Impact of Non-performing Loans on Pakistan Banks

 

This research is done to know the current trend of nonperforming loans (NPL’s) which are bring threats on conventional Banks of Pakistan and bringing highly impact on their performances. According to our research borrowers face difficulties in paying loans due to interest, inflation, taxes, investment & discount rate but interest rate/mark up and discount rate are in explanation of variations which brings highly impact on debt/equity risk, monetary policy, market risk, interest rate risk, liquidity risk, earning risk, credit risk, and solvency risk, which affects the performance of the conventional banks. Data relevant to Security requirement, unsecured loan & late or nonpayment was taken for general information and they are not in explanation of variation. This research is highly reliable with the consequence or outcome of Nonperforming Loans (NPL’s) & the final suggestion regarding nonperforming loans is that the Efficient Loan Appraisal Techniques should be introduce & adopted which is based on risk measurements & conventional investment analysis and the rule of issuance of loan should be in control with the objectives of institution. This research must be study due to recent crisis of nonperforming loans (NPL’s).

Introduction

A loan which has been in default for 90 days or 3 month called Nonperforming loans (Npl’s), these loans caused by nonpayment or failure in payment, although it relies on the agreement also. The greatest figures of nonperforming loans bringing threats in banking sector of Pakistan. The enormous figure of Npl’s is over Rs.398 billion in 2009 and Rs.459840 million till june 2010. The Banks are part of financial institutions; it’s their function to provide funds against of collateral or non collateral security which conversion of assets from excess to shortage of amount in economy. It is risky in treating or dealing effectively to accomplish their task, which is task oriented. Although cash is a part of an assets, when cash or loan could not be covered, then it effect on liquidity risk and credit growth, which puts the bank into trouble. The high borrowers or long terms borrowers are expected to be defaulters, so the long term or big borrowers should be treated carefully. Banks must have strategy to reduce NPL’s. The banks found with highest significance in nonperforming loans are Public sector Bank among all banking industry. Nonperforming loans brings an impact on operating risk, credit risk, monetary policy , market risk, liquidity risk, debt/equity risk, interest rate risk, reputation risk, earning risk, legal risk & solvency risk. Banks must have well structured strategy for the recovery of loan and the Bank must design or apply its own strategy for the recovery of loans. Unanticipated risk and inappropriate credit management could fail the financial institution. Uncertainty in economic condition of Pakistan and in global environment brings the impact in Banking sector. Although there is also a presence of poor strategy and policy, therefore the preventive strategies by managers are appreciated in a banking sector. Conventional Banks of Pakistan are constantly failed in decreasing insufficient performance which is imagined or observed by remarkable business and extraordinary trouble that happens. Customers get dissatisfy while communicating the information during the request or claim that pressurize the recital or routine of the bank. Correct information should be provided by the customer while submitting loan request. The procedure or process of granting loans is a tough step, so the bank should take this step carefully. The management should be highly effective during operations all the activities should be performed with proper documentations and according to the agreement with respect to reach competence. Lending money is risky and it includes risk management of an assets. The strategy of lending and goals should be practical or flexible for accomplishment, controlling assessment and evaluation. Although lending donates of assessing and taking the risk of bankruptcies and the strategies should be present to minimize it. Taking risk is a part of a business especially in banking. The level of achievement for a bank is when the management meet its objectives means the achievement of the bank would be when risks are minimized the net income of the Bank would be in surplus and captures the highest number of stakeholders. Advances and loans are the most important mechanism of Banks assets, these loans could be a threat for a Bank. Several Banks has been solvent due to fail in recovery of loans, it was just because of poor strategies and managing. The Banking industry playing a vital role in the economic development of Pakistan. Earlier studies proved that various banks have found obstacle to meet their objectives due to inefficient of performance causes solvency.

Literature Review

Unsettlement of loans or a loan which has been in default for 90 days or 3 month will grow Npl’s, these loans caused by nonpayment or failure in payment and unrealized markup will also be added to NPL’s. Earlier than the financial crisis of the Asia, finance experts believed that the Bank should be treated as supplementary administration reserves and in order to manage growing liquidity problems & nonperforming loans in the banking system. (Victor Shih, 2004). Nonperforming loans contain principle payments, interest & additional financial data. Loan losses could be increased in future after the after the disclose of loan loss provision and income statement disclosed or revealed as accrued expense. All uncollectable loans supposed to be as loan charge offs which are assets write-off that must be managed separately in financial statement and it can be subsequent from income statement and balance sheet. (Dr. Ishrat Husain, 2002) Every organization builds on its assets and loans are mentioned as receivables in the balance sheet and the unrealized mark up would also be include when these receivables cannot be collected then they will considered as non performing loans. Nonperforming loans bring highly impact on conventional banks.

