 | Credit Risk Management Canada Put Credit Risk Management Canada to work for you. Based out of Stratford and London, Ontario Debt Recovery solutions have been a cornerstone of CRM support for lenders across Canada for more than 30 years. |
 | IIR Interview - Phil Naylor on credit risk management Phil Naylor, Chief Executive, Mortgage & Finance Association of Australia, comments on home mortgage lending practices legislation, and the reassessment and repricing of risk. He will be speaking at the Credit Risk Management Conference in Sydney on the 25th to the 27th of February. For more information about the conference, visit http://www.iir.com.au/creditrisk. |
 | Webcast Preview: Better Management of Credit Risk (Part 1) In this BetterManagement.com webcast preview of "Better Management of Credit Risk: A Guide for Mid-Tier Banks, Credit Unions and Lenders", Mike Stefanick, Senior Manager, US Risk Practice for SAS talks about the current situation with credit risk management. To see the webcast in its entirety, visit http://www.bettermanagement.com/credit . |
 | Intro credit risk: expected loan return The expected return on a loan adjusts for default risk. If p = probability of repayment, then 1-p = probability of non-repayment. The expected non-repayment, E[loan amount*(1-p)], is an expected loss (EL) covered by loan loss provisions (a contra-asset account). A "cost of doing business". And (k) and (p) are not independent: higher k implies riskier loans and higher expected default. As (k) and (p) are strongly negatively correlated, beyond a certain point, higher contractually promised returns correspond to lower expected returns. |
 | Credit Risk Analysis Software This is a demonstration of Sageworks Analyst - Credit Risk Analysis Software for bankers. http://www.sageworksanalyst.com |
 | Altman's Z score for credit risk Altman's Z is the most famous type of linear discriminant model: borrowers are classified into high or low default risk categories. It does not directly give a probability of default (PD), although we can map to the score to a credit rating and map the rating to a PD (so there is an indirect path from the score to the PD). Four drawbacks: 1. Not granular: only gives default/zone of ignorance/no default; 2. Constant factor weights (i.e., factor weights may be time varying); 3. Only considers five fundamental variables, ignores other variables; 4. No centralized database on defaulted business loans (not really an Altman's critique at all) |
 | Credit risk mitigation in Basel II For secured (collateralized) exposures, the simple approach to CRM substitutes the risk-weight of the collateral (i.e., it operates on the risk-weight term of the formula). For secured (collateralized) exposures, the comprehensive approach adjusts the net exposure (i.e., it operated on the exposure term of the formula). |
 | Webcast Preview: Better Management of Credit Risk (Part 2) In this BetterManagement.com webcast preview of "Better Management of Credit Risk: A Guide for Mid-Tier Banks, Credit Unions and Lenders", the panel discusses moving beyond FICO scores to predictive analytics to improve credit scoring. To see the webcast in its entirety, visit http://www.bettermanagement.com/credit . |
 | My God is Not a Credit Risk! Pastor Stephen F. Smith is closing out his message, "My God is Not a Credit Risk" in Nashville,Tennessee at Cathedral of Praise COGIC which is pastored by The Bishop Jerry L. Maynard! www.preachsteve.com www.stephenfsmith.org www.preachstephen.com |
 | Standard approach to credit risk under Basel II The standard approach is a lookup table based on (i) external credit rating and (ii) the type of counterparty. |
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