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Historical and Forecast Databases
Consumer Credit Outlook Briefings
Applications is a joint product of Equifax and Moody's Analytics, leaders in the collection, analysis, and forecasting of household credit trends. is a unique tool that provides history and forecasts for a wide range of household credit, economic, and demographic variables at a detailed level of geography. Users are able to examine, segment, and stratify credit risk and economic data across states, metropolitan areas, and rest of states. provides quarterly historical credit data back to 1998. Forecasts have a five-year horizon and a quarterly periodicity, and are updated on a quarterly basis.

Key features of include:

  • Credit trend data for different product categories and subcategories, including by Prime and Sub-Prime score splits
  • Detailed economic and demographic data
  • Blended credit and economic series (including Loan to Value and Debt Service Burden)
  • Historic and forecast risk (ERS 3.0, Smart Score 2.0, Telco Risk Score, Adv. Energy Risk Score, Adv. Wireless Risk Score) and bankruptcy (BNI 3.0) scores
  • Multiple forecasted scenarios, including a baseline most probable scenario and two alternative scenarios
  • In-depth analysis across product categories
  • Quarterly historical and forecast database updates with immediate Internet deliverability
  • Timely data updates ( historic and forecast data are available within 4 weeks of the end of the previous quarter; analysis within 7)
  • Quarterly conference calls presented by Moody’s and Equifax representatives to discuss the current economic outlook and analysis performed using the data


There are seven categories and various sub-categories available from

Category Sub-Categories
Auto Auto Finance - Auto trades opened through a dealer or auto finance company.

Auto Bank - Auto trades opened through a bank or credit union.

Total Auto - Auto trades opened through a dealer, auto finance company, a bank or credit union.

Bankcard Bankcard - Unsecured or secured credit cards issued by a bank, national card company or credit union; includes revolving and open type accounts.
Consumer Consumer Finance - Revolving or installment trade opened through a sales finance company. Also includes retail trades opened with a clothing company, department or variety store, mail order catalog (including the internet), grocery store, home furnishing store, jewelry or camera store, building or hardware store, oil company, sporting goods store, farm or gardening supply store, other retailer, or charge card/revolving trade with an auto company.
First Mortgage First Mortgage - Mortgage trades with a mortgage or real estate company, bank, credit union or finance company; exclusive of Home Equity Revolving and Home Equity Installment.
Home Equity Home Equity Total - Installment or revolving trade with a mortgage or real estate company, bank, credit union or finance company identified as home equity.

Home Equity Installment - Installment trade with a mortgage or real estate company, bank, credit union or finance company identified as home equity; exclusive of First Mortgage and Home Equity Revolving.

Home Equity Revolving - Revolving trade with a mortgage or real estate company, bank, credit union or finance company identified as revolving; exclusive of Home Equity Installment.

Student LoanStudent Loan - Student loan from a bank, credit union or finance company, or the government.
TotalTotal - Top-line summary of all the categories
All categories/subcategories (except Total) are mutually exclusive (i.e. no trade is included in more than one category/subcategory). An "Other" category is also provided when the "All" option is purchased in order to complete the universe of accounts.
Other - Primarily installment loans not otherwise classified (i.e. not auto, first mortgage, home equity, or student loan)


For each of the categories, historical data and projections are available at the national, regional, state, and metropolitan area levels for the following variables:

Total Trades
Total Balances
High Credit/Loan Amount
Utilization/Balance Outstanding
Delinquency rates (% of number)
- Total, 30-day, 60-day, 90-day, 120+ day/Collections, Severe Derogatory
Delinquency rates (% of dollar)
- Total, 30-day, 60-day, 90-day 120+ day/Collections, Severe Derogatory
Historical and forecast data are also available for several consumer credit risk and bankruptcy scores. Averages for the nation, region, state, and metropolitan areas are provided, as well as range distributions for ERS 3.0:

