Portfolio Analysis & Understanding Delinquency Movements

The transition from a current, interest-earning account to a credit loss takes place through a series of different levels of delinquency. It is the analysis of movement between those levels over time that forms the core of the exercise.

The whole process falls apart if the measure of delinquency is not objective and consistent. Yet it is surprising how often that is the case among leading consumer banks.

Issues include, among others:

• Erratic treatment of partial or multiple payments
• Loan rescheduling accompanied by a reset of delinquency status and without separate monitoring
• Inconsistent treatment of fee payments
• Collector intervention in the ageing process

Analysis performed on inaccurate data is like a house built without foundations. It is likely to fall down, which is why a specified MIS begins with a review of data quality and relevance.

It is common to report the status of a portfolio broken down into levels of delinquency measured by contractual ageing — that is, the number of days delinquent is measured against the schedule established when the credit agreement was signed, and the amount reported is the balance at risk, net of any unearned income.

The numbers used are realistic for a mature portfolio. In the example, the write-off point is 180 days past due: everything from the 180–209 dpd bucket downwards has been written off.

Write-off is often mistakenly understood to mean that there will be no future revenue from the account. In fact, in most markets there is still significant value in an account that has been written off. The debt still stands and the customer remains under a legal obligation to settle it. The extent to which such debts are collected depends very much on either the local legal environment or the efforts of the collector. In countries such as Germany, where it is usual for banks to apply to the courts for a portion of the customer's wages to be assigned directly to the bank, the rate of recovery can be very high. Where this legal support is not available, the proportion collected depends on the skill of the collections department and usually varies between 0% and 33%.

In most countries there is an active market for the sale of written-off debt, with prices varying up to a maximum of around 8% of the face value of the debt. The logic for that maximum is that if the debt is recoverable at 33%, the cost of recovery will typically be less than 25%.

In our example the delinquency beyond write-off may not be important to the reported results of the business, but for the credit risk manager understanding its evolution is critical.

Of the balances which are not written off, it is normal to consider the percentage of balances greater than 30 dpd and the percentage greater than 90 dpd. In our example the ratios are:

• 30+ dpd delinquency — 2.2%
• 90+ dpd delinquency — 1.0%

The percentage of the receivable written off in a given month — the gross credit write-off — is 0.21%. If this were repeated in every month of the year, the annual gross write-off would be 12 × 0.21%, or 2.52%.

Although these numbers are commonly used, they shed very little light on any possible cause of delinquency, or on the impact of changes in the portfolio.

If the delinquency figures for two consecutive months are written side by side, a direct comparison can be made. In the table below it can be seen that not only are the receivables growing, but so are the delinquent balances at each level of delinquency.

Unfortunately the table says nothing about the movement of accounts between the two months. Accounts which are, say, 1–29 dpd in Feb-21 may have been in any non-written-off bucket in January. The maximum an account can age between two months is 30 days, but it can pay off as much of the overdue balance as it is able and become less delinquent, all the way back to current or anywhere in between.

Experience tells us that the evolution of delinquency for accounts beyond 60 dpd is likely to be determined primarily by most customers making no payment and simply ageing into the next bucket.

It suits our purpose to make the simplifying assumption that all accounts arriving in a given delinquency bucket come from the previous, one-step-lower stage of delinquency. This assumed movement from month to month is called the net flow, or roll, of delinquent balances.

On that basis, the flow from the 30–59 dpd bucket in January to the 60–89 dpd bucket in February is 11,358 → 5,111, a flow of 45%. With this simplifying assumption in place it becomes possible to analyse further what is happening to risk within the portfolio.

The first table below is a delinquency matrix showing delinquent balances over a series of 12 months. The second is a net flow matrix showing the transition into a state of delinquency in a given month from a state of lower delinquency in the previous month, under the assumption that accounts either become one step more delinquent each month or cure entirely — a simplification, but an adequate one, especially for the later buckets.

The net flow tells quite a detailed story about how the portfolio is being managed. The evolution of an account through the stages of delinquency gives the monthly gross loss, before recoveries. The simplest way of stating this is that the losses arriving at 180 dpd in August 2021 were current in January of that year. The percentage written off from that month is therefore 3,785 / 1,234,567, or 0.306% of the current balance. If this happens in each of the 12 months of the year, the annualised loss rate is 3.68% of the current balance.

Another way of calculating the same number is to take the product of the monthly flows:

5% × 25% × 45% × 75% × 85% × 90% × 95% = 0.306%

The advantage of this way of looking at things is that it breaks the loss down into the different stages of the evolution, so that deterioration in any part of the process can be quickly identified and remedial action taken.

Suppose losses deteriorate by 20%, from 0.306% per month to 0.366% per month. The reason may not be obvious immediately, but if the flow rates have changed to those below:

5% × 25% × 54% × 75% × 85% × 90% × 95% = 0.366%

it can be seen that the flow from the 30 dpd bucket to the 60 dpd bucket has increased from 45% to 54%, which accounts for the whole 20% increase in gross losses. The problem lies in a specific part of the collections area. It could be due to staff shortages or some other change in collections strategy, but at least the problem has been located and can be treated.

It has become common practice, for good reasons, to break the transition from current good customer to recognised final loss into a number of stages. This is partially encapsulated in Basel II, where a division is made between the account prior to default — usually 90 dpd — and post default. That enables the Basel II formulation of expected loss:

EL = PD × LGD × EAD

Many lenders would apply a more detailed breakdown, dividing the loss given default transition into two separate parts: that prior to write-off and that post write-off. This is because experience tells us that predicting write-off from delinquent status works quite well using a net flow model, but beyond that it is better to perform vintage analysis to forecast future losses.

The other major advantage of this kind of analysis is that it can be used to understand the true state of the portfolio without being misled by the effects of growth.

In the example above, the accountant's view of the percentage of losses would simply be the balances written off divided by the sum of the previously non-written-off balances. That is 0.203% of total balance, or 0.218% of current balance — almost a third lower than the lagged value.

This is because the receivable used as the denominator refers to the month of the write-off. Since the portfolio has been growing since the time when the newly written-off account was current, the denominator is higher and the ratio of losses is lower. If the situation is reversed, the denominator shrinks and the loss ratio becomes higher.

A further difference between the calculations relates not to the lagging factor but to the denominators used. The lagged flow gives a loss rate as a percentage of the lagged current balance, while the accountant's loss rate is this month's written-off balance as a percentage of this month's not-previously-written-off balances. Both are simplifications: the lagged calculation assumes receivables only from the current bucket, and the standard approach uses total receivables. In reality, losses should be measured as a percentage of performing, interest-earning assets.

The lagged calculation could be seen as more prudent, as it looks only at the major portion of interest-earning balances and removes the effects of growth. The accountant's simplified view of the world has an account as either performing or written off, and confuses numerators and denominators.

A more accurate calculation would apply a risk weighting or impairment across all buckets, since delinquent balances, although still considered assets, have a much diminished potential for earning interest.

The challenging part of risk analysis is not the preparation of the data — although inaccurate data makes any analysis impossible — it is the interpretation of that data, which is where a portfolio performance review usually starts.

The whole management process is geared to producing a profitable portfolio, and the credit process must be designed to be consistent with this. That means understanding what the acceptable level of losses is, and knowing the revenues and costs associated with a given product.

Once that is established, the whole lending process — from underwriting through limit setting, maintenance and collections — must function so as to achieve the acceptable level of risk.