BANK LOAN ANALYSIS USING SSMS, SQL, & POWER BI





DATA OVERVIEW

This dataset comprises detailed records of bank loans, including nearly 40,000 rows and 24 columns, representing various attributes related to loan applications and client information. The data, which was loaded into Power BI using SQL Server Management Studio (SSMS), offers a comprehensive overview of key metrics that influence loan performance and decision-making processes. Below is a breakdown of the types of data captured in the dataset:
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Client Information:
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ID: Unique identifier for each loan applicant.
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Address: Geographic location or address details of the clients. This may help in region-based analysis or assessing the impact of location on loan repayment patterns.
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Loan Application Attributes:
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Application Type: Indicates whether the loan is individual or joint. This column helps differentiate between single applicants and co-borrowers.
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Employment Duration: Captures how long the client has been employed, which can indicate financial stability.
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Employment Title: Job designation or title of the applicant, which might correlate with income level and loan approval rates.
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Grade of Loan Applied: Represents the loan’s risk grade, based on the applicant’s creditworthiness. Grades typically range from A to E or beyond, where A is the most secure.
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Client’s Financial Position:
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Home Ownership: This column indicates whether the client owns a home, rents, or has a mortgage. Homeownership is a key factor that may influence loan approvals or rates.
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Annual Income: Captures the client’s yearly income, which is an essential factor for assessing loan eligibility and repayment capacity.
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DTI (Debt-to-Income Ratio): This ratio measures the applicant’s total monthly debt payments in relation to their gross monthly income. Higher DTI ratios often signify a higher level of risk.
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Loan Details:
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Loan Issue Date: The date when the loan was officially issued or funded.
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Loan Status: This column categorizes the loan into various statuses, such as “Fully Paid,” “Current,” or “Charged Off.” It provides insight into whether the loan is active, has been repaid, or defaulted.
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Loan Purpose: Describes the reason for the loan, such as debt consolidation, home improvement, education, or medical expenses.
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Loan Term: Refers to the length of the loan, typically represented as 36 months or 60 months, showing the time horizon over which the loan is to be repaid.
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Loan Amount: This captures the total loan amount requested or disbursed. It can range from small personal loans to larger amounts for business or significant personal expenses.
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Loan Repayment Information:
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Installment: The regular monthly payment amount the client is expected to pay towards the loan.
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Interest Rate: The rate of interest charged on the loan, expressed as a percentage. Higher interest rates are often linked to riskier clients or longer-term loans.
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Total Payment: The cumulative amount paid by the borrower throughout the loan’s lifespan, including principal and interest. This field gives insights into the loan’s overall cost to the borrower.
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Credit History:
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Last Credit Pull Date: Refers to the last time the borrower’s credit report was checked, typically by the lender. This helps in evaluating the client’s financial condition at various stages of the loan.
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Last Payment Date: Captures the most recent payment date, offering insights into whether payments are up-to-date or late.
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BANK LOAN ANAYTICS BI DASHBOARD
There are three main dashboards that can be used to keep track of different aspects of the Bank loan data: Loan Portfolio Summary, Good vs Bad Loans, and Loan Details Breakdown. Let me walk you through each one.
Loan Portfolio Summary
Click on the image to view the interactive dashboard
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In the first dashboard of my bank loan analysis, I provide a high-level summary of the loan portfolio's performance.
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The dashboard highlights key financial metrics such as the total funded amount, which stands at $435.8 million, and the total amount received, which is slightly higher at $473.1 million.
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Month-over-month (MoM) comparisons indicate a 13% increase in the total funded amount and a 15.8% growth in the total amount received.
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These figures are complemented by a breakdown of the total loan applications, showing that 38.6K applications have been submitted, with a 6.9% MoM increase.
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The dashboard also provides insights into average interest rates and debt-to-income (DTI) ratios, both of which show modest increases month-over-month, standing at 12.4% and 13.7%, respectively.
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These summary metrics give a snapshot of both the volume and the health of the bank's loan portfolio.
Good vs Bad Loans
Click on the image to view the interactive dashboard
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The second dashboard delves deeper into the details of good and bad loans. It categorizes loans based on their performance, revealing that 86.2% of the loans issued are classified as "good" loans, while 13.8% are considered "bad."
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A closer look at these categories shows that 33K of the loan applications fall into the "good" category, with a total funded amount of $370.2 million and a received amount of $435.8 million.
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In contrast, there are 5K "bad" loan applications, with a funded amount of $65.5 million and a received amount of $37.3 million, signaling potential defaults or other financial issues.
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The dashboard also provides loan status details, breaking down the total number of loans into categories such as "Charged Off," "Current," and "Fully Paid."
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For example, loans that have been fully paid amount to $351.4 million in funded amounts and $411.6 million in total amounts received, which reflects successful loan completion and recovery.
Loan Details Breakdown
Click on the image to view the interactive dashboard
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The third dashboard provides a more granular view of the loan details, offering insights into loan applications by various dimensions such as loan purpose, client work experience, state, and loan grade.
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​For instance, the most common loan purpose is debt consolidation, followed by credit card repayment and home improvement.
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The dashboard also shows the loan application distribution by client work experience, with the majority of applications coming from clients with 10+ years of experience.
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Furthermore, I included a breakdown by loan term, showing that 73.2% of the applications are for loans with a 36-month term, while 26.8% are for 60-month loans.
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This level of granularity helps me understand the demographics and behaviors of loan applicants, enabling more informed decision-making regarding loan issuance and risk management.