarity with building models in banking and have a basic understanding of credit scoring.

For questions about this course, please contact Dr. Joseph Breeden,

Day 1 (9:00 a.m. – 5:00 p.m.)

Day 2 (9:00 a.m. – 5:00 p.m.)

Model Types Overview

  Collective vs individual assessment

  Comparison of strengths and weaknesses

Vintage Modeling

  Age-Period-Cohort Decomposition

  Macroeconomic Sensitivities

  Quantifying Adverse Selection

Account-level Modeling

  Logistic Regression

  Survival Models

  Multihorizon Survival Models

Model Risk Management

  Conceptual Soundness




  Stages of impairment

  12-month vs lifetime expected credit losses

  Techniques and tips

  Issues by asset class

Stress Testing

  Climate Change


  Economic Cycles


  Regulatory Capital (Basel II)

  Economic Capital

Pricing and Profitability

  Paydown / payoff / attrition models

  Interest and fees


  Optimizing yield versus volume

Machine Learning Best Practices

  Which methods work where, and why

  ML failure risks

  ML compliance risks

Registration Fees

RM 2350 for the course including meals and snacks

Cancellation Policy

Full refunds will be available on all cancellations mailed or faxed to the registrar up to 15 working days prior
to the start of the event. Registrations cancelled 6–14 working days prior to the event are subject to a
service fee equal to 50% of the registration fee. Registrants who cancel reservations 5 or fewer working days
prior to the event will forfeit the entire fee. Registrants failing to attend the event—no-shows—will not be
eligible for refunds.