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Posted on November 9, 2017

Building a better compass: creating financial inclusion measures that are allied with people and their well-being, Part 2

The last blog in this series argued that using formal account access as the primary yardstick for progress in financial inclusion is a poor navigational tool for stakeholders working to strengthen the link between financial systems and the well-being of populations.  Rather than starting from a definition of financial inclusion that is focused on service types, providers or technologies, we might consider starting with what finance can help people be, do and become.

At their best, financial services are tools to help people manage their daily needs, protect them from potentially catastrophic shocks, help them achieve the big goals they value, such as seeing their children get a good education, upgrading the roof of their home so it doesn’t leak during downpours and in many settings, even be source of social well-being through the reciprocal relationships, community investment, enhancement of identity and status that more informal financial services enable. At their worst, as might be the case with predatory loans that overburden borrowers with debt, financial services can also erode these abilities. In many cases, such as with accounts that are dormant or only used as “mailboxes”, formal financial services may not do much at all to improve people’s financial well-being.  

In 2010, motivated by the limitations of monetary measures of poverty, the Oxford Poverty and Human Development Initiative (OPHI) designed and introduced the Multidimensional Poverty Index (MPI)[1]. In part, the MPI starts from the recognition that people understand their experiences of poverty as being more than just lack of income. By tracking a broader set of disadvantages, such as little schooling, access to clean water or the quality of jobs, the MPI is able not just to identify who is poor but how. While the MPI has provided donors and policymakers an additional lens with which to measure and track poverty within and across countries, of most interest here, is the methodology it employs.

In a forthcoming concept note, we adapt the mathematics of the MPI to develop a multidimensional financial health index (MFHI) that attempts to quantify the financial well-being of Kenya’s adult population. The technical details are provided in the note, but in short, each individual in the 2016 FinAccess household survey is assigned a score according to reported behaviors or outcomes in nine indicators that map to the three dimensions of Financial health: ability to manage everyday finances, ability to cope with risk and ability to invest in livelihoods and future (Table 1).  To test whether similar conclusions can be drawn from other sources, data from the 2016 Intermedia Financial Inclusion Insights (FII) survey program was also used to create indices in the domains of managing day to day and coping with risk[2].

Table 1. The building blocks of the multidimensional financial health index for Kenya

financialhealthblog_table1

In this application the dimensions and indicators are weighted equally, so that the maximum contribution of each dimension to the overall index is 33.3 percent. If an individual satisfies criteria in all 9 of the component indicators[3], they receive a financial health score of 100%. If they only satisfy 4 of the component indicators, they receive a financial score of 40%. Individuals with a financial health score greater than 60% are considered “financially healthy”.[4] Using this approach we can calculate both the percentage of the adult population that is financially healthy overall, as well as the share of the adult population with evidence of abilities to manage day to day, cope with risk and invest in the future.

The results suggest that about 2 in 5 of Kenya’s adults have financial lives that simultaneously support everyday money management, risk management and investment, while 3 in 5 struggle in one or more of the dimensions of financial health (Figure 1). The data also suggest that Kenya’s adults have the greatest capacities in the dimension of managing day to day (63 percent of adults satisfied 2 of the 3 indicators in this dimension) and the fewest capacities in the dimension of investing in their livelihoods or future (47 percent of adults satisfied 2 of the 3 indicators in this dimension). Comparison with Intermedia’s 2016 FII survey, yield similar estimates for the share of adults able to manage day to day and cope with risk, which suggests that the findings aren’t idiosyncratic to the FinAccess survey instrument or sample.  

Figure 1. Financial health headcount ratios, by financial health dimension and data source

fsd 1

For lower income Kenyans, the ability to simultaneously allocate money for meeting the immediate needs of daily life and for longer term savings and investment, is severely constrained. Among the wealthiest quintile of adults who can manage liquidity for day to day needs, nearly 75 percent also show evidence of being able to cope with risk or invest. By comparison, among the poorest quintile of the population who can manage day to day, only 25 percent also show evidence of being able to cope with risk or invest. The financial health gap between the wealthiest and poorest is smallest in the ability to manage day to day dimension (80 vs 50 percent between the wealthiest and poorest quintile, respectively) and largest in the ability to invest dimension (71 vs. 27 percent between the wealthiest and poorest quintile, respectively) (Figure 2). Not surprisingly, the overall result is that people in the wealthiest quintile are more than four times as likely to be “financially healthy” than people in the poorest quintile.

