What is the loan mobilization scandal


Risks in the lending business

Lending business is shaped by a wide variety of influencing factors: A competitive margin decline and increasing regulatory capital adequacy burden the earnings situation of banks. In addition, volatile markets increase the risks as collateral can fluctuate in value. This applies in particular to losses in value in real estate markets, as these are often ordered as the main security.

Through theMaturity transformation the interest result of the banks can be increased further by the bank refinancing itself at more favorable interest rates in the short term and taking the long-term interest rate from the customers. This increase in the interest margin, however, harbors Interest rate risksbecause the short-term refinancing rate can rise at any time. In this case, the interest margin shrinks again.

In December 2005, the Federal Financial Supervisory Authority (BaFin) published the Minimum requirements for risk management (MaRisk). These administrative instructions are intended to strengthen the stability of the credit institutions in terms of risk.

Types of Credit Risks

Counterparty default risk

The risk of a debtor servicing his debt Not or. not as agreed Fulfills. For the bank, this means a partial or total loss of the claim, provided that no collateral in the corresponding amount can be realized. There is a balance sheet individual value adjustment (= write-off of the receivable).

According to MaRisk must therefore be specially adapted for each borrowerCredit limit be granted.(MaRisk, BTR 1)

Credit risk of deterioration

This is to be distinguished from the risk of counterparty default Credit risk of deterioration, which describes the decrease in value of the credit claim (if applicable, general value adjustment) before default. The borrower may still be able to pay interest and repayment, but the bank sees a negative forecast for the credit history due to a deterioration in creditworthiness.

Credit risk management

The responsibility for the proper business organization and its further development lies with the management and cannot be delegated(MaRisk, AT 3 and 4).MaRisk requires credit institutions to set up an internal process to ensure their risk-bearing capacity(AT 4).

These risk management and controlling processes are an important basis in banks' credit risk management (MaRisk, AT 4.3.2). The tasks include:

  1. Risk identification
  2. Risk measurement (quantitatively)
  3. Risk management (Hedging instruments)
  4. Risk controlling (Monitoring & communication)

The exact design of the individual methods in credit risk management is not required by law. Therefore, different approaches can be used in the process steps.

Risk coverage potential

In order to comply with the risk requirements of MaRisk, the risks that (can) arise in the business activities of a credit institution are continuously numerically calculated by risk management. Across the different business areas, a nominal value arises that describes the actual current risk of business operations.

This contrasts with a previous planning by the management for the relevant period: Business risks are calculated in advance from the history and, based on this, risk coverage potential is distributed to the individual business areas. These are also expressed as nominal amounts of money. Now the actual risks in the books must not exceed this upper limit (risk-bearing capacity).

The risk coverage potential is called that economic capital understood by the banks, as this backs the risks in general business operations with capital.

If a risk coverage potential in a business area is exhausted, further business in this area must be avoided. In practice, management can do this, for example, by increasing the price of the product in question.

Assessment of creditworthiness

Since Basel II, three important measures for risk assessment have been:

  • the probability of failure (Probability of Default, PD)
  • the volume of receivables in the event of default (Exposure at default, EaD)
  • the loss rate in the event of failure (Loss Given Default, LGD)

The expected loss (Expected loss, EL) results from:

EL = EaD * LGD * PD

Valuable collateral and cash flows from insolvency proceedings must be taken into account in the default volumes, as these reduce the expected loss.
For the Total loan portfolioFor a bank, the expected losses of the borrowers are added up and these form the overall risk in the banks' lending business as a nominal amount of money (in euros).

Classification models

The credit-worthiness a debtor can be determined using different methods. The aim of these methods is to bring the borrower into an associated with the help of evaluation methods Risk class classify. Based on this risk class, credit decisions are made and the conditions for a loan are calculated.

In the past, only a year-end analysis with an associated credit report was carried out. However, since this method is characterized by a high degree of subjectivity, quantitative or mathematical-statistical processes are increasingly being carried out in banks using computer programs.

verbal-qualitative proceduresTraditional year-end analysis with credit log
quantitative methodScoring procedure (point evaluation)
mathematical-statistical proceduresDiscriminant analysis

2) Scoring process

The scoring process or the point evaluation process is a quantitative method for determining creditworthiness and is therefore used to assess credit risks. It is easy to implement and helps quantify individual risks.

  1. Definition of certain characteristics / criteria
    (e.g. earnings position, liquidity, sustainability, ...)
  2. Definition of a point scale / possible characteristics
    (e.g. from 1 = bad to 10 = excellent)
  3. Weighting of the characteristics
    (e.g. feature A = 20%, B = 15%, C = ...)
  4. Awarding of points for the individual categories
  5. Multiplication of the points with the weighting factor
  6. Summary of the weighted points in the conclusion

Using these results, risk classes can be formed from point intervals. This procedure has the advantage of being systematic and transparent makes a credit decision. It is characterized by higher objectivity and Traceability out. The goal is that two different employees would come to the same conclusion.

