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FinNeeds

A new understanding of financial services usage

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Framework components and key indicators

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Download the FinNeeds Indicators here.

Element

Indicators

Needs
For each of transfer of value, liquidity, resilience and meeting goals
  • Proportion of adults who experienced [specific use case]
Disaggregated by sex, socio-economic status or geographic location as relevant

Note: liquidity is a single use case (need)
Device portfolio to meet needs

For each need, or per specific use case as relevant:

  • Proportion of adults using [a specific financial device] to meet each need
  • Proportion of adults using at least one formal financial service to meet their needs
Disaggregated by sex, socio-economic status or geographic location as relevant
Usage

Usage intensity indicators defined as relevant per use case or need category:

  • Proportion of adults who use digital financial services to transfer value on a weekly, monthly or infrequent basis
  • Duration of client relationship
  • Monetary value of transactions, balances, loan amounts or sums assured
The three usage indicators can be split into typical usage pattern in cash or on informal or social devices
Drivers
  • Relative strength of functional versus relational (refer to the drivers section for detailed explanation) self-reported reasons for device choice.
  • Statistical significance of personal characteristics such as income/socio-economic status, gender, age or education in explaining usage intensity
Outcomes
  • Proportion of adults who experienced liquidity distress in the last year
  • Proportion of people who experienced a shock in the last year and have not yet recovered
For both indicators overlay device uptake portfolio between different distress outcome categories to infer insights on relevance of device choice to outcomes.




Needs

The needs measurement framework is at the heart of the FinNeeds approach and it focuses on use cases as the starting point.

Each use case can be classified into one of the four categories of financial needs:

  • Transfer of value. Most people, as part of their daily lives, need to transfer money or digital value from one person to another. This could be to make a purchase, receive income, pay a bill or send money to friends or family. Transfer of value is a core functional need in the economy. It is also a prerequisite for accessing savings, credit and insurance and, in some way or another, comes into play in each of the other four categories of financial needs. A financial service meets this need by moving value from one person to another in a manner that is safe and creates certainty (See our drivers note for a detailed outline of all the factors that providers need to consider). Outside of formal financial services, value can be transferred in cash or in kind.
  • Liquidity This need refers to the need to meet expenses in each income cycle. It is essential for survival and to maintain productive relationships. Financial services enable liquidity by allowing a person to accumulate a pool of resources that are available on demand, or by providing the option to borrow funds on a short-term, flexible basis.
  • Resilience This is the ability to deal with unexpected shocks that have a financial impact. Thus, the need to build and maintain resilience goes beyond short-term liquidity management to the need to avoid falling into poverty or reducing living standards due to the impact of risk events. Financial services can improve people’s welfare by helping them prepare for, manage and recover from unexpected financial shocks.
  • Meeting goals. This is the need to meet foreseeable life objectives or life stage or social obligations, for example: maintaining health and education; providing security, for example in old age; taking productive risks; accumulating assets; and providing for lifecycle events such as weddings and births. These use cases all require accumulating larger amounts of money than the person or household can fund from a single income cycle, hence financial services (savings, credit or payments) serve a facilitating function in meeting goals.

Each of these financial needs is made up of a combination of use cases. People exhibit a specific use case which is then classified within a particular need “bucket”.

Needs measurement framework at a glance

  • Indicator: For each of transfer of value, liquidity, resilience and meeting goals:
    • Proportion of adults who experienced [specific use case]
    • Disaggregated by sex, socio-economic status or geographic location as relevant

Example outputs from our pilot studies

The diagram below shows examples of % of adults in the sample who expressed specific transfer of value, resilience and goals use cases (Over the past 12 month period) in one of our pilot studies:

Transfer of value
Sending Remittances
19%
Receiving income
66%
Making payments
99%
Resilience
Coping with a big accident or injury
7%
Coping with theft, damage, loss or breaking of an important expensive item e.g. a car, television, tractor, machine
12%
Dealing with loss of a family member or someone closely related
13%
Dealing with loss of income from you or the main income earner
14%
Coping with a natural disaster or other environmental issues e.g draughts, floods, earthquakes etc
16%
Dealing with a big sickness or health problem
27%
Personal Goals
Buying a vehicle
8%
Paying for vacations or an important holiday/big life event like a wedding sweet 16 or birth of child
10%
Buying land or house or building for renting out
10%
Saving for retirement for the future or to leave a heritage to your family
16%
Buying big things for personal use. Like electronic devices house contents TV phone furniture
17%
Paying off debts or loans in a lump sum
24%
Buying land or house to live in
24%
Paying for your or your children's education
36%
Business Goals
Buying land or house or building for commercial use or farming
13%
Buying equipment tools animals over-and-above your regular operational farming costs
15%
Starting or buying into a business or make investments to grow your current business
40%


Devices used to meet needs

Once we know what people’s use cases are and how these classify across the four needs, the next step is to understand how people meet their needs and what role formal financial services play compared to informal or social means of meeting needs. There are various ways people can meet their financial needs or use cases, which are known as the “financial devices” used.