Gross NPLs/gross advances and net NPLs/net advances necessarily monitored because they are reasonable and simple. Better quality of loans is issued due to carefulness, these ratios could be decline after a while and assets could be affected. The non-provisioning of NPL’s could bring an impact or a threat on the performance of the entire banking system. The higher the provision, the lower the systemic risk will be (Dr. Ishrat Husain, 2002). The banks must monitor the payment series of the borrowers and take some legal action against the defaulters less monitoring could be the reason of nonperforming loans. Nonperforming loans could not be removed from conventional banks but it can be minimize by increasing security requirement, reducing unsecured loans and making restrictions on late payment, the strategy should be flexible and well structured.

The study has shown that high income earners has superior access to property and mortgages while low income earners have inferior (Cheron, 1999). The credit endorsement rates is greater than before for usually discarded households, mostly low income, inflation, taxes non white and younger households (Getter, 1996). Lending methods for low income earners, non white and younger households separate them from the financial system which is not socially acceptable.

The default risk of lenders evaluation depends on the loan arrangement, which is obviously depend on the employment, income and credit history of the borrower at issuing loan, household has connection or linked with marginal risk (Higgins, 1999). Although failure in adjusting the credit risk will increase the loan default risk, hence instant or immediate rising in the cost of financial institution causes decreases the further borrowing of retail credit (Lucket, 1988). In nonprofit organization, the appropriate risk management strategy is more complicated to define, in this situation the managers or bankers have to develop such strategy which decrease the loan default risk in order to recover loan and maintain capital (Eales and Bosworth, 1998). The task is to maintain the loan recover it, reduce credit risk and to reach at a low cost credit it could be achievable or enhanced by ethical risk obstacles that households face while claiming or requesting for a loan. Collateral security requirement control the all risk in a better way. Risk management and this diversified strategy will accumulate the huge demand of credit of different sector of financial system but also minimize the nonperforming loans (Badu, 1999). The bank should have to sanction the loan where chances of risk would be less before assigning loans the credit history of the borrower must be seen. The chances of liquidity risk, solvency risk and earning risk are high during issuance of loans. The new credit culture, certainly, has some negative impact as credit officers have turn into more risk reluctant in recommending new loans and the potential borrowers have turn into more alert in contracting new loans. Turn down in private sector credit can be to some extent recognized to this risk dislike among the bank credit staff. The SBP is trying to lessen this by asking the banks to expand their portfolios and inaugurate new lines of business – consumer.

Studies have described that increased in consumer credit with its ease of access, unemployment to households moves them to the bankruptcies in developed countries (Ziegel, 1997; Getter, 1996; Sullivan and Drecnik Worden, 1991). Studies have described that high debt service levels and social attitudes have an interconnection with individual bankruptcy (DeVaney and Lytton, 1995). Some of the borrowers believe that being bankrupt is the solution of credit problems except of paying loans according to the contract or an agreement (Sullivan and Drecnik Worden, 1991). Perception and experiences are applied by credit officers to appropriate constant lending principles. The belief is that the borrowers should be access in terms of nature, reason of the loan, capability or schedule of repayment and available collateral security (Shanmugam, 1992). Borrowers become defaulters due to late on nonpayment so late or nonpayment should be treated strictly. The position of defaulters occur where risk is high so the banks should not grant the loan where chances of risk would be high because defaulters is the position of the borrowers by which non performing loans occur.

