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The credit exposure policy is the follow-up procedure to the credit score card design and its execution. They tell us how we interprete the client rating and what an appropriate usable approach would be that corresponds to that rating. It is the winner which, when implemented: 1 ) enhances the client franchise, 2 ) decreases the credit exposure and 3 ) maximizes the return.
Prior to starting the strategic review and performing many what-if scenarios iterations it is important to clearly define the target of your company and understanding the key businesses that drive the review. This is the most commonly used and simple type of credit quality policy and it is designed around a one-dimensional limit for an acceptance or rejection of a credit rating.
However, the cut-off stage, i.e. the credit rating, can be a rigid cut-off with a set value or have configurable settings with various treatment options such as acceptance without condition, acceptance condition or rejection. Often creditors use a divisional approach to identifying different cut-off thresholds between client business units.
Thus, for example, strategic tiering can be built on the same failure ratio across client sectors and benefit from higher acceptance ratios for better sectors or maintain the same acceptance ratio across all sectors, resulting in lower failure ratios across better sectors. The thresholds are dependent on the general commercial goals.
If, for example, the target is set to maintain an 80% acceptability ratio, review may set the cut-off value at 320, but if the target is set to a 6% failure ratio, the policy could be more stringent and the cut-off threshold rises to 360.
Assuming the policy is purely P/L valuation, the cutoff score would have to be set to 440 as shown in the example in Fig. 1. Chart 1 shows how various KPIs (Key Key performance Indicators) such as adoption rates, failure rates or win amounts affect the scorecard's cut-off-level.
Credit loss divisions, for example, target the reduction of defaults and the reduction of debts, while a marketer can demand an increase in cut-off levels to increase its client bases. However, a possible trade-off could be to create a new score card that will increase the number of acceptances at the same poor rating or lead to a reduction in the poor rating at the same rating.
The goal of reducing the poor installment is better suited in business drives. Complex credit exposure policies have more than one cut-off level or a combination of two or more credit ratings, e.g. in-house proposal evaluation and office evaluation. Often there are other predictable frameworks in the strategy such as loyalty, return rates or value.
Behavioral values, in combination with policies and regulations, as well as key performance indicators, can derive the greatest benefit from predictive analyses and compliance policies. You can also use score for risk-based price setting to customize your products, such as interest rate, credit line, redemption term, etc. Riskbased price setting assumes many shapes, from one-dimensional repeated cut-off treatment on the basis of P&L analyses (e.g. acceptance with lower limit) to a grid structure that combines two aspects, e.g. behavioral score and residual to help determine credit lines or interest rate levels.
The combination of two predictable paradigms - score and response rates - can, for example, allow marketers to concentrate on low-risk clients with a high likelihood of responding to an offering. For example, the policy may refuse to accept high-risk clients who would have been loyally or profitably high.
Whilst a CLV can help in identifying value propositions, creditors may be hesitant to use CLV because it can be highly challenging and complicated to compute. A thorough insights assessment in such a situation can help in identifying precious business areas and adjusting the strategic direction accordingly.