Nigeria: exploratory analysis of local needs and microfinance supply

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Jan 1, 2012
Dr. Adegbola Ojo, Scott Gaul

In August 2011, MIX launched a map that displays the location of 819 microfinance banks currently licensed to operate in Nigeria. The map gives a basic view on the market supply of microfinance services, in the context of some key factors such as mobile penetration rates and unemployment levels.

In order to take this dataset to the next level, MIX partnered with Dr. Adegbola Ojo of the African Higher Education and Research Observatory (AFRIHERO) in an effort to link the supply of microfinance services with highly localized information on individual districts, or local government areas (LGAs), in Nigeria. In this post, we present a short executive summary of this research, the full results of which are posted in the complete article, Exploratory Analysis of Local Geographies of Need and the Proximity of Microfinance Service Providers in Nigeria.

The analysis yields the following results:

  • The current footprint of microfinance banks is below target levels. Reaching targets would require roughly doubling the geographic footprint of these banks by 2015.
  • Microfinance banks are currently disproportionately represented in urban areas, especially affluent urban areas.
  • Similarly, the location of the poorest and poor households is negatively associated with the supply of microfinance services.
  • Microfinance banks are most likely to reach poor populations by concentrating in the North-East of the country or on rural areas.
  • There is a strong positive relationship between formal employment in the private sector and microfinance supply.

Overall, we can see that there is ground to cover to meet goals for financial inclusion and that using geodemographic data can help to monitor and target expansion to meet development goals.

Setting the baseline

The first step in this investigation is to assess our current knowledge about financial inclusion in Nigeria. Fortunately, we have two sets of indicators to guide us in this endeavor - targets set forth in the Central Bank of Nigeria’s microfinance policy framework and indicators agreed upon by the Financial Inclusion Data Working Group (FIDWG) of the Global Policy Forum. These indicators provide a common framework for measuring financial inclusion and thus we can compare levels and progress from Nigeria to other markets. Tables 1 and 2 below present these indicators and their current levels. (N.B. We compute these metrics only for microfinance banks. The policy framework is targeted only at microfinance banks, but the FIDWG indicators would typically cover all institution types.)

We can draw two quick conclusions from the tables:

  1. Many of the indicators rely on tracking geographic information, such as the location of microfinance providers.
  2. On most indicators, the microfinance banks are currently either short of targets or at what appear to be low-levels.

Table 1: CBN MFB targets

 Target

Target level

Current level

Data sources

To increase access to financial services of the economically active poor by 10 percent annually

10% growth

Not available via public sources

 

To increase the share of microcredit as percentage of total credit to the  economy from 0.9 percent in 2005 to at least 20 percent in 2020; and the share of microcredit as percentage of GDP from 0.2 percent in 2005 to at least 5 percent in 2020

Microcredit / total credit = 20%

0.57%

CBN Statistical Bulletin Tables 4.5 and 8.1

 

Microcredit / GDP = 5%

0.24%

 

CBN Statistical Bulletin Tables 4.5 and 1.1

 

To ensure the participation of all States and the FCT as well as at least two-thirds of all the Local Government Areas (LGAs) in microfinance activities by 2015

100% states coverage

100%

CBN bank listings

 

67% LGA coverage

31% (= 242 / 774)

 

MIX Nigeria site

 

To eliminate gender disparity by ensuring that women’s access to financial services increase by 15 percent annually, that is 5 percent above the stipulated minimum of 10 percent across the board

15% growth

Not available via public sources

 

 

Table 2: FIDWG indicators

 Indicator

Current level

Data sources

Number of access points per 10,000 adults

 Not available via public sources

 

 

Percentage of administrative units with access points

31%

MIX Nigeria site

Percentage of population living in administrative units with access points

41%

MIX Nigeria site + National Bureau of Statistics

Percentage of adults with a regulated deposit account

Not available via public sources

 

Percentage of adults with a regulated form of credit

Not available via public sources

 

 

For instance, from the tables we can see that the CBN is roughly halfway to meeting its 2015 target for coverage of local government areas. Thus, microfinance banks would need to double their coverage within the next 4 years. What are the characteristics of the areas in which MFBs already operate? How do currently under-served or unbanked districts differ from these areas? Through detailed geodemographic information we can begin to build information to help anticipate challenges and opportunities that may be encountered during the potential rapid growth of this sector.