The current issue in credit & risk management is Nonperforming Loans. The growth of NPL’s is a threat on economy as well as which declining trade (Deservigny & Renault, 2004) described that NPL’s has got a latest measurement now as an assets, interest rate & credit management. Increasing threats of NPL’s bring impact on bank balance sheet and income statement causes constant Banks failures, the Central Bank provides guidelines and services in order to manage credit, overdraft, advances, Bankers approval, commercial documents, leases, guarantees, bills discounted and contingencies are interrelated with credit risk of Banks. The credit activities in provision of repayment and nonpayment could be in assembly of performing and nonperforming facilities of credit (Kassim, 2002) define the impact of nonperforming loans as: Insufficient credit measurement, insufficient management, false practices, require flexible credit policy, unnecessary stress on profitability, Fault in documentation, Political & economic uncertainty, weak sector, strange competition, Social & political pressure on operations of Banks, inconsistencies in policies and rules (Elaine, 2007) define Credit risk or NPL’s could be the reason of loss or default risk, Flexible credit evaluation or assessment of loan is necessary for the creditor (Dorfman, 1998) define bankers need to know the credit principles, the procedure through which the credit value & arrangements are evaluate, assessment method, concession, take notes, crisis decision & credit risk should be successfully manage (Abolo, 1999) define credit’s protectionism, appropriateness & effectiveness force the Bankers to come on a track of lending system & policy. Credit is based on a trust; it’s not an issue that borrower and lender have trust on each other & it could not reduce the value of loan selection analysis, this trust could be dishonored consciously or unconsciously, its includes sound credit analysis (Nwankwo, 1991) define the procedure of evaluating the business or personal credit risk adjacent to accruable profit from those investments. The profits could be direct or indirect in terms of interest earning & deposit balances essential according to the situation of loan, which is launch or preservation of an association with borrower causes enhanced deposits received by the Bank and insist for a diversity of Bank services. Additional description is that the credit risk evaluation has quantitative and qualitative aspects. The credit officer must have borrower’s information & record, identify the actual and accurate reason of borrowing, determine the risk of the borrowers that borrowers face existing & potential of political, economical & approximate the level of assurance concerning the repayment.

In the approximation of financial portfolio capability, Banks must not bound the analysis at task assessment method without help and the entire credit risk are also assessed which could bring an impact on portfolio (Schall & Halley, 1980) define that loan analysis would be summarize as ability, security, assets, circumstance and personality. Lending creates the assets risk & it’s a valuable project for the management of the Bank. The greatest way of earning is receivable and risky task for the Bank. The financial cost of these loans, are valuable and differ with possibility and the crisis extent. (Cortavarria Luis & C. Dziobek, 2000)The main reason of the failure of the Bank is Nonperforming Loans & this NPL’s has trim down the values of credit risk management. The soul of credit risk management is the recognition of the accessible and possible natural risk during issuance of loan. The procedures to minimize them is to make a flexible & innovative strategy which could control the credit risk (Deservigny and Renault, 2004) defines that credit risk management procedures involves some guiding principles that causes credit risk. First one is objectives should be increase or decrease the credit risk i.e. strategies on applications, experience, sufficient expansion, issuing loans to associated parties, or over experienced. The second one, which reveals the bank to credit risk i.e. rules of resources categorization. The third one strategies of loan loss provision

Methodology

It is the basic structure of the research. In other word, I am going to make a participative survey. It is basically a quantitative and causal research. This research has done in year 2010. In this research I have made 200 sample sizes but 50 of them have been dropped out due to fake or incomplete information. 100 sample size has been made to collect data from borrowers and 100 made to collect data from Bankers. Borrowers & Bankers would be the sample unit of the research, so the data has collected from 100 borrowers and 100 Bankers from different areas, with different ages, income and gender. The sample technique that I have used for research is snowball sampling because borrowers & Bankers data are confidential and Conventional Banks have not provided me data relevant to borrowers and Bankers, that’s why I have to choose snowball sampling in which I have got the references for the collection of data. Data have collected from two different sources are mentioned below. Secondary Sources: Published Articles, websites, L.E.J digital Lab (University of Karachi), Maulvi Abdul Haq Library (FUUAST, Gulshan Campus, Karachi). Primary data Collection: Primary data will be collect from different borrowers or defaulters of banks.

