Developing A Credit Scoring Model - 2203 Words

INTRODUCTION The dataset used for the project is the German credit dataset that consists of customers’ financial and credit information and the resulting classification of customers as â€Å"good† or â€Å"bad† credit risks. This is a well-known publicly available dataset containing observations on 20 variables of 1000 past applicants of which 700 are classified as â€Å"good† credit risk and 300 are classified as â€Å"bad† credit risk. This report lists the detailed steps involved in developing a credit scoring model that can be used to determine if a new applicant is a good credit risk or a bad one, based on their predictor variables. Tools Used: SAS Enterprise Miner 4.3 IBM SPSS Statistics 22 Modeling Techniques Used: Decision Tree DATA PREPARATION AND EXPLORATION The modeling process incorporated in this project is based on the Enterprise Miner SEMMA methodology which stands for Sampling, Exploring, Modifying, Modeling, and Assessing data. The goal of this project is to develop a credit score model that can be used as a prediction model for any prospective customers. Hence, the next step was to prepare the collected data. The German credit score dataset was provided in a comma separated values (.csv) format. When the dataset was opened through MS Excel, the values of the variables were displayed as numbers without any logical understanding of what they meant. A screen shot of the data viewed through Excel is provided in Figure 1. The description of the data was provided separately (SeeShow MoreRelatedThe Financial Crisis Of The Subprime Mortgage Crisis2261 Words   |  10 Pagesput financial institutions at the centre of harsh debate and massive critism,†¦Ã¢â‚¬ ¦banks had gradually relaxed their screening and monitoring standards before the crisis, especially in the US subprime mortgage market. Then, they sharply curtailed new credit and forced ï ¬ rms to reduce their investments, hence propagating the financial crisis to the real economy,† (J.Godlewski, 2013, p1). The financial crisis which has been mentioned is the financial crisis occurred in 2008. Majority of consumers, companiesRead MoreTypes Of Collateral Used For Business Lending1474 Words   |  6 Pagespersonal and bank guarantees. When banks across developed and developing countries are compared, it was observed that developed countries rank real estate as the most important type of collateral more frequently than the developing countries. About 56% of the developed country banks rank real estate as the most important collateral type for business lending to small firms compared to only 37 % of the developing country banks. In case of developing countries, the banks consider a higher variety of collateralsRead MoreDevelopment Of Rad Tokens983 Words   |  4 Pagesfacilitate the development of our p2p lending platform and a line of credit products. What is RAD token? RAD token is issued to fund the development of RAD Lending Platform and a family of credit products built on it. RAD Lending platform is based on a concept of peer-to-peer (p2p) lending with credit products secured by borrower’s crypto assets. †¢ A family of credit products will start with: †¢ RAD credit card with grace period and a credit limit secured by borrower’s crypto assets †¢ Personal loan securedRead MoreData Mining in Banking Industry2778 Words   |  12 Pagesthe financial behavior before and by the time the client was given the credit. The bank clients are classified into four classes. The first class clients contain all those clients who pay back the bank credit without any problems. The second class clients contain all those clients who pay back the bank credit with little problems here and there. The third class clients contain all those clients who should only get a bank credit after detailed checks because substantial problems occurred in the pastRead MoreEvaluation And Applied Research Methods1068 Words   |  5 Pageshealth programs could be evaluated. Webb (1975) proposed an objective scoring system that enables individual programs to evaluate their capabilities objectively in relation to a realistic, albeit theoretical, model occupational health program. In order to evaluate a program’s capability to fulfill its mission and c ommitment to short range and long range health interests of its employees, Webb (1975) illustrated that having a scoring system in which weights were assigned to different components of aRead More Data Mining in a Nut Shell Essay1701 Words   |  7 Pagespre-process the data† (SAS Institute). There are several different types of models and algorithms used to â€Å"mine† the data. These include, but are not limited to, neural networks, decision trees, rule induction, boosting, and genetic algorithms. Neural networks are physical cellular systems which can acquire, store, and utilize experiential knowledge (Zurada). Neural networks offer a way to efficiently model large and complex problems. Decision trees are diagrams used for making decisionsRead MorePestel Factors Affecting Credit Card Industry1422 Words   |  6 PagesThe political and legal environment In the aftermath of the credit crisis, governments and regulators are strengthening consumer protections and promoting the concept of responsible lending; new developments are being made with the customer’s interests in mind, ensuring that the customer is in control of their own finances,. The Consumer Credit Act section 75 provides added protection to consumers, offered for transactions over  £100. It is notable that higher earners, are among the financially savvyRead MoreA Report on Sme Financing in India3287 Words   |  14 Pagestheir service of SMEs is a major factor in increasing SME access to finance. Although, numerous issues surface when it comes to SME lending, banks, by employing a range of measures, such as risk adjusted pricing, credit scoring models, and SME-tailored non-lending products are developing ways to mitigate risks, lower costs, and increase the overall benefit accrued from SME banking. Question 1: Why Banks should lend to SMEs? SME banking is an industry in transition. From a market that was consideredRead MoreThe Dictionary Of Banking And Finance1471 Words   |  6 Pagesto include a critical place in the field of money related administrations in India in the changed period. This field of money related administrations could turn out to be more imperative in the years to come. The always expanding modernity and developing of the monetary markets from one viewpoint, and the quick changing corporate scene from a defensive foundation to a globalized commercial center on the other, would prompt more unpredictable corporate exchanges and hence, the part of speculationRead MoreIntroduction. Predictive Analytics Is Quantitative Analysis1371 Words   |  6 Pages costs, headcount, metrics; customer churn; credit scoring; cross sell / up sell opportunities; market campaign response; anomalies, fraud. SAP Predictive Analytics is business intelligence software from SAP that is designed to enable organizations to analyze large data sets and predict future outcomes and behaviors. For example, SAP Predictive Analytics can help make sense of big data and the Internet of Things by building predictive analytics models to identify unforeseen opportunities, better