Jun 2021 | General | Credit Risk Management
By Posted by Bartłomiej Staszewski
Bartłomiej Staszewski
Bartlomiej Staszewski
Senior Global Consulatnt

Risk costs

In 2021 risk costs and the value of credit write-offs in the banking sector, by comparison, will be twice, three times as high as in 2019.*

Despite implementing aid programmes for the banking sector, what is forecasted is an increase in risk costs of between twice and three times: there will be a smaller increase in the case of banks which are exposed to less vulnerable sectors, less cyclical ones, on the other hand, a higher increase will occur in the banks which are exposed to more cyclical sectors or more vulnerable profiles of clients, in other words, such banks that followed a more aggressive credit policy.

So far, based on the partial results published for 2020**, most of the banking institutions in Poland and in Europe have created portfolios reserves for the future probable risk of credit portfolio deterioration connected with lockdown economic consequences.

At the turn of the fourth quarter of this year and the first quarter of 2021 banks will already create reserves for particular exposures on the basis of individual credit engagements also for the ones, whose moratoria and aid programmes come to an end.

At that time what will become visible is the effect of loss emergence on particular exposures.

There are credit repayment deferral programmes offered by banks on their own initiative as well as anti-crisis shields which introduced payment holidays based on the act of parliament  for individual customers who lost their jobs as a result of the lockdown, there are also various anti-crisis shields for entrepreneurs – to a large extent such anti-crisis deferral and shield measures so far have not manifested themselves in the form of payment losses or even delays.

They will be visible only when the subsidy programmes or credit repayment holidays come to an end and when the economy returns to a normal rhythm i.e., some time at the turn of the fourth quarter of this year and the first quarter of the next one unless new aid schemes appear as and answer to current lockdown.

The key question that arises is the following: how to approach the de facto massive and non-standard process of evaluation and categorization of those exposures.

The economic situation – consequences of restrictions introduced in the pandemic

The lockdown has hit all the sectors but the force of impact and expected revival path depend strictly on the particular sector.

Let us look into some examples: after summer holidays it was clear that in spite of activating events, hotel and restaurant industries, customers do not make use of hotel and restaurant services as willingly as before Covid-19. If we look at the event industry and the temporary closing of shopping malls, we can observe that customers are hit by economic consequences of the lockdown. However, some of the companies show resistance to the economic effects of the pandemic: we can notice a growth in the sectors that have upheld high investment activities, which particularly concerns the sectors manufacturing and selling necessity goods, among others food and pharmaceutical industries.

More than that, there are some sectors which profit from the pandemic, particularly IT and ecommerce, which are great winners in the face of the pandemic. More customers take advantage of online vehicles: what is observable is the switch from direct shopping mall purchases to the Internet ones in the case of buying the same kind of products. In addition, courier services indirectly make use of the development of the Internet commerce. Also, some of the restaurants try to take the opportunity and switch services to the Internet by offering such deliveries.

We must remember that present situation with new strike of epidemic may lead to a massive lockdown again. Economical consequences of such event are very hard to forecast at this stage.

The upcoming crisis which is of credit and sector character is the one for which banks have been preparing for the last 12 years; its specificity consists in the fact that with different force the crisis will impact concrete areas of the economic life.

Consequently, the key answer is to the question: which sectors and customers will suffer from predicament and if and how it is possible to help them?

The financial sector response

It seems that the present situation has created the need for changes in the areas related to risk modelling, particularly in banks, insurance and telco. These changes follow from the need of more extensive and dynamic identification of signals and events concerning financial institutions’ clients as well as correct interpretation of these events. What can have greater and greater significance is the making use of both alternative and external data from the point of view of identifying risk factors and warning signals. What will be essential is the skill of connecting such data with the existing ecosystem of analytical institutions.

It will also be decisive to acquire these data much more frequently than so far in order to detect early enough problems connected with clients’ liquidity. If we realise the fact that the lockdown hit us only 6 months ago, we will understand how it becomes problematic to look at the client exclusively in the anticyclical terms.