Hypothesis Testing

It is the most valuable part of the research in which i have to prove my research, which can be done on the basis of hypothesis testing. The primary data which I have collected through survey has Cronbach’s Alpha (α) = 0.805 which means data is 80.5% reliable. I worked on the F- test and Test, this test has divided into between people effect (this is effect due to survey) and within people effect (this is the unsystematic variation in the data). The between people effect is overall the survey effect (the impact of nonperforming loans on conventional banks), where the sum of squares for the model (SSM = 472.854) and the average amount of unsystematic variation, Between people Mean Square (MSR = 4.776) and the sum of squares for the model (SSM = 3334.286) and the average amount of unsystematic variation, within people Mean Square (MSR = 2.565) and the Grand Mean (GM = 3.43) which is good enough. In the analysis of T-test and F-test where P = 0.000 which means there significance level is less than 0.05 (P<0.05) has been found, it means H0 (null hypothesis) is rejected and H1 is proved and accepted on the basis of analysis and significance level.

H1 = The Nonperforming loans will bring impact on Conventional Banks.

H0 = The Nonperforming loans will not bring impact on Conventional Banks.

Data Analysis

The data I have collected are primary and secondary first I am to analyze secondary these data were provided by State Bank of Pakistan as you can see the tables. This secondary which is mentioned below, only all banks data would be analyzed because it’s the compilation of the data.

By looking at the table as you can see the Nonperforming loans in 2002 has decreased to 0.05, in 2003 the Nonperforming loans has decreased to 0.09, in 2004 the Nonperforming loans has decreased to 0.05, in 2005 the Nonperforming loans has decreased to 0.11, in 2006 the Nonperforming loans has decreased to 0.02, but in 2007 the Nonperforming loans has increased to 0.24, in 2008 the Nonperforming loans has increased to 0.61, in 2009 the Nonperforming loans has increased to 0.15 and in 2010 which semiannual data, the Nonperforming loans has decreased to -1 this figure is different because this data is half year data and the figures of year 2010 are in million Rupees while the rest of figures were in billion Rupees

By looking at the table as you can see the Net Nonperforming Loans in year 2002 has decreased to 0.17, in 2003 the Net Nonperforming loans has decreased to 0.16, in 2004 the Nonperforming loans has decreased to 0.20, in 2005 the Net Nonperforming loans has decreased to 0.26, in 2006 the Net Nonperforming loans has decreased to 0.20, in year 2007 the Net Nonperforming loans has decreased to 0.19, in 2008 the Net Nonperforming loans has increased to 2.77, in 2009 the Net Nonperforming loans has increased to 0.07 and in 2010 which semiannual data, the Nonperforming loans has decreased to -1 this figure is different because this data is half year data and the figures of year 2010 are in million Rupees while the rest of figures were in billion Rupees

By looking at the table as you can see the Net NPLS to Net Loans , in 2004 the Net NPLS to Net Loans was 3.8%, in 2005 the Net NPLS to Net Loans has decreased to 2.1%, in 2006 the Net NPLS to Net Loans has decreased to 1.5%, in year 2007 the Net NPLS to Net Loans has decreased to 1.1%, in 2008 the Net NPLS to Net Loans has increased to 3.47%, in 2009 the Net NPLS to Net Loans has increased to 3.73% and in 2010 which semiannual data, the Net NPLS to Net Loans has increased to 3.81% this figure is different because this data is half year data and the figures of year 2010 are in million Rupees while the rest of figures were in billion Rupees

The primary data that I have collected from the borrowers to know what difficulties and problems they faces in paying loans, this was necessary to know the reason which brings obstacles for the borrowers in paying loans.

Demographic

The data that I have collected in terms of age, gender and income has been analyzed. According to age group analysis 22% respondent were between 18-25, 32% were between 26-35, 21% were between 36-45, 18% were between 46-55 and 7% were Above 55%. Male Respondent was 65% and Female was 35%. With respect to income the respondent who has income below Rs.15000 were 7%, between Rs. 16000 – Rs. 25000 were 25%, between Rs. 26000 – Rs. 35000 were 26%, between Rs. 36000 – Rs. 45000 were 20% and Above 46000 were 22%.

Age group has mode 2 which means between the age of 26-35 years are highly respondent and the mean is 2.56, the mean is the average of the data which describes the central location of the data, standard deviation is σ=1.217, standard deviation indicates that the data points tend to be very close to the mean, and the variance is σ2 = 1.481 It describes how far values lie from the mean. In gender mode is 1 which means males are highly respondent. In Income mode is 3 which means respondent having income between Rs. 26000 – Rs. 35000 are highly respondent and the mean is 3.25 standard deviation is σ=1.250, and the variance is σ2 = 1.563. These all data analysis were that anaylsis of demographic variables.

