Senior Advisor, Risk and Quantitative Research
Naeem Siddiqi is the author of Credit Risk Scorecards : Developing and Implementing Intelligent Credit Scoring, (Wiley and Sons, New York, 2005), Intelligent Credit Scoring: Building and Implementing Better Credit Risk Scorecards (Wiley and Sons, 2017), as well as various papers on credit risk topics.
Naeem meets with senior executives and decision makers from between 40-50 lenders globally each year, and provides strategic advice to them on areas such as the development and validation of credit scoring models, climate change risk, infrastructure planning for analytics, and retail credit risk strategy. He has also trained hundreds of bankers in over 25 countries on the art and science of credit scorecard development, and helps credit risk analysts develop better scorecards.
Naeem has an Honours Bachelor of Engineering from Imperial College of Science, Technology and Medicine at the University of London, and an MBA from the Schulich School of Business at York University in Toronto.
Intelligent Credit Scoring: Building and Implementing Better Credit Risk Scorecards (Wiley and SAS Business Series) 2nd Edition
Credit Risk Scorecards: Developing and Implementing Intelligent Credit Scoring
|2020||Economic Downturn: How Credit Risk Managers Can Prepare for Better Outcomes||On-Demand Webinar||SAS|
|2020||Credit Risk Modeling : How to Prepare for the New Normal||On-Demand Webinar||SAS|
|2019||How to use altrenative Data for credit assessment||Cairo, Egypt||SAS|
|2019||AI/ML: Lessons from Global Experience||Bangkok||SAS Customer Connection|
|2019||Getting the most from Alternative Data||Beijing||SAS Customer Connection|
|2019||Keynote: Making the most of AI and Alternative Data||Ho Chi Minh City (Vietnam)||SAS|
|2019||AI/ML and the use of alternative data for lending||Sao Paolo||Febraban (Brazilian Banking association)|
|2019||Artificial Intelligence and Credit Risk||Montreal||PRMIA|
|2019||Machine Learning and Alternative Data: Myths vs Reality||Kenya||Credit Information Sharing Conference|
|2018||Machine Learning and AI in Credit Scoring: Global Perspectives||Canada||Credit Scoring and Risk Strategy Association conference|
|2018||Machine Learning and Alternative Data: Lessons from Global Experience||Malaysia||CRO Forum Malaysia|