Post financial crisis risk management at financial institutions must be future focused and probative—not a mere
chronicling of the past. CRMA meets this standard.
Your Data. Your Future.
CRMA (Credit Risk Migration Analyzer©), CRM's proprietary solution provides a meaningful break from linking historical net charge-offs
to estimates of future defaults and losses. The Company's process flexes for a forward looking stress testing and trend analysis by
leveraging and reverse engineering a financial institution's portfolio data to discover institution-specific Default Probabilities ("PDs")
and Loss Given Defaults ("LGDs"). These metrics are then matched with loan-level risk grade migrations and modeled probabilistically.
CRM's CRMA product Accomplishes This:
Unleash the Power of your Loan Data to stress and manage credit risk and to estimate potential credit losses and reserves.
Understanding the risk associated with the various types of loans constituting a financial institution's loan portfolio plays an integral role in its
ability to properly measure its risk adjusted return and estimate its formula-based reserves. To better understand these risks throughout
the business cycle, the use of data modeling tools and frameworks to estimate and forecast losses are often encouraged. The use of such
risk parameters replaces a number of the subjective elements inherent in many financial institutions' credit loss estimates with the Institution's own historical
risk migration and loss data.
CRMA...
- Currently runs in financial institutions, including a credit union (one as large as $5B), plus its methodology has provided estimate for potential
credit losses (PCL's) in numerous M&A or capital raise due diligences.
- Provides a variety of uses without sacrificing its methodology (see Key Applications below)
- Uses institution-specific data (primarily the regulatory flat file)
- Is forward looking
- Informs loan underwriting controls and pricing decisions by product type
- Is fully auditable and has been accepted by accountants and regulators; has been validated by mathematicians, and back-tested
- Avoids the currentcy of data traps with conventional stress testing
- Controls the disproportionate effects of historical losses (as markets begin to recover and portfolios begin to shift)
- Endures beyond the financial crisis to continue as a reliable risk management tool
- Provides output useful for Enterprise Risk Management and loan pricing decisions
- Feeds blind pool data, maintained by CRM, and used for comparative purposes
- Drives the credibility CRM enjoys nationwide with investment and aggregator bankers, PE and investor groups.
Stress Testing
Unleash the Power of your Loan Data to perform stress tests and probabilistic loss modeling by loan product.
CRMA's Migration-Based Approach to Stress Testing quantifies the impact of changing economic conditions on asset quality, earnings and capital.
It also allows Management to form contingency plans in the event downside scenarios occur.
Probability of Default and Loss Given Default parameters can be combined to provide potential credit loss estimates that are comprehensive,
well-documented, and institution specific. Based on the established probabilities and losses, CRMA enables stress testing of the portfolio in a
manner consistent with the methodology typically used to measure capital adequacy. In order to estimate potential credit loss occurring under
varying levels of macro-economic stress, CRMA applies graduated factors, including scenarios furnished by the Federal Reserve and harsher treatment
of impairments than recognized for ALLL purposes.
Rather than depending on the variously and inconsistently obtained traditional underwriting data points such as DSC, LTV and DTI,
CRMA assumes the risk grade to be the proxy, or principal representative, of a loan's risk profile—and stresses accordingly.
Included in the Stress Test are:
- Potential Credit Losses under Baseline Scenario Approach
- Potential Credit Losses under a Stressed Scenarios
- A probabilistic View of Credit Loss (Value at Risk Analysis*)
ALLL (loan loss reserves)
Unleash the Power of your Loan Data to estimate ALLL (Allowance for Loan and Lease Loss Reserve) provisioning.
CRMA's key attributes include its ability to:
- Leverage data from existing internal risk rating systems to inform institution-specific estimates of credit loss;
- Provide forward-looking credit loss estimates on a loan-by-loan basis;
- Use an Internal Ratings Based approach to estimate loan default probabilities;
For ALLL purposes, CRMA will estimate a Financial Institution's formula-based (non-impaired) reserves using Probability of Default ("PD") and
Loss Given Default ("LGD") parameters informed by historical risk grade migration and net charge-off data. The use of this type
of Migration-Based Approach will leverage the Institution's internal risk rating system to develop defendable, repeatable, institution-specific
credit loss estimates. Coupled with impairment-specific reserves CRMA then allows application of qualitative and environmental factors to
round out the reserve estimation.
All analyses are based on the Financial Institution's existing risk grading system, past due data and net charge-off data.
Estimates of Potential Credit Losses (Capital Raises / M&A's)
Unleash the Power of your (or target) Institution's Loan Data to estimate potential credit losses—beyond the level of reserves—with impact on capital.
CRMA is the basis for estimates of potential credit losses (PCL's) in numerous capital raise and M&A due diligences.
It models existing and stressed states of the portfolio based on the current state of portfolio quality. The current state of portfolio quality is primarily measured
by recommended impairments and risk grades (enhanced from a Loan Review) and viewed in conjunction with the remaining Financial Institution risk grades. Expected losses against the risk
grades are measured by CRM default rate study and on the impairments by CRM impairment estimates. In general, PCLs are expected to come first from impaired loans, then
non-impaired criticized and classified loans and then from the pass loan pool. CRM presents a range of outcomes based on the described methodology and assumptions.
To complement a historical loss-based Low / Medium / High PCL estimate, CRMA produces a like range including a Mean (medium) and +one standard deviation (high)—overlaid
by a probabilistic loss distribution model.
Risk Grade Integrity
Unleash the Power of your Loan Data to validate your risk grading integrity—portfolio-wide and by loan product and other measures.
Using the Financial Institution's regulatory flat file, and through an automated process, CRMA observes migration of the Institution's loan balances between risk grades and to default and
pay off status. This shows from what risk grades the Institution's loans have historically defaulted, thus enabling Management to confirm the expected strong correlation
between initial risk grade assignment and PD.
Such process provides a basis to test both the design and implementation of internal controls surrounding a Financial Institution's internal risk rating system and is:
- Cost effective
- Comprehensive
- Mineable