Figure 2. Financial health headcount ratios, by financial health dimension,  relative asset wealth and data source finhealth_bywealth

Figure 3 shows a select number of financial health risk factors in the domains of debt-stress and negative customer experience with financial services derived from the 2016 FinAccess household survey.  Out of the population of borrowers, 50 percent report having at least one of the following signs of debt stress: a monthly debt obligation exceeding 50% of self reported income, having had to sell an asset to repay an outstanding loan, and having had to borrow more to repay an outstanding loan. The direction these indicators take over time is important, but certainly the high prevalence of borrowers reporting some degree of stress with debt is a cause of concern – and possibly explains the popular support for the interest rate cap that was passed into law in 2016.

Figure 3. Financial health risk factors by relative asset wealth

finrisks_bywealth

Negative experiences with financial service providers are most common among bank customers. Almost 1 in 3 bank account holders either reported having lost money or having faced unexpected charges in the prior year, compared to about 1 in 5 mobile money users and savings groups members and 1 in 10 mobile banking users and SACCO members. A greater policy focus on market conduct is beginning to emerge, but there is still plenty providers can do to improve price transparency, disclosure of terms and conditions and ultimately customer understanding of the ever-growing array of products that they are bringing to market[5].    

While the data can be parsed in a number of additional ways, overall the evidence suggests that the constraints that Kenyan’s face in their financial lives are least acute in managing day to day, more acute in the dimensions of being able to cope adequately with unexpected shocks and most acute in the domain of investing in their livelihoods, quality of life and future. In a way, this pattern mirrors developments in Kenya’s financial sector over the past 10 to 15 years: low-cost, no frills bank accounts, mobile money and more recently mobile-only low-value savings and credit products have risen rapidly and provided large segments of the population with additional tools to manage the ups and downs of daily financial life and leverage their social networks. While tools that enable people to manage day to day are relatively well developed, the penetration of health insurance, higher-value loans in agriculture or in the SME sector, investment products and other tools that enable individuals to be protected from the financial costs of major shocks or to more quickly take advantage of larger investment opportunities, has been much slower. This is only one explanatory narrative, it certainly isn’t the only possibility, but the data does raise the question of whether public and private actors should redouble efforts on finding ways to protect people from the costs of financial shocks and to help people raise larger investible sums of money that can support skill and livelihood development, greater occupational choice, security in old-age and improvements to quality of life that might help families save time and resources.

The objective of presenting the multidimensional financial health index here, is not to advance a definitive or final blueprint on how to measure population financial well-being – certainly this approach has limitations and weaknesses – but to raise one possibility and to contribute to the ongoing discussion on how measurement can more precisely gauge and guide efforts in financial inclusion to create shared prosperity.

 

Notes & references

[1] www.ophi.org.uk/multidimensional-poverty-index/background-to-the-mpi

[2] An insufficient number of questionnaire items that relate to the survey respondent’s ability to invest in productive assets precluded our ability to generate the headcount ratio for “ability to invest”

[3] It should be noted that the FinAccess questionnaire was not optimized for the purpose of measuring financial well-being, so we had to work within the constraint of the questionnaire items that are available. The general rule for the selection of indicators within each dimension was that they should neither be too weakly correlated (so as to suggest they do not conceptually belong together) nor too strongly correlated (so that each indicator contributes new information).

[4] This threshold is somewhat arbitrary. In this case 60% was selected as it increases the probability the financially healthy individuals will have capabilities in all three dimensions. 

[5] See for example Rafe Mazer and Kate McKee on consumer protection in digital credit:  http://www.cgap.org/sites/default/files/Focus-Note-Consumer-Protection-in-digital-Credit-Aug-2017.pdf  and Edoardo Totolo on the costs and transparency in banking products:  http://fsdkenya.org/publication/the-price-of-being-banked/

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