Score Range Performance Predicted Target Population
Equifax Risk Score 3.0 - Odds Scale 280-850, higher score=lower risk 90+ Days Past Due or Worse in 24 Months General
Smart Score 2.0 - Odds Scale 280-850, higher score=lower risk Charge-off+ in 12 Months Sub-prime
Bankruptcy Navigator Index 3.0 1-300, higher score=lower risk Bankruptcy in 24 Months General
Telco Risk Score 200-840, higher score=lower risk 60+ Days Past Due or Worse in 12 Months on Telco General
Advanced Wireless Risk Score 1-999, higher score=lower risk 60+ Days Past Due or Worse in 6 Months on Wireless General
Advanced Energy Risk Score 1-999, higher score=lower risk 90+ Days Past Due or Worse in 12 Months on Energy General

Historical and Forecast Databases

Historical Data
The historical credit data are made available from the Equifax National Consumer Database, which contains information collected from over 60,000 contributors who furnish data on tradelines, collections, public records and demographics across a broad range of industries, with updates on a daily basis. Within a month, the database experiences on the order of 1.5 billion tradeline updates, 45 million collection updates, 500 thousand public record updates, 180 thousand bankruptcy updates and 12 million address changes, as well as over 70 million phone number updates annually. Information being added to the database goes through a rigorous quality assurance process, including automated and manual reviews, to ensure the highest accuracy possible.

A 5% random sample of the Equifax National Consumer Database, approximately 14 million files, is selected every month. Selection always occurs at month-end so that the results are not affected by any in-month reporting fluctuations. The 5% samples do not track the same consumers over time, but are independent random samples each month. Changes in the universe of credit-eligible consumers are thus tracked, rather than that of a fixed set of customers. Quarterly 5% samples were used going back to the beginning of 1998.

Equifax developed special credit trend attributes that aggregate the consumer file into attributes specifically intended for quarterly trending. These attributes consider only trades with activity in the last three months and only look at current delinquency statuses in order to focus on the true state of credit (balances, high credits, delinquencies, etc.) in the given quarter. These attributes were calculated for each consumer file in the sample and then aggregated to the zip code, county, metro area and state levels. This will allow to quickly adapt to upcoming changes in the county definitions of metro areas.

Prime/Sub-Prime classification is based on ERS 3.0 - Odds Scale (score range 280-850) with score cuts follow OCC guidelines by industry:

IndustrySub-Prime Score Cut
Auto Finance<640
Auto Bank<640
First Mortgage<620
Home Equity Installment<620
Home Equity Revolving<620
Student Loan<660

Forecasting done for Prime and Sub-Prime separately; Total forecast is additive. Classification is done at the consumer level, based on the consumer's score at the given quarter (rather than on a loan-by-loan basis at time of origination).

Comparison with Other Data Sources
The historical data have a number of significant advantages over publicly availably sources of credit data. These other sources include data on consumer loan delinquencies from the American Bankers Association, mortgage loan delinquency and foreclosures available from the Mortgage Bankers Association, and consumer and mortgage delinquency and charge-off data available from the Federal Reserve Board and FDIC.

The most significant advantage of the data is that they are available for the nation, states, and metropolitan areas. The ABA and MBA data are available only for the nation and states, and the Federal Reserve Board and FDIC data are only available for the nation.

The data are also timelier than other sources of credit data. It is made available within 6 weeks of the end of the quarter, compared to 2-3 months for the other sources.

The data are also based on where the borrower resides. The ABA data by contrast are based on the branch or operating location of the lending institutions participating in the survey. This may or may not coincide with where the borrower lives. This is of particular importance for the ABA's data on bank cards given that many of the cards are originated by lenders with operations in New York, Delaware and South Dakota for borrowers that live all over the country. The MBA does ask lenders to report by the state where the property is located.

Since the data are based on borrower information they are not affected by changes affecting lenders. The ABA and MBA data can be significantly affected by any change by the lenders included in their surveys. For example, the MBA has recently expanded the number of subprime mortgage loans in their survey, resulting in a substantial increase in measured credit problems. Actual credit quality has not eroded to such a degree. The Federal Reserve and FDIC data, which are based in part on Call reports provided by lending institutions, can also be affected by changes in the status of lenders. Historically, the acquisition by a large commercial bank of a retailer's credit card portfolio and the resolution of failing lending institutions have affected measured credit quality.