Many financial inclusion surveys already track the devices people have, but the FinNeeds approach tracks what devices people use when responding to each use case and need.

What is a financial device?

A financial device is any physical, social or electronic mechanism that stores, accumulates, distributes or transfers value, and can be used to meet a financial need. Financial devices is a broader concept than financial services, it is what a person makes use of to meet a financial need. For example, cash at home or savings in gold or other assets would be a “personal device”, while assistance from family and friends would be a “social device”.

Financial devices can be classified in terms of provision or products:

  • Provision dimension: Personal devices include cash at home and liquid assets, social devices include borrowing or assistance from friends and family. Formal devices are services provided by a formal financial institution, while informal devices are provided by third party service providers not licensed as financial institutions. People may use a combination of financial devices, depending on the use case.
  • Product dimension: Financial product categories include savings, payments, credit and insurance, as well as unreciprocated assistance.
Download the FinNeeds Measurement Framework note here.

Devices-towards-needs measurement framework at a glance indicator:

  • Proportion of adults using [a specific financial device] to meet each need.
  • Proportion of adults using at least one formal financial service to meet their needs
  • Example outputs from our pilot studies

The chart below shows the range of financial devices used to address the liquidity need in one of our pilot studies.

FinNeeds Indicator
% of adults with liquidity distress who do not use formal financial services to resolve it
FinNeeds indicator unpacked: how do people manage liquidity distress?
Formal
Informal
Social
Personal
 
 
32%
 
Assistance from family and friends
 
 
9%
25%
Used savings
(34%)
7%
10%
25%
 
Used credit
(42%)
FinNeeds insight: Formal devices a last port of call when cash strapped, preference for social assistance, credit

Usage

We know from conventional financial inclusion measurement frameworks what financial services or devices people have, but often there is not much detail on how people engage with these devices and how usage patterns differ between different use cases and types of devices. The usage measurement framework explores usage-towards-needs according to four indicators, the specifics of which will differ per use case and device:

  • Frequency: How often a device is used or the number of transactions within a defined period. For example, the number of payment transactions, deposits or withdrawals in one month.
  • Recency: When last a financial device was used. For example, the number of days since a remittance was sent or received, or a savings deposit or draw-down was made.
  • Monetary value: The amount of money involved in a specific financial action or the balance (stock) of money involved. For example, for credit, the value of loan instalments or outstanding loan balance; for remittances or payments, the value of money sent or received; for savings, the value of money deposited, drawn down or accumulated as savings over time; for insurance, the value of an insurance premium or sum assured.
  • Duration: The length of time a person has been using a financial device. For example, how long a person has been a savings or loan or bank or insurance client, and whether membership or policy ownership has been renewed.

Usage is most objectively gauged via financial service provider transaction data. For example, tracking account activity, mobile money or card transactions. Consumer surveys or other demand-side data cannot give as granular or objective a picture of usage, but they are currently the only way to gauge usage patterns of informal and social devices.

Download the Drivers Measurement Framework note here.

Usage measurement framework at a glance

Indicators: Usage intensity indicators defined as relevant per use case or need category:

  • Proportion of adults who use digital financial services to transfer value on a weekly, monthly or infrequent basis
  • Duration of client relationship
  • Monetary value of transactions, balances, loan amounts or sums assured
The three usage indicators can be split into typical usage pattern in cash or on informal or social devices

Example outputs from our pilot studies

The table below illustrates usage intensity clusters identified for point-of-sale customers in one of our pilot studies:

