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To Rate or Not To Rate, the question is just by how much!

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To Rate or Not To Rate, the question is just by how much!

To Rate or Not To Rate, the question is just by how much!

Whether you use a rating model or you are considering a rating model for your financial services businesses, one vendor, a perceived market leader, claims that you will struggle with the competitor output (model) and will be difficult to get regulator approval as their models are far superior. You’ve heard it all before, one vendor stating their solution is better than the other vendors in the market.

The fact remains;

Irrespective of which rating vendor you choose, the rating model is a tool, it’s a tool to support the credit decision making process and not the method by which a decision is made, and the model’s judgment of a particular business should never be taken as a guide on whether the business will do well or not or it’s probability of repayment of a facility post default.

The regulators are not required to approve which rating platform you select, it’s an internal tool, and it contributes to the multi-level and multi-dimensional collateral used by various layers of panels of experienced executives who are part of the decision making process.
You just have to make your credit policy clear, water tight, and the methods used to derive probability of defaults and approvals are defencible.

Furthermore making a decision to choose one model platform against the other based on, “we are the leader in the region” or “our models are better than the others” is superfluous. Most of the leading rating agencies are being sued for their similar rating results on toxic products that were part of the global financial crisis, and in many early circumstances they are settling out of court to contain the avalanche legal activities against them.

The advantage of a vendor’s regional footprint is local knowledge and perhaps tailoring of models to suit the region. Most respected rating agencies are global companies, but none can be leaders in regional footprints and model diversity, whist one vendor who has a bigger footprint has a limited number of models, whereas the vendor with no regional footprint has a significantly wider range of models for different market segments. Therefore one vendor has more tuned models for a limited number of market segments whilst the other has a large number of models for many more market segments and tuned to a global standard but no regional tailoring.

One can argue that the more market segment specific models are more suitable as businesses vastly differ in each market segment, and localization or regionalization could be covered by calibration features within the product.

So what is so different about these globally adopted rating models from different rating agencies, that makes each of them believe their model is better than the other, all have equally rated hundreds of bonds and companies that have since defaulted, no longer exist, with no capability for financial repayment and cause significant shockwaves and chaos in the financial markets lasting years and ultimately negatively affecting 100’s millions of people’s livelihoods.

For instance, some say S&P ratings seek to measure only the probability of default. Nothing else matters — not the time that the issuer is likely to remain in default, not the expected way in which the default will be resolved. Most importantly, S&P simply doesn’t care what the recovery value is — the amount of money that investors end up with after the bond issuer or borrower has defaulted.

Whilst others state Moody’s, by contrast, is interested not in default probability per se, but rather expected losses. Default probability is part of the total expected loss — but then you have to also take into account what’s likely to happen if and when a default occurs.

Moody’s view is a fair assumption, however these rating platforms indicate a ‘probability’ of default, and that is already hard enough to predict and it’s a future probability/gamble of something occurring which is random within itself, let alone predicting the expected loss and what happens after a default.

Therefore measuring and predicting the expected losses, is largely an academic exercise. Length of time to remain in default and how a default is resolved will add no value to credit decisions for non-sovereign corporates, SMEs or high net worth individuals in any region. When a default occurs in the future, it is very difficult to quantify a sovereign, corporate or individual’s willingness to pay or ability to pay, compounded by legal and statutory hurdles that may present themselves when default occurs.

Credit ratings are a lagging indicator, it is out of phase with the market, upgrades and downgrades tend to lag the market, rather than anticipate it, which is why and all lenders always find themselves behind the curve when defaults occur. Ratings agencies and credit rating tools are structured advice/warning beacons, but are not a guide to help people beat the market.

To be ahead in our game;

You need to constantly listen to the market, as the market is the best guide for credit worthiness of a business or a sector or the economy as a whole.
Improve your market intelligence.
Improve your sector knowledge beyond the basic framework of credit analysis.
Use tools effectively such as SmartOrigin, SmartGov and SmartRisk to help guide you to the right credit decisions with improved efficiency and accuracy.
Monitr and improve the accuracy of your quantitative and qualitative data to ensure management reporting is rich in quality.
Be vigilant by monitoring entities that have been downgraded as its much more likely to get another downgrade than it is an upgrade.
Use Business Intelligence data from the customers accounts to monitor their case movements, volatility, rate of in/out flow, in real time if possible.
Experience and knowledge is key and invaluable irrespective of what tools or methodologies are being used.
As your local market grows and changes, data build-out and mining will be a distinct advantage.
Increase the rate of deal flow and cherry pick deals based on their quality and rate of return, and have a wide distribution to hedge one segment against the other.
Standardise your rating and use one unified and universal rating method and structure.

References
The difference between S&P and Moody’s: Aug 2011: http://blogs.reuters.com/felix-salmon/2011/08/09/the-difference-between-sp-and-moodys/
The difference between Moody’s and S&P bank ratings: is discretion in the rating process causing a split? Sept 2012: http://www.rmi.nus.edu.sg/research/files/rmiworkingpp/WP1205.pdf