Forecast Data
Projections of the credit, economic and demographic variables are available with a quarterly periodicity and a five-year forecast horizon. Forecasting is done for the Prime and Sub-Prime separately; Total forecast is additive. The forecast database includes a baseline most probable forecast and two alternative scenarios. The alternative scenarios vary according to where we are in the business cycle. For instance, when the economy is weak, a mild recession or a severe recession scenarios may be most appropriate. In a recovering economy, a pessimistic and an optimistic scenario are likely to be more appropriate. The projections are updated with new history and forecasts four times per year.

The economic and demographic forecasts are produced using Moody's Analytics's detailed econometric model system. A description of this system is available upon request. The credit forecasts are produced with a model developed using a recursive pooled time series and cross-sectional specification. Each equation is estimated for all metro areas using the available historic data. The equations are log-linear in form, meaning the terms (unless otherwise indicated) are specified as the natural logarithm and the coefficients can be interpreted as elasticities. All the equations contain metro area-specific constant terms to capture the metro area-specific fixed effects. Finally, all of the equations contain an autoregressive term to capture the inertia in the series.

Consumer Credit Outlook Briefings subscribers will be able to participate in quarterly conference calls devoted to a discussion of current and anticipated trends in household credit conditions. Each call begins with a brief description of the current economic environment and baseline forecast and includes an assessment of risks to the baseline forecast. We then discuss recent and forecasted trends in consumer spending, balance sheets, and credit usage. Each call lasts from 60 to 90 minutes and includes an accompanying PowerPoint presentation.

For more information on signing up for a Consumer Credit Outlook Briefing, contact your Equifax consultant or Moody's Analytics at 1-866-275-3266. Outside of the U.S. or Canada, please call 610-235-5299.


Benchmarking can be used by lenders to benchmark their portfolio's performance against that of the entire credit market. This can be done across product lines and detailed levels of geography and for both the growth in credit and credit risk. Historically lender benchmarking has been done solely vis-à-vis specific competitors. allows for benchmarking against the entire market, which will allow lenders to identify risks and opportunities that cannot be determined by benchmarking against a self-identified set of peers.

Scoring can be used by lenders to improve the predictive ability of their current customer-level scoring. Lenders have historically used credit scoring models based only on customers' past credit history. Since economic conditions change quickly and are oftentimes different than those that prevailed historically, credit decisions based on credit scores developed using historical information do not fully account for all the information available to lenders. provides lenders with a method to incorporate forward-looking economic information into credit decisions.

Profit and Loss Forecasting can be used to improve the accuracy of P&L forecasting. Most P&L forecasting done by lenders at a portfolio level does not take into account the changing economic environment. These models are often based on historical roll rates that remain constant regardless of economic conditions. Roll rates are highly dependent, however, on the health of the job market and broader economy. P&L models in which roll rates are a function of economic and credit variables available from thus result in more accurate forecasting.

Sensitivity Analysis can be used to evaluate the sensitivity of lenders' portfolios to shifting economic conditions. Just how important are falling unemployment or rising interest rates to loan growth and credit quality? Do they vary significantly across product line and regions of the country? Lenders can determine whether, for example, a strongly expanding economy experiencing lower unemployment, but higher inflation and interest rates, will have a negative impact on the credit quality of their mortgage versus credit card portfolios.

Regulatory Oversight can be used by regulators to assess the performance of financial institutions. Certain lenders may be at heightened risk of suffering credit losses given their regional and product line exposure. This risk can be measured using Mortgage lenders in California, for example, may be at greater risk in a rising rate environment given surging activity and housing values in the state in recent years. Lenders can also use to demonstrate to regulators their ability to measure and manage risk.

Investing can be used by investors evaluating opportunities and risks in the rapidly growing asset and mortgage-backed securities markets. Do interest rate spreads on ABS and MBS pools adequately reflect current and prospective economic and credit conditions? Are interest rate spreads appropriately discounting regional economic and credit differences across pools? Equity investors can also use to evaluate earnings growth prospects and stock price valuation of lending institutions.