q factors: how to justify in periods of low loss
DESCRIPTION
Qualitative factors, or "Q factors" for short, can be a black box for bankers looking to build an objective ALLL calculation. In times of low losses, it can be even more difficult to justify these qualitative factors. This slideshow offers recommendations to add objectivity, directional consistency, and improve the process behind the qualitative portion of the allowance calculation as a whole.TRANSCRIPT
Q FACTORS: HOW TO JUSTIFY IN PERIODS OF LOW LOSS
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About Sageworks
+ Financial information company that provides credit and risk management solutions to financial institutions
+ Data and applications used by thousands of financial institutions and accounting firms across North America
+ Provides resources including: whitepapers, webinars, videos, and templates for bankers, accessible at www.sageworksanalyst.com
Who will be speaking?
Garrett Morris - ModeratorManaging director of consulting
services at Sageworks
Aaron Lenhart - PresenterRisk management consultant at
Sageworks
Learning Objectives
+ What are qualitative factors?
+ Why the subjectivity?
+ How has it evolved?
+ Largest obstacles
+ How to justify adjustments to qualitative factors, particularly in times of low loss
+ What are the regulatory expectations?
+ Internal and external drivers
+ Conclusion
What are Qualitative Factors?
+ Qualitative and environmental factors are used to reflect risk in the portfolio not captured by the historical loss data
Why the Subjectivity?
+ 2006 Interagency Policy Statement on the ALLL
+ Qualitative adjustments are subjective by definition
+ The 2006 Interagency Policy Statement on the ALLL provides little direction, advising only that “management should consider those current qualitative or environmental factors that are likely to cause estimated credit losses as of the evaluation date to differ from the group's historical loss experience. These determinations are to be based on a comprehensive, well-documented and consistently applied analysis of its loan portfolio.”
How Has it Evolved?
+ Often viewed by bankers as a plug or “manipulative” factor for their allowance calculation
+ They draw close scrutiny from regulators
Largest Obstacles
+ Limiting subjectivity
+ Justifying assumptions
+ Providing proper documentation and defense
Recent Periods Reflect Low Losses
FAS 114s Fall, FAS 5s Rise
Things to consider in periods of low loss
+ Basic rules when handling declining historical loss
+ Improving process/does lookback period make sense?
+ Can I justify a “net 0” change?
+ Risk of overinflated adjustments
+Thomas Curry’s statement – don’t be too quick to release reserves
Other Banks’ Q Factors: Q2 2014
Unallocated Reserve?
+ Intended to address environmental risk outside of standard Q factors
+ Can potentially draw scrutiny (particularly from auditors)
+ Can be easier to justify than using Q factors to “artificially” increase loss rates/maintain current reserve levels
+ Try to keep unallocated reserve to no more than 5%-10% of total ALLL
+ Clearly stated policies and documentation of assumptions and procedures are a must
How to Justify Assumptions
+ Use recommended factors
+ Consider Qualitative Scoring Matrix
+ Ensure Directional Consistency
Use Recommended Factors – Internal Factors
+ Lending policies and procedures, including changes in underwriting standards and collections, charge offs, and recovery practices
+ Nature and volume of the portfolio and terms of loans
+ Experience, depth and ability of lending management
+ Volume and severity of past due loans and other similar conditions
+ Quality of the organization’s loan review system
+ Existence and effect of any concentrations of credit and changes in the levels of such concentrations
Use Recommended Factors – External Factors
+ Value of underlying collateral for collateral-dependent loans
+ International, national, regional and local conditions
+ Effect of other external factors (e.g. competition, legal and regulatory requirements) on the level of estimated credit losses
Use Recommended Factors – Others?
+ Can be used for institutions that have unique risk scenarios to incorporate
+ For example, a bank with a large concentration of loans to Native American businesses, tribal news might be a significant factor
Ensure Directional Consistency
+ As factors change direction, qualitative rates should
change accordingly:
Drivers for Q Factors
+ Each qualitative factor has drivers that are the recommended variables to measure over time
+ Internal drivers+ External drivers
Internal Drivers
Lending policies and procedures Noted changes in policy requirements, new procedures, % renewed with policy exceptions
Nature and volume of the loan portfolio and terms of loans
Loan growth, maturity analysis, vintage analysis, pricing compared to benchmarks, new products
Experience, depth and ability of lending management
# of new positions, % with >good performance, change in % of staff <3 years experience
Internal Drivers (Cont.)
Volume and severity of past due loans % of segment past due or on nonaccrual, % change in segment past dues, # or % of TDRs
Quality of loan review system Exception rates per loan review report, grade variances, frequency of reviews
Existence and effect changes in the levels of such concentrations
Concentration % of portfolio, concentration as % of capital, segments over limits
External Drivers
Value of underlying collateral for collateral-dependent loans
# of stale appraisals, % of appraisals > 2 years old, # of RE-secured loans with LTV>70%
International, national, regional and local conditions
National and local unemployment, GDP rates, industry or economic data
Effect of other external factors (i.e. competition, legal and regulatory requirements) on the level of estimated credit losses
As needed but could include litigation, enforcement actions in process, new competitors
External Data - FRED
+ Federal Reserve Economic Data (FRED) provides free, customizable macro-level data:
External Data – Sageworks Industry Data
+ Objective industry analysis based on financial performance metrics weighted by NAICS code
+ More granular analysis to reflect the unique industry composition of each pool
Conclusion
+ Top 3 things to remember:1) Use recommended Factors and Drivers
2) Consider a Qualitative Scoring Matrix to limit subjectivity
3) Ensure Directional Consistency
Document, document, document…and then document some more.
Questions
Garrett MorrisManaging Director of Consulting [email protected] ext. 568
Aaron LenhartRisk Management [email protected] ext. 532
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