General Information & Client Services
  • Americas: +1.212.553.1653
  • Asia: +852.3551.3077
  • China: +86.10.6319.6580
  • EMEA: +44.20.7772.5454
  • Japan: +81.3.5408.4100
Media Relations
  • New York: +1.212.553.0376
  • London: +44.20.7772.5456
  • Hong Kong: +852.3758.1350
  • Tokyo: +813.5408.4110
  • Sydney: +61.2.9270.8141
  • Mexico City: +001.888.779.5833
  • Buenos Aires: +0800.666.3506
  • São Paulo: +0800.891.2518
April 2018

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

Click Here for the Presentation

Related Insights
Whitepaper

August 2018 U.S. Middle Market Risk Report

Private firm default rates have declined steadily during the past five years. At 1.4%, the rolling 12-month default rate is down 74% from its September 2009 peak of 5.2%. This trend has been driven primarily by a decline in the charge-off rate, now at its lowest level in ten years. In addition, the percentage of borrowers in non-accrual status has decreased 56% since September 2009. The number of borrowers rated “Substandard” has seen a steady increase since the first quarter of 2016, above pre-crisis levels, reflecting banks' cautious lending practices.

August 2018 Pdf Irina Korablev, Lin Moon, Stephanie Yu
Whitepaper

Features of a Lifetime PD Model: Evidence from Public, Private, and Rated Firms

With the new CECL and IFRS 9 requirements, we see an increased need for lifetime probability of default models. In this document, we formally investigate and summarize the term structure properties consistently seen across public, private, and rated firms. We observe that the default rate for “good” firms tends to increase over time, while the default rate for “bad” firms decreases over time, an indication of the mean-reversion effect seen with firms' default risk.

May 2018 Pdf Sajjad Beygiharchegani, Uliana Makarov, Dr. Janet ZhaoDr. Douglas Dwyer

Leveraging Bank Internal Data and Industry Group Data for CECL Modelling

The presentation discussed strategic and tactical considerations when creating a CECL modeling approach. We discuss the approach of adapting models built from industry/peer group data and then examine leveraging bank internal ratings and industry data for both C&I and CRE portfolios.

April 24, 2018 Pdf Eric Bao, Dr. Yanping Pan, Yanruo Wang
Presentation

Applications of Alternative Data in Credit Decisioning

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, and text analytics for credit risk.

April 2018 Pdf Eric Bao, Irina Korablev, Rama Sankisa, Dr. Janet Zhao
Whitepaper

November 2017 U.S. Middle Market Risk Report

Private firm default rates have declined steadily during the past five years. At 1.5%, the rolling 12-month default rate is down 73% from its September 2009 peak of 5.3%. This trend has been driven primarily by a decline in the charge-off rate, now at its lowest level in the past ten years. In addition, the rate of borrowers in non-accrual status has decreased 53% since September 2009. Banks downgraded 17% of borrowers on their internal rating scales during the past year, compared to 15% in 2016.

November 2017 Pdf Lin Moon, Stephanie Yu, Irina Korablev
Whitepaper

Combining Financial and Behavioral Information to Predict Defaults for Small and Medium-Sized Enterprises – A Dynamic Weighting Approach

One large challenge lenders currently face is how to combine different types of information into metrics that can support good business decisions. Currently, the banking industry uses two primary types of information — financial information and behavioral information — independently, to assess risk. Financial information includes Income Statement, Balance Sheet, Cash Flow, and Financial Ratios. Behavioral information includes spending and payment patterns, among others. Both types of information provide unique insights, but, to date, they have not been combined to generate one comprehensive risk metric for commercial use.

September 2017 Pdf Alessio Balduini, Dr. Douglas DwyerDr. Janet Zhao, Sara Gianfreda, Reeta Hemminki, Lucia Yang
Presentation

Leveraging Industry Data for CECL Compliance Presentation Slides

In this presentation, Irina Korablev, Senior Director and Deniz Tudor, Director will discuss various tools that can capture economic, loan-level, and cohort-level data across several asset classes, which can be used for forecasting credit losses and benchmarking internal models.