Bankruptcy

The data I have collected from the borrowers 86% of them were non defaulters and 14% of them were defaulters, and mode is 0 means non defaulters were highly respondent. The research was conducted to know the reasons that create the problem for the borrowers in paying loans that’s why I have to collect primary data from the borrowers only. The variables which create the problems for the borrowers are high interest rate and mark up, inflation and taxes.

Nonperforming Loans

The most important variable of this research is nonperforming loans. This data is collected to know and to provide the knowledge relevant to the nonperforming loans that their nonpayment of loans could be the reason of Nonperforming Of loans, here the medians is 5 and range is 4 means maximum respondent are strongly agree and minimum respondent are strongly disagree that their nonpayment of loans could be the reason of non performing of loans. The Pearson’s correlation coefficient has been analyzed to see the covariance’s between two variables

Regression also has been analyzed to see relationship between the variables

Regression Equation(y) = a + bx

Slope(b) = (NΣXY – (ΣX)(ΣY)) / (NΣX2 – (ΣX)2)

Intercept(a) = (ΣY – b(ΣX)) / N

This variable has been taken to see the variations with other variables that could be the reason of nonperforming loans.

Interest/Markup

The way of income for every conventional bank is interest/mark up, here the median is 5 which means majority of respondent are strongly agree that high interest rate/markup creates problem for them in paying loans because they have to pay the excess amount of money than the actual amount, median is the numeric value separating the higher half of a sample, a population, or a probability distribution, from the lower half and the range is 4 means maximum respondent are strongly agree and minimum respondents are strongly disagree, it is the length of the smallest interval which contains all the data or it is the difference between the maximum data and minimum data.

The correlation between nonperforming loans and interest/markup r = 0.951 has been found which is strongly positive and p = 0.000 means the significance level is less than 0.05 (p<0.05). If interest/markup is increase then nonperforming loans will also increase.

The regression equation is where y = nonperforming loans and x = Interest/markup

Nonperforming loans = 0.350 + 0.938Interest/markup

And the coefficient of determination is 0.903 therefore, about 90.3% of the variation in the in the nonperforming loans data is explained by interest/markup. The regression equation appears to be very useful for making predictions since the value of r2 is close to 1.

Income

The another variable of the research is income, the borrower pay the loan from his income if the borrowers income or another variables bring impact on the income then of course it will become the reason for nonpayment of loans. Here median is 5 and range is 4 it means maximum respondent are strongly agree and minimum respondent strongly disagree that their income could be the reason of nonpayment of loans.

The correlation between nonperforming loans and income r = 0.600 has been found which is strongly positive and p = 0.000 means the significance level is less than 0.05 (p<0.05). If income is affected then nonperforming loans will also affected.

The regression equation is where y = nonperforming loans and x = Income

Nonperforming loans = 2.215 + 0.530Income

And the coefficient of determination is 0.360 therefore, about 36% of the variation in the nonperforming loans data is explained by income. The regression equation appears to be not useful for making predictions since the value of r2 is not close to 1.

Inflation

Inflation is increase in the prices of services & goods, it is the variable which brings highly effect on other variables on household size and income as well as on other variables, in the similar way inflation will create the problem necessarily for the borrowers in paying loans because it will increase their spending and decrease their saving by which they have to pay their loan. Here the median is 5 and range is 4 means maximum respondent respondent are strongly agree and minimum respondent are strongly disagree that inflation creates the problem for them in paying loans.

The correlation between nonperforming loans and inflation r = 0.591 which is approximately r = 0.6 has been found which is strongly positive and p = 0.000 means the significance level is less than 0.05 (p<0.05). If inflation is increase then nonperforming loans will also increase.

The regression equation is where y = nonperforming loans and x = Inflation

Nonperforming loans = 2.268 + 0.524Inflation

And the coefficient of determination is 0.349 therefore, about 34.9% of the variation in the nonperforming loans data is explained by inflation. The regression equation appears to be not useful for making predictions since the value of r2 is not close to 1.

Taxes

Tax is a financial charge on an individual or personality. When high tax is impose then the individual have to bear the burden, especially in Pakistan where the situation of Tax is different than other countries where government focuses on indirect tax rather than direct tax. Median is 4 and range is also 4, which mean maximum respondent are strongly agree and minimum respondent are strongly disagree that the Tax rate create the problem for them in paying loans.

