With an immense amount of available data generated worldwide within the last two years, the next evolution of banking analytics will include information from a variety of open and closed sources.
At Moody’s Analytics, we are leveraging our credit risk expertise and long history of data and modeling to address the ever-growing demand for more insightful analytics. We are currently evaluating the predictive outcome of these alternative datasets as they are applied to various stages of the credit process. Given the promising results so far, we believe this is the future of more powerful decisioning capabilities within the financial industry.
In this webinar, a panel of research and data scientist experts across Moody’s Analytics discuss:
- Social data in probability of default modeling
- Closed and open data for location scoring
- Text analytics for credit risk
Coronavirus (COVID-19): Credit Risk Impact on Commercial Real Estate Loan Portfolios (September 2020 Update)
As an update, this study continues to monitor COVID-19's impact on the credit risk of financial institutions' commercial real estate (CRE) loan portfolios under latest baseline and Fed scenarios.
This article examines the financial health of small businesses prior to COVID-19 based on a unique dataset covering the last 20 years.
Originating, scoring, and maintaining proactive knowledge of your lending book can be an overwhelming task.
COVID-19 has impacted several industries. We examine qualitative overlays to CRE loans that can be made no matter your CRE model.
Moody’s Analytics analyzed a range of plausible outcomes of quantitative expected losses under CECL, incorporating COVID-19 impacts across commercial and industrial (C&I), commercial real estate (CRE), and retail loans.
CECL was scheduled to go into effect at the beginning of 2020 until COVID-19 disrupted businesses. Moody's Analytics analyzed a range of plausible outcomes of quantitative expected losses under CECL, incorporating COVID-19 impacts across commercial and industrial (C&I), commercial real estate (CRE), and retail loans.
This study takes a scenario analysis approach and dissects the credit risk impact on financial institutions' commercial real estate (CRE) loan portfolios under various COVID-19 scenarios.
This document presents an approach that converts Through-the-Cycle (TTC) Probability of Default (PD) measures to Point-in-Time (PIT) measures and produces a lifetime term structure.
Learn to differentiate C&I, CRE, retail, and securities. Choose approaches at the right level of flexibility and sophistication. Apply model-free solutions based on historical internal or industry data.
Is a financial statement decision useful? Is it informative enough to make a loan, acquire a company, increase a limit or move a borrower to work out? The quality of financial statements is a concern for all firms, especially as the demand for faster and more accurate due diligence grows.