Data mining is a critical step in knowledge discovery involving theories, methodologies and tools for revealing patterns in data. It is important to understand the rationale behind the methods so that tools and methods have appropriate fit with the data and the objective of pattern recognition. There may be several options for tools available for a data set.
When a bank receives a loan application, based on the applicant’s profile the bank has to make a decision regarding whether to go ahead with the loan approval or not. Two types of risks are associated with the bank’s decision –
If the applicant is a good credit risk, i.e. is likely to repay the loan, then not approving the loan to the person results in a loss of business to the bank
If the applicant is a bad credit risk, i.e. is not likely to repay the loan, then approving the loan to the person results in a financial loss to the bank
Objective of Analysis:
Minimization of risk and maximization of profit on behalf of the bank.
To minimize loss from the bank’s perspective, the bank needs a decision rule regarding who to give approval of the loan and who not to. An applicant’s demographic and socio-economic profiles are considered by loan managers before a decision is taken regarding his/her loan application.
The German Credit Data contains data on 20 variables and the classification whether an applicant is considered a Good or a Bad credit risk for 1000 loan applicants. Here is a link to the German Credit data (right-click and "save as" ). A predictive model developed on this data is expected to provide a bank manager guidance for making a decision whether to approve a loan to a prospective applicant based on his/her profiles.
The German Credit Data contains data on 20 variables and the classification whether an applicant is considered a Good or a Bad credit risk for 1000 loan applicants.
Germany's leading credit rating bureau, SCHUFA, has immense power over people's lives. A low SCHUFA score means landlords will refuse to rent you an apartment, banks will reject your credit card application and network providers will say 'computer says no' to a new Internet contract.
How does it work? Schufa operates as a credit scoring system, assigning a score to each citizen based on their financial history. This score reflects a person's likelihood of meeting financial obligations, such as paying loans and bills.
Generally, a SCHUFA score above 90 is considered to be a good one. However, you should know that a SCHUFA score of 95 % and below already indicates a certain level of risk to financial institutions, companies offering financing terms for products and of course, most importantly landlords.
Once a year you can apply for and receive a free Schufa report. The main purpose of this annual report is for you to check the accuracy of all the data collected about you. Here is a step by step guide to ordering a free Schufa report: Go to the page meineSCHUFA.de .
Credit Data is any well defined dataset that has direct applications in the assessment of Credit Risk of an individual or an organization, or more generally allows the application of data driven Credit Portfolio Management policies.
Schufa Holding AG is a credit investigation company which collects information from consumers and companies involved in the lending process. Schufa Holding will review your past payment history, and forecasts your payment behaviour in the future in the form of figures ("Schufa score").
Generally, VISA and Mastercard have the highest acceptance rate at stores and make up around 80% to 90% of all credit cards issued in Germany. American Express and JCB networks will be a bit more difficult, but are accepted at large restaurants and hotels.
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Data mining is a critical step in knowledge discovery involving theories, methodologies and tools for revealing patterns in data. It is important to understand the rationale behind the methods so that tools and methods have appropriate fit with the data and the objective of pattern recognition. There may be several options for tools available for a data set.