The correlation between nonperforming loans and Taxes, r = 0.266 which is approximately r = 0.3 has been found which is weakly positive and p = 0.005 means the significance level is less than 0.05 (p>0.05). If taxes increase then nonperforming loans will also increase.

The regression equation is where y = nonperforming loans and x = Taxes

Nonperforming loans = 3.791 + 0.196Taxes

And the coefficient of determination is 0.071 therefore, about 7.1% of the variation in the nonperforming loans data is explained by Taxes. The regression equation appears to be not useful for making predictions since the value of r2 is not close to 1.

Investment

Another part of this research is to know, have the borrowers taken loans for the investment or for another purpose. Here median is 4 and range is also 4, which mean maximum respondent are strongly agree and minimum respondent are strongly disagree that they take loans for the investment.

The correlation between nonperforming loans and investment, r = 0.354 has been found which is weakly positive and p = 0.000 means the significance level is less than 0.05 (p<0.05). If Investment increases then nonperforming loans will also increase.

The regression equation is where y = nonperforming loans and x = Investment

Nonperforming loans = 3.791 + 0.196Investment

And the coefficient of determination is 0.125 therefore, about 12.5% of the variation in the nonperforming loans data is explained by Investment. The regression equation appears to be not useful for making predictions since the value of r2 is not close to 1.

Discount Rate

Another part of this research to know will they be able to pay loans if low discount rate is offer to them. Discount rate is made with the KIBOR* (Karachi Inter Bank Offer Rate) these two variables are directly proportional to each other. These rates are decided by State Bank Of Pakistan these rates are increase or decrease in order to increase or decrease the saving and investment, but if increase then these will create problem for the borrowers in paying loans. Here the median is 5 and range is also 4 means maximum respondents are strongly agree minimum respondents are strongly disagree that they will be able to pay loans if discount rate is offer to them.

The correlation between nonperforming loans and Discount rate, r = 0.915 has been found which is strongly positive and p = 0.000 means the significance level is less than 0.05 (p<0.05). If discount rate increases then nonperforming loans will also increase.

The regression equation is where y = nonperforming loans and x = Discount Rate

Nonperforming loans = 0.696 + 0.855Discount rate

And the coefficient of determination is 0.837 therefore, about 83.7% of the variation in the nonperforming loans data is explained by discount rate. The regression equation appears to be useful for making predictions since the value of r2 is close to 1.

Security Requirement

Another part of this research is relevant to security requirement during issuance of loans, Here median is 4 and range is also 4, which mean maximum respondent are strongly agree and minimum respondent are strongly disagree to the security requirement during issuance of loan.

The correlation between nonperforming loans and security requirements is r = 0.343 has been found which is weakly positive and p = 0.070 means the significance level is less than 0.05 (p<0.05). If security requirement increases then nonperforming loans will also increase.

The regression equation is where y = nonperforming loans and x = Security Requirement

Nonperforming loans = 3.600 + 0.252Security Requirement

And the coefficient of determination is 0.118 therefore, about 11.8% of the variation in the nonperforming loans data is explained by security requirement. The regression equation appears to be not useful for making predictions since the value of r2 is not close to 1.

Unsecured Loans

Unsecured loans are the loans which does not have security requirement these loans are issue on the basis of salary or personality, Here median is 3.50 and range is 4, which mean maximum respondent are strongly agree and minimum respondent are strongly disagree to the preference of unsecured loans.

The correlation between nonperforming loans and unsecured loans is r = 0.189 which is approximately r = 0.2 has been found which is weakly positive and p = 0.060 means the significance level is greater than 0.05 (p>0.05). If unsecured loans increase or decrease that do not significantly relate to increases or decreases in nonperforming loans.

The regression equation could not be made on unsecured loan because their significance level is greater than 0.05.

Allowance To Late Or Nonpayment

The median is 4 and range is also 4, which means maximum respondent are strongly agree and minimum respondent are strongly disagree to allowance of late or Nonpayment of loans. Which clarifies that the borrowers want to pay loans and they are strongly agree to pay but if they are not able to pay than they should be allow to pay late.

The correlation between nonperforming loans and allowance to late or nonpayment, r = 0.156 has been

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