Using geodemographic data

What is geodemographic data? A geodemographic system is an area classification that simplifies a large and complex body of multivariate and multidimensional information about people, where and how they live, work and recreate. Using data from national statistical bodies and detailed geographic information, the NIGECS system provides geodemographic information on the 774 local government areas (LGA) in Nigeria. For each LGA, the data covers ten broad themes:

  • Agriculture
  • Demographic
  • Education
  • Employment
  • Health
  • Household Composition
  • Household Infrastructure
  • Housing
  • Socio-economic
  • Women and Children

Consequently, for each LGA we are able to build a good understanding about each of these factors. All 774 LGAs are further classified according to a hierarchy by their main characteristics, so that we can group similar areas with each other for analysis. The geodemographic approach is anchored in the view that areas that are socially or economically disadvantaged differ in terms of their pathology of disadvantage, but we can group areas that have common characteristics together. In addition, we mapped the location of microfinance banks to LGAs, based on data provided through the central bank. (See our prior post for more on this.)

What do we know about where MFBs operate?

As a first set of results, we can now describe in more detail where microfinance banks operate. In our earlier post, we noted that banks appear to be concentrated in certain parts of the country, and do not appear to target high-poverty areas. Analysis of the detailed geodemographic data confirms that there is a disproportionate concentration of microfinance banks within Urban Nodes. And even within Urban Nodes, the comparatively advantaged districts have greater shares of the proportion of currently-licensed microfinance banks. Similarly, we find that there are fewer MFBs within Country Dwellings (a type of rural area) and in Deprived Intermediate Territories. Deprived Intermediate Territories are of particular interest as some of the key geodemographic features of their residents suggest the likely greater requirement for the microfinance services and social safety nets.

Local needs and local supply

To realize the full potential of the geodemographic data, we need to take this analysis a step further though. While the best way to quantify the need for microfinance services is to embark on a consultation that asks participants direct questions relating to the topic, in the absence of detailed information from such surveys, we can rely on geodemographic data.

As noted above, one area covered by the geodemographic data is socio-economic status, including poverty levels. Analysis of poverty levels by LGA indicates that if an initiative was aimed at the poorest fifth of households selected at random, the likelihood of reaching the target household is highest for:

  • Country Dwellings (with the share of the population in the poorest quintile 48% above the national mean)
  • Intermediate Territories (45% above the national mean)
  • Diluted Societies (40% above the national mean)

Evidence from mapping work further suggests that relative levels of deprivation are greatest in the eastern half of Nigeria and appear to concentrate in the North East. Banks are most likely to reach the poor when based in these localities. While these results conform to findings of earlier work done at regional and state levels, the LGA dimension of the analysis makes it more relevant to community-level decision-making, policy development and deployment.

Using geodemographic data, we can begin to look more closely at the poverty status of the districts in which banks operate as well. At the LGA scale, the location of the poorest and poor households is negatively associated with the supply of microfinance services. In contrast, middle, rich and richest households have positive relationships with microfinance supply. These findings suggest that the supply of microfinance services decreases with increasing propensity for households to be poor.

Relationship between Poverty and Wealth Variables and Modeled Supply of Microfinance


The geodemographic data also provides insights on socio-economic factors, such as difficulty paying costs such as rent, health care or in receiving government payments, such as for pensions.

Government-to-person (G2P) programs have received attention recently as a means for financial inclusion. The LGA information on pension payments indicates a high positive association between irregularity in pension payment and microfinance supply, which suggests that service providers are located within areas with higher predisposition for pensioner households. This may present an opportunity for microfinance banks to target pensioners with product offerings designed to mitigate problems from irregular payments.

We also see a strong positive relationship between formal employment in the private sector and microfinance supply. One would expect microfinance service providers to aim at strengthening the informal economy. However, the strong negative correlation between private informal employment and microfinance supply tells a different story. Why do service providers have significantly high association with these groups of people? Is it because they are more likely to yield greater returns on investment? Could their level of education be a determining factor? Are microfinance banks started or owned by members of this group? These questions call for further analysis.

Conclusion

This research shows that local-level disparities exist in the supply of microfinance for different communities in Nigeria. Using proxy indicators, the study demonstrates the need for microfinance also varies across these community types. From the preliminary findings, it appears that residents of neighborhoods of greater need are under-served, although we have not factored in information on demand for services. Apart from trying to respond to urban unemployment, microfinance banks in Nigeria appear to be located in areas where they are unlikely to meet other key mandates, such as raising the living standards of the rural and semi-rural poor. As the sector expands to meet the CBN policy targets, focusing on these regions is a critical question.

Read the full article for a more in-depth look at our analysis