Impact of interest rate regulation

on MFIs development: case of

Benin in West Africa

Speaker

Romeo S. ZOMAHOUN TCHALA

Workshop UMM «Investments and Regulation in Microfinance »,

Frankfurt School of Finance & Management

July 11th - 12th 2011

Content

Who am I?

Introduction & theoretical framework;

Interest rate regulation in Benin;

Methodology;

Sample description;

Specificity of the approach;

Data collection tool;

CGAP tool for Annual Percentage Interest rate;

Assessing of interest rate ceiling impact in Benin;

Conclusion.

Who am I?

ZOMAHOUN TCHALA S. Roméo

From Benin, a West African country (between Togo and Nigeria)

Studied statistics, Finance and Microfinance (in Benin, France and Belgium respectively)

10 years working experiences with 8 years in the field of microfinance as Statistic Division Chief

and Inspector of MFI

Experience as Intern at CERISE: helped improving their data base on social perfomance

indicators

Writer in chief of the Quarterly report on Microfinance business

Impact studies "Impact and Effects evaluation of RENACA & ACFB on beneficiaries”.

Conducted study on Problems of the introduction of MFIs on the financial market (PADME case).

Experience in writing procedures manuals for microfinance institutions (business plan; credit

policy).

Introduction & theoretical framework

This study tried to proof some evidences through field data analysis and discussed different points of view. It verified these three main hypotheses :

• H1: In Benin, the MFIs respect the interest rate regulation;

• H2: The interest rate ceiling generates mission drift;

• H3: The interest rate ceiling prevents the MFIs from reaching the profitability.

Methodology

To check whether interest rate ceiling is a detriment to the growth and development of Beninese MFIs or not, we apply a deductive

hypothetical methodology. This means that each hypothesis is justified by different concepts enounced in the literature review and verified

by the result of indicators’ calculated with data collected on the field.

• We used two main tools for data collection: secondary data (from CSSFD) and a questionnaire addressed to a representative sample of Benin MFIs.

• data needed to compute the annual effective interest rate set by Beninese MFIs.

• data needed to compute financial indicators for MFIs selected in our sample.

Sample description

The research sample has include sixteen (16) MFIs (Networks had taken as an entity) over forty (40) that are operating in Benin.

In term of branches and representation throughout the country, the sample covers 74.5% of the total of the MFIs of Benin.

93.7% are not for profit oriented.

The data used cover 13 years (1998 to 2010).

Specificity of the approach

Up to now the lack of adequate data does not help to conduct such empirical study.

Generally, most MFIs do not provide accurate information about the annual effective interest rate they charged and therefore make its’ evaluation difficult.

The originality of the present study is that the calculation of the Effective Interest Rate is done based on all the different

fees charged on the loan.

Data collection tool: Elements include in the Effective Interest rate calculation per MFI

Credit Product Short term Ordinary

Individual loan Employee's Loan

Loan amount (in CFA francs) 100 000 5 000 000 100 000 5 000 000

Interest received by period

Rate 1,00% 1,00% 0,50% 0,50%

Periodicity Monthly Monthly Monthly Monthly

Type of rate (declining balance /Flat)

Flat Flat Flat Flat

Fixed Amount

Commissions/ fees

Files purchasing fees

Rate

Fixed Amount 5200 5200 5200 5200

File studies/follow up fees

Rate

Fixed Amount 0 0 0 0

Life insurance fees Rate 2% 2% 1% 1%

Fixed Amount 2 000 100 000 1 000 50 000

Others fees (insurance)

Rate

Fixed Amount

Total 7 200 105 200 6 200 55 200

Compulsory savings Rate 10,00% 10,00%

Fixed Amount 10 000 500 000 0 0

Additional savings Rate

Fixed Amount 0 0 0

Maturity 12 12 100 100

CGAP tool for Annual Percentage Interest rate calculation

Reference Period M <-- Choose S, 15j, M, 2M, Trim, Sem, An

Annual nominal rate 18,000%

Periodic nominal rate 1,500%

Up front Commissions / fees 178 500 <-- Enter calculation formulas (% initial amount, fixed amount, by

tranches...)

