A case study presentation of credit bureau data files in Uganda of how some of the smallest borrowers in the country are committing to repay large loans elsewhere.

All lending institutions that are regulated by the Bank of Uganda (BOU) have been sharing positive and negative credit data in the form of loan  application and loan performance data to the credit bureau. Since the launch of the credit bureau in 2009, data from ongoing monthly submissions and historical extracts that have been collected has enabled the bureau to start seeing information that was previously unavailable for review. Much like many emerging market economies, Uganda has suffered from not having a reliable and unique national identification system. This was an obstacle to any early plans to deliver a credit bureau and all initial efforts were compromised. Bank of Uganda’s requirement was that all borrowers should be  properly identified and as part of the credit bureau project all borrowers are now required through bank regulations to be enrolled on the biometric based Financial Card System (developed and supported by Compuscan). Through this system each borrower has been able to get a unique identity and the status quo of no identity number has been restored. With the workable identity solution, the credit bureau was able to be developed and deployed successfully.

A key concern that was expressed to Compuscan about lending in the country was the ability (prior to the introduction of the credit bureau) for borrowers to take out loans at multiple institutions, sometimes even at the same institution across different branches, and declare different information about  themselves allowing them to get credit easily, without fear of being declined. With the introduction of the credit bureau several organizations are reporting being able to reduce these exposures. The credit bureau is assisting to highlight risks where other exposures are and how they are being  managed by the borrowers concerned. Lenders can also see how well (or not) these debts are being repaid and can use this information to make  further quality decisions.

Concerns starting to be raised

Although there are 28 institutions that participate in the credit bureau (regulated by BOU) the bulk of debt volume in the country lies with the smaller informal Microfinance sector where large exposures that go bad can have undesired and crippling effects to the economy. As more and more borrowers are cornered for not being able to get credit due to their history being properly recorded on the database concern is being raised as to where these people will go.

The need for money does not stop simply because the bank won’t lend it! To better understand cross exposures of small debtors in Uganda and to test  the claims that “many borrowers are multi-borrowed” an analysis of the data was undertaken.

The Analysis

An extract was performed as follows:

• Loan at Micro Finance Deposit Taking Institution (MDI) borrowers of less than $450, and
• Cross borrowing exposure at other lenders where other loans had a value of $2350 at disbursement

The full sample represented 534 loans where a borrower had both a small exposure at an MDI in Uganda and a significantly larger exposure  elsewhere.

Exposures at other Institutions Table 1 shows how the debt is broken down at other Institutions (number of accounts in the value categories) showing that there is a very clear correlation where borrowers have more than one active loan account at different institutions. For this purpose the current
balance owing on the debt has been used so that there is clear relevance to measure that the exposures elsewhere are current and “real”.

Table 1 MDI Exposures by Current Balance elsewhere

To see the full extent of this information is to understand the cumulative groupings which are presented in Table 2. For comparisons purposes three scenarios are presented to show how borrowers are indebted elsewhere, and to what extent.

Table 2 Cumulative groupings of MDI borrowings elsewhere

• 83% of all borrowers have exposures elsewhere of more than $1,000 and less than $10,000
• 35% of all borrowers have exposures elsewhere of more than $10,000 and less than $15,000
• 10% of all borrowers have exposures elsewhere of more than $15,000 and less than $20,000

Bad borrowers are bad everywhere

The analysis looked at credit risk classifications according to the definitions laid down by BOU. 34% of MDI debt sampled was deemed higher than normal risk.

Table 3 MDI Risk Classifications of loans analysed

This data was then cross analysed with data from the loans at other Institutions to see how the debt was performing elsewhere. This increased the total high risk percentage to 40% (211 out of 534). All loans shaded in red are deemed to be high risk according to the institutions that report on these loans to Bank of Uganda.

Table 4 Cross risk exposures of all loans analysed

Conclusions Cross borrowing or multi borrowing definitely exists. High concern is expressed at the percentage of accounts that are exposed (40%) with
adverse risk classifications.

Using the MDI loans in this sample as a proxy for MFI loans (whose data is not on the credit bureau and is therefore not available at this level of detail) there is a strong argument to suggest that high levels of poor performance and further multiple borrowing exists within MFI data that the Banks and  MDI’s in Uganda are not seeing when making credit decisions.

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