Systematic use of this method can be a bank-wide way of identifying and measuring risks.

Despite all efforts for objectivity, the characteristics / criteria are ultimately predefined by a subjective opinion. This can lead to distortions (pseudo objectivities) again.

3) Discriminant Analysis

Discriminant analysis is a more advanced model for quantifying credit risks. For this purpose, historical data from credit agreements are viewed and evaluated. This analysis takes into account various factors influencing the credit history. In this way, factors are systematically highlighted that occurred in the case of non-performing loans.

The univariate discriminant analysis looks at a single solution as the simplest solution Credit rating factor(KBF). For example, the characteristic "owning your own property" can have a positive effect on the credit history.
Based on this factor, risk-adequate conditions can be determined: A borrower without real estate has a higher risk of default and must therefore accept a higher risk premium in the interest rate.
As a model, these failure frequencies are viewed as normally distributed depending on the CBF. To determine a separation point (Cut-off point), we consider a sufficient expression of the CBF, on the one hand, with few loans defaulting (α error) and on the other hand, few loans are rejected, the course of which would actually have been positive (β error).

Well-suited credit rating factors lead to a small spread around the center of the distribution and thus to only a small overlap of the functions.

This procedure is characterized by a high degree of objectivity because it only refers to data related to the past. However, taking into account a single CBF does not process enough information from the borrower to draw accurate conclusions about the development of the loan.

The model is therefore further specified below, including additional factors, in order to estimate the credit risks more precisely. A multivariate discriminant analysiscan be based on the credit rating factors of a univariate analysis with differently selective variables and link these with one another. This form of the model is convincing in the lending business with its systematic and objective assessmentwith very high forecast accuracy.

Expressed formally, the factors Xi with weighting coefficientsβi determine a value for risk assessment:

Possible credit evaluation factors that can be included in the model are financial ratios from the annual financial statement analysis. A credit decision is now made by comparing D. determined with the previously defined cut-off value.

Despite long research in this area, there is still no uniform formula, as each credit institute defines its own focus of analysis. To make matters worse, the introduction of an in-house multivariate model initially causes considerable effort, since historical data has to be processed.
In addition, several discriminant analyzes may have to be carried out for different target groups and there has to be an ongoing check to ensure that the model remains valid over time.

Control credit risks

After risks from the lending business have been identified and measured at an early stage, it is important to manage them correctly. It's going on continuously Process improvements worked so that the risk management can act even more precisely and individually.

In order to prevent grievances and damage that arises from credit risks, banks have various options for managing the risks:

  1. First of all, you can Loan collateralagreed, which can be used in the event of a failure. It finds one Risk transfer / compensation (with insurance if necessary).
  2. In addition, regulateCovenants certain behaviors of the borrower (e.g. a prescribed minimum equity ratio) and serve the Risk reduction.
  3. Pricing mechanisms enable aRisk coverage through risk-adjusted pricing and finance possible failures.
  4. ACredit rationing through a legal or voluntary limitation of lending to individual borrowers reduces the default risk of an individual (Risk avoidance / limitation).
  5. It can be a Risk sharingby Syndicated Loans can be achieved, which means that the risk of default is spread across several banks.
  6. Inadequate claims are identified in the Risk provisionby Value adjustments amortized early.

In the following we will primarily consider the Pricing mechanisms of the credit institutions, as this is the most important control option for credit risks. To arisk-adjusted pricing When calculating the loan, the necessary risk costs are included in the loan price.

Profit margin Profit Credit price
↕   ↕   ↕   ↕   ↕   ↕   ↕   ↕
Processing costsReserve price
Risk costs
Refinancing costs
Cost of equity

The level of risk costs depends on the customer's individual PD rating (probability of default). The bank protects itself against loan defaults by adding a risk premium to all loans. In total, this surcharge should be sufficient so that successfully repaid loans can then intercept failed loans.

Standard risk costs

After segmenting individual customer groups or types of business, the standard risk costs can be determined for these segments. They are expressed by a risk premium and result from the probability of default (PD) in the respective segment and the risk-free, term-congruent interest rate (rf):

With this surcharge on the loan price, the bank can failed interest and repayment payments compensate.