In this context, what may turn out to be crucial is using modern modelling techniques, for example machine learning rarely so far applied in banking industry, (though with great results in telco) as well as the application of flexible and adequately powerful systems, particularly decision engines in which such models will be implemented.

An SME Experian solution example:

Usually, teams monitoring a client’s situation traditionally look into data of low frequency appearing with a considerable delay e.g., financial reports or some data from credit information bureaux. Instead, it is worthwhile to try following activities in real time. Analysing clients’ transaction data and real financial flows between entities based on internal banking data and publicly available ones ( e.g., information from credit bureaux and such instruments as WebScore offered by Experian), we have a possibility of pinpointing precisely when and in what areas, after making use of aid programmes, clients begin to come back to economic activities and in which areas they fail to do so. Then and only then, fully aware, and on the basis of precise data and reliable analytical models provided by trusted advisors, we will be able to manage one factor after another: portfolio, risk, strategy and crisis.

Otherwise the crisis will manage us. And the abyss may gaze into us.

One should take into account that what will be of importance is the models which concentrate on forward looking components – both in tests of extreme conditions, allowing for simulation of risk levels resulting from scenarios related to the changing environment and also such factors whose “hic et nunc” we cannot forecast. These are the variables which ought to be relevantly taken account of in risk models. The obvious consequence of Covid-19 is a decrease in direct contact among people and an increase in the role of remote channels. That is paramount in banking, insurance and in the telco sectors. What follows is the need to build dedicated processes and risk models based on clients’ transactions, analyses of behaviour on the Internet and advanced models analysing data available in public space.

So what can happen? Absolutely everything. Maybe nothing? Or perhaps from a mild slowdown to massive increases in outstanding loans, overloads and inefficiencies in debt collection processes, resulting in customers migrating between stages and rising provisioning costs; shortages of people to service overdue liabilities in banks. And pressure, social and regulatory, to continue to help customers in the retail sector who have lost their jobs, lost their income and are looking for help.

There will be customers who want to maintain their standard of living at all costs and who are looking for a real way out of a difficult situation. There will be honest, hard-working people who have had bad luck and there will be scammers taking advantage of every situation.

And those who will want to make money from it all.

What to do? How to remain ethical, pragmatic and loyal to shareholders?

This question will have to be answered by every risk manager in the market, every debt collection manager. Everyone in the sector.

There is no simple answer to that question. But there are tools. Methodology.
Proven risk assessment in stressful situations. There is an advanced analytics that really is more than just a nice and catchy power point slide title.

Experian’s proposal is a comprehensive solution to help optimize the cost, risk and value of the entire debt collection cycle.

As the costs of recovery increase with the migration of the customer through the delinquency buckets, the first thing to do is to focus on getting the maximum value from the prevention processes and how much it is possible to help the customer before hits the collections.

In the next stage, the analyst helps to understand the client’s actual current ability to repay as well as the circumstances that exist to model the right actions towards the clinic. In the next stages we propose to focus on efficiency, productivity and effectiveness. We are able to transfer all this to the virtual world and respond to our clients’ needs in a pandemic reality.

What is essential is the ability to effectively implement a truly multi-channel concept of communication with the client and to affectively observe dynamically changing legal statutory rights of consumers in collections process is essential. Apart from establishing the debtor’s actual situation on the objective ground, it becomes crucial to apply an appropriate strategy for each phase of the debt cycle.

What is also obvious is the fact that the client who grants broad consent to analysing his data in the GDPR regime will get a better access and more tailored offer than the one that did not grant such a consent.

Experian possesses knowledge and experience indispensable for providing complex solutions in question. Our solutions support the process of portfolio management as well as debt collections and contact with the relevant parties through combined segmentation, communication and decision-making strategies using predictive analytics, models and assessments to prioritize actions.

We have analytical resources, credit information bureaux’ data and the professional team of people with experience in risk management, analytics, modeling, strategy building and other areas of the financial sector.

We are waiting for You.

Happy to help.

* by Marek Lusztyn CEO and CRO of Bank Pekao SA in 2017-2020
** based on Q1 and Q2 results of: Bank Peako SA, PKO BP, ING Poland, Santander Poland, source webpages of the banks