Client Name

JS Bank Ltd

Faculty Advisor

Dr. Mohsin Sadaqat

SBS Thought Leadership Areas

Investment Decision Making

SBS Thought Leadership Area Justification

It helps tailor credit policies so that financial institutions can participate in responsible lending practices

Aligned SDGs

GOAL 12: Responsible Consumption and Production

Aligned SDGs Justification

our project will help Js bank give out better credit to companies partnering with them to achieve  their economic goals and improving the innovation in the economy and infrastructure as a whole. Most importantly, it helps with responsible lending decisions that aligns with responsible consumption and production goals.

NDA

Yes

Abstract

The main aim of this Experiential Learning Project (ELP) was to find out the key characteristics and risk concentration patterns amongst the companies identified as Non-Performing Loans (NPLs) in the corporate lending book of the JS Bank Limited and compare them with the actively performing counterparts. The research will identify most significant qualitative and quantitative warning indicators for NPL formation and suggest a structured Early Warning Framework, which can be integrated with the existing credit management processes within the bank. The study uses a quantitative-descriptive research design based on secondary data collected from the internal credit data of JS bank. The analytical methodology includes a qualitative risk indicator coding, to twelve different warning flags, a financial ratio analysis with the Current Ratio and Debt-to-Equity Ratio, a disaggregation by industry level, fourteen of the most important sectors; and a comparative analysis with the NPL cohort, which comprises 10 companies, and the performing borrower cohort, which is composed of 6 companies. A Financial Health Quadrant was built to categorize companies within four risk quadrants according to the combination of liquidity and leverage. The analysis gives rise to several important results. Foreign exchange (FX) exposure proved to be the top  most risk indicator with 73.3% of NPL companies, highlighting the far-reaching effects of the depreciation of the Pakistan Rupee in the 2022-2024 period. There was evidence of an over-representation of small and medium-size enterprises (SMEs) within the NPL category and a strong under-representation of performing borrowers within the large and very large corporate category. The risk signals that were co-dominant in the loan monitoring stage were declining profitability (60%) and industry slowdown (60%), while negative cash flow (53%) and financing pressure (53%) were each dominant. The ratio analysis of several NPL borrowers was found to be satisfactory at point in time evaluation and thus the financial ratios alone were found to be inadequate. There was a significant variation in risk profiles between industries; FX exposure was the dominant risk for industries such as automobile, construction and fertilizer; high leverage was the key risk for real estate and construction companies; and customer and supplier concentration was the main risk in businesses related to commodities and agri. The findings show significant implications for credit risk governance. The evidence strongly indicates that an industry specific approach to developing an Early Warning Framework would be preferable to a single standard prediction model of NPLs. The bank is recommended to implement a three-stage monitoring process for the entire life cycle of the credit based on the risk profile of each sector: Appraisal, Monitoring and Deterioration. The inclusion of qualitative indicators, together with financial ratios, in an automated Early Warning Scorecard would significantly enhance the bank's ability to identify signs of distress before default, thus safeguarding capital adequacy, lowering provisioning needs and providing better discipline in portfolio management.

Keywords: Credit Risk, Non-Performing Loans (NPLs), Default Risk, Liquidity Risk, Leverage Risk, Current Ratio, Debt-to-Equity Ratio, Financial Distress, Portfolio Risk Assessment, Asset Quality,Initial stage,Loan tenure stage,Deterioration stage,Credit Risk Assessment, Borrower Deterioration, Foreign Exchange Risk, Financial Ratio Analysis, Early Warning Framework, Portfolio Quality, Pakistani Banking Sector,Merton's Structural Model,Macroeconomic Determinant

Document Type

Restricted Access

Document Name for Citation

Experiential Learning Project

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