August 2017 Pdf Dr. Deniz Tudor, Irina Korablev
Webinar-on-Demand

Leveraging Industry Data for CECL Compliance

In this webinar, Irina Korablev, Senior Director and Deniz Tudor, Director will discuss various tools that can capture economic, loan-level, and cohort-level data across several asset classes, which can be used for forecasting credit losses and benchmarking internal models.

August 2017 WebPage Dr. Deniz Tudor, Irina Korablev
Whitepaper

Moody's Analytics RiskCalc Transfer Pricing Solution

Tax authorities monitor cross-border, inter-company loan and financing transactions to curb tax avoidance and require arm's length pricing for such transactions. At the core of arm's length pricing is the process of understanding the creditworthiness of a borrower and identifying a typical interest rate charged to borrowers with comparable credit ratings. The Moody's Analytics RiskCalc Transfer Pricing Excel Template provides a consistent, analytical solution to the arm's length transfer pricing process. This document explains the methodology behind this tool.

August 2017 Pdf Dr. Janet Zhao, Jeunghyun Kim
Article

Machine Learning: Challenges, Lessons, and Opportunities in Credit Risk Modeling

In this article, we analyze the performance of several machine learning methods in assessing credit risk of small and medium-sized borrowers.

July 2017 WebPage Dinesh BachamDr. Janet Zhao
Whitepaper

May 2017 U.S. Middle Market Risk Report

Report highlights include: Private firm default rates have declined steadily during the past five years. At 1.5%, the rolling 12-month default rate is down 73% from its September 2009 peak of 5.3%. This trend has been driven primarily by a decline in the charge-off rate, now at its lowest level in the past ten years. Banks downgraded 16% of borrowers on their internal rating scales during the past year, compared to 14% in 2015. Among the ten states showcasing the largest change in EDF levels during the past ten years, Oklahoma and New Mexico experienced significant increases.

May 2017 Pdf Stephanie Yu, Irina Korablev, Stafford Perkins, Lin Moon
Webinar-on-Demand

CECL Quantification: Commercial & Industrial (C&I) Portfolios

In the third webinar in our CECL quantification webinars series, our experts discussed which commercial and industrial (C&I) models and methodologies can be leveraged to fulfill CECL requirements, and key considerations in transitioning these models.

March 2017 WebPage Emil LopezDr. Janet Zhao
Presentation

CECL Quantification:Commercial & Industrial (C&I) Portfolios Webinar Slides

In the third webinar in our CECL quantification webinars series, our experts discussed which commercial and industrial (C&I) models and methodologies can be leveraged to fulfill CECL requirements, and key considerations in transitioning these models.

March 2017 Pdf Emil LopezDr. Janet Zhao
Webinar-on-Demand

Data Visualization for Improved Credit Analytics and New Portfolio Insight

Market-leading risk professionals are using advanced data analytics to inform sound risk management decisions. Benchmark data can help financial institutions and corporations achieve a more holistic view of credit risk across multiple industries and regions.

December 2016 WebPage Irina Korablev, Grace Wang, Andy Condurache
Whitepaper

October 2016 U.S. Middle Market Risk Report

This semiannual report examines credit risk in the otherwise opaque U.S. private firm credit market. At 1.5%, the rolling 12-month default rate is down 73% from its September 2009 peak of 5.3%. This trend has been driven primarily by a decline in the charge-off rate, now at its lowest level in the past ten years. In addition, the rate of borrowers in non-accrual status has decreased 53% since September 2009. The number of borrowers rated “Substandard” has seen a steady increase since the first quarter of 2015, rising above pre-crisis levels, reflecting banks' cautious lending practices

October 2016 Pdf Irina Korablev, Stafford Perkins
Whitepaper

RiskCalc Banks v4.0 Model

There has been a significant increase in the demand for quantitative tools that assess the default risk of banks across different geographies. Pooling data from more than 90 countries, we see commonalities in linking default risk to a specific set of financial ratios. This finding suggests that a prescribed set of financial ratios, properly transformed, works well in estimating banks' default risk in a robust fashion. With this insight, we constructed the RiskCalc™ Banks v4.0 Model, intended for assessing the probability of default (PD) for banks across different geographies and regulatory environments. The model provides a unified framework to assess bank risk across different countries and regions, as well as different economic cycles. The one-year model is based upon a set of well-defined and ready-to-calculate financial ratios that effectively measure bank profitability, leverage, liquidity, growth, and asset quality. The five-year model combines these ratios with a measure derived from an economic capital framework based upon portfolio theory. Specifically, this measure captures the unexpected loss of a bank's loan portfolio relative to its loss-absorbing capital. Validation results show that the model delivers strong and robust power in rank ordering high risk banks from low risk banks, and that the results are robust across geographies and bank sizes.

