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商业数据分析作业代写 Case Study代写 BISM7233代写

Individual Case Study: Application of analytics method

商业数据分析作业代写 Case Description  Please see below: CREDITBANK of Australia Case Study CREDITBANK of Australia Loan default Case Study

Case Description

 Please see below: CREDITBANK of Australia Case Study

CREDITBANK of Australia Loan default Case Study

CREDITBANK of Australia is one of the major banks in Australia with offices in all the state capitals and offers a wide range of personal as well as business banking products & services to their retail and business customers. It provides a variety of loan services such as personal loans, home loans, business loans, auto loans, study loans, and so on. The Bank operates on a slim profit margin as it offers attractive interest rates on fixed deposits as well as loans. As a result, CREDITBANK of Australia leads the Australian market as one of the largest loan providers that the customers rely on. 

The default loans, also known as Charged Off Loans, are usually declared when payment is 270 days late. 商业数据分析作业代写

Banks can lose a huge sum of money when borrowers default, which in turn, forces banks to reassess their lending procedure to reduce their credit risk. In recent years, loan default rates have increased steadily in the Australian market. Compared to other banks, thanks to its strategy of operating with a slim profit margin, CREDITBANK of Australia is more vulnerable to the impact of increasing loan default rates. The management believes that building analytics capability to understand and predict future loan defaulting applications can help the managers to make better decisions on future loan applications. The management has already started gathering data from both internal and external sources to build models that help to make informed decisions on loan applications.

CREDITBANK of Australia recently hired you as a data analyst, and you are tasked to develop a loan default prediction model.

The bank believes that as a UQ graduate with excellent educational background, you are an ideal fit to develop the model and present it to the executives who would make the decisions on whether to implement it or not. 

Your first responsibility is to deliver the report with a summary of the tasks you performed and insights to solve the problem CREDITBANK of Australia is facing. However, as a new employee, you are still not familiar with the reporting requirements and are unsure about the level of detail. Fortunately, your team has created an incomplete template that you need to fill up with useful insights and analysis based on the model you develop. 

Best of luck with your assignment!

Assignment Deliverable and Report Structure: 商业数据分析作业代写

This is a submission template. Please insert your responses/answers/works between the two opening and closing angled brackets as shown << >> . DO NOT DELETE OR CHANGE ANY OTHER PARTS OF THE TEMPLATE. ANY TEXT OR VISUALS OUTSIDE THE << >> WILL NOT BE GRADED! REPORTS NOT USING THE TEMPLATES WILL BE PENALISED.

Please make sure to carefully read and answer the questions. Answering different questions or not answering each part of the questions will lead to a deduction of points. For each question: 

i. Include screenshots of only the relevant process(es), step(s), or result (s). The number of screenshots should be the same number as asked in the question.

ii. You need to apply two different methods, compare the methods and select the best methods.

iii. You also need to consider several aspects of model building such as, data sampling, cross validation, class imbalance, and performance metrices.

iv. Your screenshots should be clear, with important details visible and similar to the sample screenshots.

v. Your analysis, recommendations, discussions, and conclusions should be related to the model you develop.

vi. Provide your answer in the respective deliverable section

CREDITBANK of Australia Loan Default Report Template 商业数据分析作业代写

1.Executive Summary:  

An executive summary is a short summary (max. 300 words) of the key information in the document and is written for a businessperson. It should contain clear, well-structured, evidence-based summary of your findings from your models and analysis and should provide insights for CREDITBANK of Australia managers on what to consider in order to effectively address the problem of customers defaulting loan application. 


2. Predictive analysis of loan default via RapidMiner:

You understand that data integration is an essential part of business analytical work and that answering descriptive questions through visualizations is helpful to effectively communicate with businesspeople. However, you know that CREDITBANK of Australia’s management and their statisticians will expect some definitive answers about their loan default. You asked the team to prepare an analysis in Rapidminer for you. (Use the tutorial on classification as a reference guide to build analytical process in Rapidminer).


The team knows that you are interested in classifying whether or not a loan application will default in future. The manager asks you to find the best performing models and you are asked to develop two models to predict whether the customer would default the loan based on the past loan applications and loan outcomes provided to you as “loan_default_data.csv”. Based on the lectures and tutorials, develop, and evaluate two different models for classifying loan applications (It’s also okay to choose models outside the content of this course). Remember that you can switch between the different analyses by connecting the respective operator and temporarily disabling the operator (i.e., uncheck “enable operator”) that you do not wish to run in this moment.

Note: You don’t have to use all the variables provided on the original dataset to train the model


Please document all changes and specifications below. Note: You can choose the models learned from this course or choose any other model outside the tutorial exercise.

2.1.1 Deliverable: Screenshot of Analytical Process and explanation of the process

<< Insert screenshots of the analytical process for the first model you choose (include the sub-process within cross validation: one for the process within Cross Validation and one for the overall RapidMiner process)   

Also include brief explanation of the process and operators you create>>

2.1.2 Deliverable: Screenshot of Analytical Process

<< Insert screenshots of the analytical process for the second model you choose (include the sub-process within cross validation: one for the process within Cross Validation and one for the overall Rapidminer process) >>



Now that you have created the process for both models, explain which variable(s) is/are the most decisive predictor of loan default regarding each model

3.1.1 Deliverable: Screenshot of Results of the first model

<< Insert screenshot of the outcomes of the first model>>

3.1.2 Deliverable: Interpretation of the results of the first model

<< Explain the choice and impact of the most decisive predictors (max. 200 words in total) >>

3.1.3 Deliverable: Screenshot of Results of the second model

<< Insert screenshot of the outcomes of the second model>>


3.1.4 Deliverable: Interpretation of the results of the second model

<< Explain the choice and impact of the most decisive predictors (max. 200 words in total) >>


After expertly drawing these conclusions, you anticipate questions regarding the quality of your model. Compare the model performance of both models and justify which method should the management use:

4.1 Deliverable: Screenshots of Results of the two models that you chose.

<< Insert two screenshots >>


4.2 Deliverable: Interpretation and justification of model performances

<< Describe the model performances and describe which model is better for this analytical task. Justify your preference. You may also refer to the loan default, prediction and classification, model selections and other related academic articles, blogs, and other publications to justify the model selections by following academic style of writing and referencing (max. 250 words in total) >>

5.Generate Business Insights and Strategize:  

Generate Business Insights and Strategize:  Following your analysis of loan default in the case of CREDITBANK OF Australia, please present a brief reflection on the value of business analytics for the company. You may also refer to the loan default, ethical issues in prediction models and other related academic articles, blogs, news, and other publications to make the recommendations, explain drivers and discuss ethical issues by following academic style of writing and referencing. In this reflection, you ought to apply your business knowledge to: 商业数据分析作业代写

5.1 Offer compelling explanations for the observed findings (e.g., regarding the financial health and employment information) and suggestions for additional analyses (or data) that could be used to investigate them. (max. 200 words)

<< Develop explanations for the reported findings and describe means on how to potentially analyze and improve the data or model or analysis>>

5.2 Propose specific actions on how to address the identified factors that contribute to loan default. (max. 200 words)

<< Describe means on how to potentially overcome the loan default-drivers that you

identified >>

5.3 Now that you have selected the preferred model for this analytical task, is there any potential ethic problem that you can identify from the data analytical process?   (max. 300 words)

<< Describe the potential ethical and the legal issues that the bank needs to be concerned of  >>


Please include all the references (minimum 5 reference) that you cited in your report.



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