Eventual interest up counted 0 <-- up date only if option choice is P (up counted)

Tot.Fees/Commiss./Eventual up counted interest 178 500 <-- Sum of two previous lines

Loan amount 7 000 000

Maturity in number of reference periods 18 <-- " reference period " : understand month if the reimbursement is on

monthly basis

Number of instalment 18

Calculation mode C <- C for Flat or D for Declining balance

D et P incompatibles

When interest Payment should take place E <- P (up) or at the end E; fill in P or E

accordingly

Savings

Savings cumulated through reimbursement --> do

not influence the Present value but will generate a

Future Value

<-- fill in the amount that has to be paid at each instalment (a formulas

or a percentage given to the design)

Compulsory savings (influence the Present Value) 1 050 000 <-- fill in the amount or a formulas that indicated for instance, a

percentage of borrowed amount

Annual rate on deposit

Periodic Annual rate on deposit 0,000%

future Value of deposits 1 050 000

Present Value 5 771 500

PMT = VPM = Capital + Interest 493 889

Total amount of reimbursement 8 890 000

Interest amount paid 1 890 000

EPIR 3,91% Effective Periodic Interest rate (reference period)

Maturity 18

APR 46,93% Annual Percentage Rate of interest.

Assessing of interest rate ceiling impact in Benin

Graph 1 : Analysis of Interest rate Ceiling’s effects

Source: own calculation from field data & data base CSSFD

Graph 2: Distribution of the Average Loan Size from 1998 to 2010 (16 MFIs of the sample)

Source: own calculation from field data & data base CSSFD

Graph 3: Average Loan Size and APR of the 16 MFIs of the sample (1998-2010) “H2”

Source: own calculation from field data & data base CSSFD

Graph 4: Curve of APR and OSS from 1998 to 2010 (16 MFIs of the sample)

Source: own calculation from field data & data base CSSFD

Table 7: Distribution of MFIs of the sample per level

Operating Self Sufficiency ratio over

the last five years Frequency Percentage

Less than 100 11 68,75

More than 100 5 31,25

Total 16 100,0

Source: Own calculation from data base CSSFD

Graph 5: Distribution of APR in function of the operating Self Sufficiency Ratio (H3)

Annual Percentage Rate and others financial indicators from 1998 to 2010

Conclusion

The first immediate effect of interest rate ceiling we found is that the perspective of

respect of the cap could constrain MFIs and prevent them from diversifying their

loan products.

The second effect of interest rate ceiling is the non transparency. As we have seen,

Benin MFIs practices include various loan products (from 2 to 18 loan products)

with several options on the components. Most of them (69% of our sample)

continue to use flat balance method to calculate interest on the loans. This means

that the total loan amount is used to determine the interest rate, ignoring

instalments paid by the borrowers normally on a monthly basis.

By setting a maximum nominal interest rate of 24% per year, MFIs divert

Government, Monetary and Financial Authorities from the fact that they are not

respecting the cap of 27%. As consequences, they integrate different others options

on the loan product that lead to increase the effective interest rate. Indeed, 100% of

the MFIs in our sample charge a certain upfront fee prior to the loan disbursement,

require compulsory savings life insurance, integrate variation on the Maturities or

loan amount to change the design of the loan product.

The non respect of the cap helps loan product diversification but at the detriment of the borrower since loan scheme include several fees put at the charge of the client.

Despite the ceiling Benin MFIs are seeking for exceptionally high profits, as high spreads can still be generated on larger loans. The reality here is that in fact, only competition is determining the price of loan products, not legislation.

The non respect of the cap does not drive MFIs toward sustainability. The main reason for this is that the cap is below the market rate from 34 points of base.

Limitations

The delay for the study was very short;

The extension of the study to other

countries of the West African Union could

help its generalisation;

The study does not take into account all

the transaction cost from the client

perspective. For this, we need more

money and time to conduct such research

especially in a case of a PHD.

Thank you for your attention