July 2016 Pdf Dr. Douglas DwyerDr. Janet Zhao, Yanruo Wang
Whitepaper

May 2016 U.S. Middle Market Risk Report

This semiannual report examines credit risk in the otherwise opaque U.S. private firm credit market. We report trends in four different areas of risk measurement: realized defaults, internal bank ratings, financial statement-based information, and model-based risk estimates. We derive the statistics in this report from Moody's Analytics Credit Research Database (CRD®).

April 2016 Pdf Stephanie Yu, Irina Korablev, Stafford Perkins
Whitepaper

Modeling the Joint Credit-Interest Rate Dynamics on a Multi-Dimensional Lattice Platform: Model Validation and Applications in Risk Integration

This document presents validation results for the credit-interest lattice or the multi-dimensional lattice (MDL) valuation model within Moody's Analytics RiskFrontier™.

June 2015 Pdf Dr. Yanping PanDr. Yashan Wang, Sunny Kanugo, Rama Sankisa
Whitepaper

May 2015 U.S. Middle Market Risk Report

This semiannual report examines credit risk in the otherwise opaque U.S. private firm credit market. We report trends in 4 different areas of risk measurement.

May 2015 Pdf Stephanie Yu, Brian Waldman, Irina Korablev, Stafford Perkins, Dr. Douglas Dwyer
Whitepaper

Estimating Commercial Real Estate (CRE) Stressed Loss Measures Under Federal Reserve 2015 Comprehensive Capital Analysis and Review (CCAR) Scenarios

The Comprehensive Capital Analysis and Review (CCAR) program is an annual capital adequacy exercise conducted under the requirements of the Dodd-Frank Wall Street Reform and Consumer Protection Act rules. For the 2015 CCAR program, the Federal Reserve published three macroeconomic and financial scenarios to be used in the stress tests of 31 CCAR financial institutions. In this study, we analyze 22 of these financial institutions, with a total of more than $558 billion in exposures to commercial real estate loans, under the Moody's CMM Stress Testing framework. This report describes how we derive credit loss estimates for the CRE loan portfolios held by CCAR firms. Our analysis estimates that the expected nine-quarter, cumulative CRE portfolio loss through the end of 2016 is 5.6% under the CCAR 2015 Severely Adverse Scenario. The primary factor behind the slightly higher loss estimate compared to last year's stressed scenario is that the proportion of construction loans in banks' CRE portfolios has started to increase.

December 2014 Pdf Megha Watugala, Dr. Jun Chen, Kevin Cai, Eric Bao, Wenjing Wang
Whitepaper

October 2014 U.S. Middle Market Risk Report

This semiannual report examines credit risk in the otherwise opaque U.S. private firm credit market. We report trends in four different areas of risk measurement: realized defaults, internal bank ratings, financial statement-based information, and model-based risk estimates.

November 2014 Pdf Stephanie Yu, Irina Korablev, Stafford Perkins
Whitepaper

RiskCalc Plus Stress Testing Model (ratio-based approach)

In this paper, we detail a RiskCalc™ Stress Testing Model (ratio-based approach), based upon economic and accounting principles. Our simple, yet fundamental, model assumptions make the framework adaptable to many uses, including: loss forecasting, pro forma analysis, stress testing, as a challenger or benchmark model, and for customized scenario analysis.

