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Scoring system is an effective tool to forecast and minimize credit risks.

Banks started using scoring systems since the mid-1950s, when one of the first companies to develop scoring systems - Fair Isaac Corp./ San Francisco began its activity in 1956.

In 1941 David Duran first applied this technique to classification of loans as "bad" and "good." By that time it coincided with the Second World War, when almost all credit analysts were called to the front and banks faced the urgent need to replace these professionals. Banks made their analysts (before they leave) to write a set of rules that should guide non-specialists on the decision to grant a loan. This served a prototype for future expert systems.

The scoring system today is an algorithm that allows a bank to evaluate creditworthiness of a potential borrower based on collected data.

With growing increase in retail lending volume traditional methods of assessing individuals in expert way lose their effectiveness. The increase in supply of new banking services and credit products require partial or full automation of the client's solvency assessment and underwriting.

Scoring is one of the decision making components of a credit assessment. The objective of scoring system for a bank is to cut off the unwanted borrowers. Such unwillingness to lend is normally formed on the basis of historical data on the parameters and results of lending to the existing borrowers. Scoring is most actively used for express loans.

In its simplest form scoring model is a table of certain characteristics of a client: gender, age, marital status, income, line of business and other. Depending on the value of such characteristics the system assigns the client a certain amount of points. The higher is the total, the greater is the probability that the loan will be repaid on time. Then this total is compared to the "threshold value" which is determined according to the bank's risk appetite. Those customers whose total exceeds the "threshold value" are granted the loan. Those who have it lower than the “threshold” are not.

Banks usually have several different scoring tables: for different products, regions and customer segments.

To evaluate borrower’s payment capacity credit scoring evaluation model uses three groups of characteristics.

1. Personal data – this is, first of all, the age, gender, number of children and marital status.

2. Financial condition of the borrower. This is the type of business, years in business, income, expenses and debt and the ratio of income to expenses.

3. Information that will help to confirm creditworthiness of a person - real estate in possession expressed in cars or property; additional sources of income, such as apartments for rent, income from playing at the stock exchange, securities etc. Existence of a guarantor or guarantors will also be a plus.

Documents submitted by the borrower and information received according to his words - all available information serves as the data on the potential borrower.

Credit scoring should not be considered as a procedure for assessing the borrower before loan issuance only. Various types of credit scoring are used to optimize process of working with the borrower throughout the entire loan cycle.

Following are the types of credit scoring:

• application-scoring – assessment of a borrower’s payment capacity (scoring based on primarily biographical data),
• behavioural-scoring – estimation of probability of loan repayment (behavioural analysis),
• collection-scoring – assessment of possibility for the client to repay the loan in full or in part on violation of the repayment terms (calculation of portfolio risks),
• fraud-scoring - methodology and processes to detect and prevent fraudulent activity of potential and existing borrowers.

Scoring system always implies performing technical processing and technical analysis.

The set of characteristics used to describe a borrower and their relative weight in credit risk assessment is not the same in different countries, as different are economic conditions and national mentality. Therefore one should not automatically transfer the same model from one country to another.

We would like to note some advantages and disadvantages of scoring assessment:

Advantages of scoring

- optimization of costs related to loan application review by automating the process of decision making and underwriting;

- reducing the time required for an application review, increasing the number of applications and speed of their processing

- lack of an individual expert’s subjective opinion in making the decision on lending

- determination of profitability level and loan portfolio risk etc.

Disadvantages of scoring

- it is not the borrower who is assessed, but his answers, so any well-trained loan applicant can know what to answer so the system could make a favourable decision to grant a loan for him;

- credit rating is based on the data about the borrowers who received a loan. One can only guess about the behaviour of borrowers whose applications were rejected;

- scoring system requires constant revision and updating in order to give information as accurate as possible.

Due to the increasing capabilities of automated systems as well as changing market conditions, the loan process is being constantly changed and modified, new technologies are introduced resulting in assessment of borrowers to be performed more thoroughly and impartially. However, this does not mean that tightening of scoring procedures leads to complications with obtaining a credit.

In the current economic environment banks do not want to lose even a single customer and therefore they start to develop more flexible instruments of credit management, changing interest rates and requiring additional loan security. Thus, in the cost of a consumer credit (and it reaches 50-100% per annum), the risk margin is 10-12%, which means that with the improvement of risk assessment methodologies loans will become cheaper. 

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