Excursus: Risk costs through option pricing models

On the basis of options, theories exist as to how risk costs can be determined alternatively for a loan: The borrower receives the loan amount from the bank to finance his company (Strike price) paid out. At the end of the loan term, the borrower decides (corresponds to the Buyer of the option), whether he has the loan at the bank (corresponds to the Writer) actually erases.

Otherwise he leaves his assets to the creditors. This is the case when the entrepreneur has done so badly with the money that he cannot repay the loan in full.

The position of the entrepreneur is thus a Long putbecause in case of doubt he can leave the company to the bank.

The bank charges a for this risk Option premium in the amount of the risk incurred. For this, however, the value of the company (corresponds to Underlying) must be known very precisely.

Management of overall bank risks in the lending business

The interest-bearing business (lending business) plays the most important role for banks in generating income. Therefore, the risks that can arise in this business area must be controlled in a targeted manner at the superordinate bank level.

Possible control instruments will be discussed in the further course. Including the Credit rationing & credit crunch, theDiversification, the Credit Value-at-Risk as Credit portfolio models.

Credit rationing and credit crunch

The possibility of avoiding risks in lending business can be achieved by generally reducing the loan volume granted. There are basically two forms:

The Credit crunch describes a fundamental shifting of the supply curve to the left / up, which creates a new equilibrium (K1 ; i2 red). Due to a general shortage of credit, customers will be willing to pay a higher interest rate in order to get a loan. At the same time, the volume of credit granted by the banks is decreasing.

The Credit rationing on the other hand, is a steering calculation of the individual bank in order to take fewer risks into the books. The bank will only add loans with the best creditworthiness to the portfolio and reject loan inquiries more quickly if the rating is poor. This results in a falling interest rate, since borrowers with a good credit rating only pay a lower interest rate. It thus results in point (K1 ; i2 blue) no new equilibrium.


Based on Harry Makrowitz's portfolio theory, diversification effects take place in the lending business because the bank owns a loan portfolio from a wide variety of borrowers. If one fails, the remaining credits absorb the failure.

You can find the detailed model of diversification in portfolio management!

Credit Value-at-Risk

In contrast to stocks, the expected return on a loan portfolio cannot be viewed as normally distributed. By a asymmetrical risk distribution the negative deviation from the expected value cannot be determined using the standard deviation.

There is thus a modification of the model to Credit Value-at-Risk (cVaR) instead. This estimates the greatest loss that we will accept at a given confidence level. With a confidence level of 95%, the probability of even higher losses above the cVaR is therefore 5%. The highest possible confidence level is chosen in order to capture the risks generously.

The calculation is based on an empirically determined distribution function:

The expected loss (Expected loss) from the lending business is managed at an early stage by means of impairments using the balance sheet risk provisioning. These losses are due to the risk-adjusted pricing again borne by the customers.

Theunexpected loss is the negative deviation from the expected loss. Depending on the chosen confidence level, this then resultsCredit Value-at-Riskthat limits these unexpected losses. This part is going with economic equity (=Risk coverage potential) underlaid.

Below a given confidence level, there remains a residual risk that a maximum loss in the loan portfolio. So almost all of a bank's loans would default overnight at the same time.Since this event is very unlikely, it is neglected in risk management.

Credit portfolio models

To Determination of the loss distribution loan portfolio models are used. For this purpose, the existing credit data of a bank is processed and risk factors that have an influence on the credit history are highlighted. The effect of these factors on the result is estimated and a confidence level is established for the model.

Credit portfolio models can basically be divided into two categories:

  1. Failure rate models
  2. Goodwill models

When using Failure rate models possible loss sizes (LGD) are weighted with probabilities (PD). The curve described results from this. This is a well-known example CreditRisk + CreditSuisse model that takes into account a diversification effect resulting from different correlations between the branches / sectors.

The Goodwill models on the other hand, calculate a market value of the loan portfolio based on forecast deterioration in creditworthiness. These are expressed in impairments in the loan portfolio. The CreditMetrics Model by J.P. Morgan takes this approach and calculates the present values ​​of the loans through forward rates.

Bad loans

A loan exposure is under special observation if there are indications of an impending default on the receivable. These exposures are monitored more frequently than other loans. At this stage, the deposited collateral should be checked again for its intrinsic value. As a rule, a customer meeting now takes place, which provides information about the reasons for the impending failure.

The goal of intensive care is orderly return the debt burden. However, if the performance disruptions continue to develop negatively, the Loan restructuring Avoid a total failure through negotiations and rescheduling measures. This requires an acceptable and feasible rescue plan for the debtor.

If negotiations have no prospect of success, the loan commitment is terminated and due. This is the requirement for an orderly completion of credit. From this point in time, if there is no immediate repayment, the bank is entitled to the Realize collateral and Enforcement title acquire against the customer.