July 2014 Pdf Dr. Douglas DwyerDr. Janet Zhao, Monalisa Sen
Whitepaper

Usage and Exposures at Default of Corporate Credit Lines: An Empirical Study

A major source of firm funding and liquidity, credit lines can pose significant credit risk to the underwriting banks. Using a unique dataset pooled from multiple U.S. financial institutions, we empirically study the credit line usage of middle market corporate borrowers. We examine to what extent borrowers draw down their credit lines and the characteristics of those firms with high usage. We study how line usage changes with banks' internal ratings, collateral, and commitment size and through various economic cycles. We find that defaulted borrowers draw down more of their lines than non-defaulted borrowers. They also increase their usage when approaching default. Risky borrowers tend to utilize a higher percentage of their credit lines as well.

Whitepaper

May 2014 U.S. Middle Market Risk Report

In this edition of our semiannual report we will examine the decline of private firm default rates over the past four years, the decrease of the number of borrowers rated "Substandard" among other credit risk topics in the US private form credit market.

May 2014 Pdf Stephanie Yu, Irina Korablev, Stafford Perkins
Whitepaper

Bank Failure Case Study: Bank of Cyprus PLC

In this report, we demonstrate the performance of the RiskCalc™ Banks v4.0 model on government bailout banks. To demonstrate the use of the RiskCalc Banks v4.0 model, we look at the 1-year Credit Cycle Adjusted (CCA) EDF of the Bank of Cyprus, beginning January 2008. RiskCalc produces a default probability combining bank-specific financial statement information and forward-looking banking-sector-wide equity market information.

November 2013 Pdf Yanruo Wang, Clara Bernard, Irina Korablev
Whitepaper

October 2013 U.S. Middle Market Risk Report

This semiannual report examines credit risk in the otherwise opaque U.S. private firm credit market. We report trends in four different areas of risk measurement: realized defaults, internal bank ratings, financial statement-based information, and model-based risk estimates. We derive the statistics in this report from Moody's Analytics CRD™ (Credit Research Database).

October 2013 Pdf Shivansh Gulwadi, Irina Korablev, Stafford Perkins, Dr. Douglas Dwyer
Whitepaper

May 2013 U.S. Middle Market Risk Report

This semiannual report examines credit risk in the otherwise opaque US private firm credit market. We report trends in four different areas of risk measurement: realized defaults, internal bank ratings, financial statement-based information, and model-based risk estimates. We derive the statistics in this report from Moody's Analytics Credit Research Database® (CRD).

May 2013 Pdf Bryce Bewley, Irina Korablev, Stafford Perkins, Dr. Douglas Dwyer, Dhivya Madhavan
Whitepaper

October 2012 U.S. Middle Market Risk Report

This semiannual report examines credit risk in the otherwise opaque US private firm credit market. We report trends in four different types of risk measures: actual defaults, internal bank ratings, financial statement-based information, and model-based risk estimates. The statistics in this report are derived from Moody's Analytics Credit Research Database® (CRD).

October 2012 Pdf Bryce Bewley, Dhivya Madhavan, Irina Korablev, Stafford Perkins, Dr. Douglas Dwyer
Whitepaper

Private US Bank Default Report: Excel Bank (Sedalia, MO)

On October 19, 2012, Excel Bank (Sedalia, MO) was closed by the Missouri Division of Finance, and the FDIC was named Receiver.

October 2012 Pdf Irina Korablev, Yu Jiang
Whitepaper

Validating the Public EDF™ Model Performance during the Credit Crisis

In this paper, we validate the performance of the Moody's KMV EDF™ (Expected Default Frequency) model during the recent credit crisis. We analyze the model performance during the past two years, and compare this performance to the model's longer history (1996-2006).

June 2009 Pdf Irina Korablev
Whitepaper

Valuation of Corporate Loans: A Credit Migration Approach

Banks and investors in loan assets have always had difficulty obtaining an unbiased and consistent value for the assets they hold. With the growth of liquidity in the loan market, the demand for a valuation method that can be consistently applied has been growing. However, the problems of loan valuation are complex. In large part this is because of the existence of embedded options and contractual conditions that can significantly affect the value of a loan. In this paper, we present the Moody's KMV methodology for valuing corporate loans, taking into account both embedded options and credit state contingent cash flows. We have found that our valuation and risk measurement methodologies compare extremely well to quotes from the secondary loan market, making their use in broad portfolios with limited secondary market prices both feasible and valuable.

January 2008 Pdf Deepak Agrawal, Dr. Douglas Dwyer, Irina Korablev