Your HMDA-LAR data is the ground floor of a fair lending examination, and your regulators are performing detailed statistical analysis in preparation for the exam. It is a goldmine of information simply because it contains demographic information of applicants and borrowers.

Performing analysis of HMDA data is no longer a best practice; it is an expectation of examiners. They expect you to understand your own data and be able to apply a risk-based focus in your efforts.

The stakes are only getting higher: the Dodd-Frank Act contains provisions requiring additional HMDA data to be collected and submitted in the years to come, and in the years to come we'll be collecting and submitting data on commercial applications, as well.

Understanding your data is no longer a "nice-to-have"; it's a necessity. But what does this mean? How to best do this?

This program explores ways to use HMDA data in various types of analysis's. This isn't meant only for larger institutions, either. There are many tools that even the smallest community banks can (and should) utilize. Many of these analysis's can be performed with just Excel. But in today's strict fair lending examination environment, understanding your own data is a necessity.What You'll Learn:

• Collecting the information you need (it's more than just LAR data)
• Basic calculations to run to identify areas for further analysis: disparity ratios, t-values, and more
• Analyzing your data by "slices"
• Identifying problem areas
• Reviewing peer data
• Examples of tables, calculations and comparisons to run
• Analyzing pricing information
• Examiner expectations regarding additional data elements
• Identifying and analyzing "outliers"
• Regression analysis, matched pairs/comparative file review, and individual file review
• Service level analysis
• Analyzing foreclosures, modifications, and other distressed situations
• What to do with the information when you're done – reporting and escalation