Okello3030-i/FINANCIAL-PROJECT-ANALYSIS

Analyzed loan default trends in Uganda (2018–2026) across major financial institutions. Assessed causes of non-performing loans, borrower behavior, and credit risk practices, providing recommendations to improve loan recovery, reduce defaults, and strengthen financial sector stability. # FINANCIAL-PROJECT-ANALYSIS Analyzed loan default trends in Uganda (2018–2026) across major financial institutions. Assessed causes of non-performing loans, borrower behavior, and credit risk practices, providing recommendations to improve loan recovery, reduce defaults, and strengthen financial sector stability. ## Project Overview This project analyzes loan default trends in Uganda between 2018 and 2026, focusing on the factors that contribute to non-performing loans (NPLs) across major financial institutions. The study evaluates borrower characteristics, economic conditions, lending practices, and institutional performance to identify the key drivers of loan defaults and recommend strategies for reducing credit risk. ## Objectives * Analyze loan default trends from 2018–2026. * Identify factors associated with borrower default. * Compare default rates across financial institutions. * Assess the impact of macroeconomic conditions on loan performance. * Develop predictive insights for credit risk management. ## Key Drivers of Loan Defaults ### Borrower Factors * Income level * Employment status * Business performance * Credit history * Existing debt burden * Loan purpose ### Loan Characteristics * Loan size * Interest rates * Repayment period * Collateral availability * Type of credit facility ### Macroeconomic Factors * Inflation rates * GDP growth * Unemployment rates * Exchange rate fluctuations * Effects of COVID-19 and economic shocks ### Institutional Factors * Credit appraisal standards * Loan monitoring practices * Recovery mechanisms * Risk management policies ## Methodology ### Data Collection Data sourced from: * Annual reports of major Ugandan banks * Bank of Uganda publications * Uganda Bureau of Statistics (UBOS) * Financial institution disclosures ### Data Preparation * Cleaning missing values * Standardizing variables * Removing duplicates * Creating analytical datasets ### Exploratory Data Analysis (EDA) * Default trends by ye …