SegmentSEG 1 SegmentSEG 2 SegmentSEG 3 SegmentSEG 4 SegmentSEG 5 SegmentSEG 6
Average number of transactions per month since customer first seen
Average number of transactions per month since customer first seen 4.5 4 5.5 23 60 120
Average value per transaction
Average value per transaction N 7,300
$20.28
N 9,200
$25.56
N 28,000
$77.78
N 9,500
$26.39
N 11,400
$31.67
N 11,600
$32.22
Median spend per month since customer first seen
Median spend per month since customer first seen N 24,000
$66.67
N 25,000
$69.44
N 100,000
$277.78
N 210,000
$583.33
N 690,000
$1,916.67
N 1,500,000
$4,166.67
Average unique MCC codes used
Average unique MCC codes used 15 10 20 50 80 100
Proportion of total customers in segment
Proportion of total customers in segment 39% 13% 10% 22% 13% 4%
Proportion of total spend contributed by segment
Proportion of total spend contributed by segment 5% 2% 7% 20% 42% 24%

To derive this table, we applied statistical clustering techniques to cluster digital payment users into different “intensity of usage” groups. Segment 1 consists of low users of point-of-sale devices across the frequency and monetary value indicators. This is the largest segment, at 39% of the clients. On average people in Segment 1 have four transactions per month with an average monthly expenditure of NGN 24,000 at point-of-sale machines. In contrast, Segment 6 has high usage, with 120 average monthly transactions and an average spend of NGN1.5 million at point-of-sale machines. Segment 6 consists of only 4% of the sampled clients. The different segments give a usage measure which can be used to better understand how people interact with a device across multiple dimensions.

The next step is to compare and contrast the profiles of different usage clusters to inform strategy and policy interventions to increase usage. For example, are high usage customers likely to be more educated and higher-income than low users? Is there a relationship between geographic location (close or far from access points) and usage? Or is there some other element, such as compulsion or having a specific other financial service, that explains intensity of use? And how does intensity of use differ across use cases?

Drivers

The drivers of usage conceptual framework seeks to explain why people choose the devices that they do to meet their needs. This framework draws on human decision-making models, augmented by financial-inclusion-specific research, to consider how individuals make decisions about the use of financial services. Understanding these drivers can help policymakers to address key policy problems such as high use of informal financial services. Financial service providers can also use this framework to identify which factors to consider when trying to drive use of specific financial products. Four broad classes of drivers are defined:

  • Functional drivers: The extent to which a financial product helps to fulfil a use case – that is, whether it provides the user with functional value, which, in itself, becomes a driver of sustained usage.
  • Relational drivers: Decision-making considerations that are associated with the way in which consumers relate or connect to a financial provider or device. These are not just based on a functional cost-benefit analysis but are often influenced by factors that appeal to emotions when individuals interact with financial services. These include respect, trust and a sense of belonging.
  • Behavioural drivers: Non-cognitive factors that influence how individuals reach a decision. These are in the form of biases and heuristics (or mental shortcuts) that individuals employ during decision making. For example, it is typical for financial service users to exhibit a status quo bias – consumers tend to stick with their existing devices even when there are better alternatives because they feel that they are invested in the product they are currently using.
  • Contextual drivers:Pre-existing conditions (such as gender or societal context) that influence uptake and usage of financial services but over which the individual, policymaker or financial service provider will have no or very little control.

The drivers that matter most will differ across use cases and will be based on factors such as local context, device type, provider type and consumer characteristics.

Download Drivers Measurement Framework note.

Drivers measurement framework at a glance

Indicators:
  • Relative strength of functional versus relational self-reported reasons for device choice
  • Statistical significance of personal characteristics such as income/socio-economic status, gender, age or education in explaining usage intensity

Example outputs from our pilot studies:

One of our pilot demand-side surveys asked people to rate the reasons for choosing each device in their portfolio, based on a list of reasons such as “it’s convenient”, “I’m comfortable with it”, “others like me use it”, etc. These reasons were designed to be classified into two categories: functional reasons (benefits, convenience, cost considerations) and relational reasons (trust, sense of belonging, comfort). The results suggested that respondents tended to use:

  • Formal services and cash for functional reasons
  • Informal and social devices for relational reasons (trust and sense of belonging)

All socioeconomic classes skew towards relational factors, except the very top two high-net worth categories, who emphasise functional benefits.

In a separate statistical modelling exercise of the determinants of usage intensity, conducted on bank transaction data as part of the same study, it was found, not unexpectedly, that income is by far the largest driver of usage, followed by education and relationship status. The demand-side survey responses, however, suggest that more may be at play than just demographics in explaining uptake and usage of different types of financial devices.

Outcomes

The FinNeeds framework seeks to understand the mix of financial devices that people have, as well as the way in which they engage with their financial devices (usage patterns), towards fulfilling their financial needs. Outcomes of use refer to the extent to which financial services enable people to meet their needs.

The outcome indicators aim to establish the percentage of people meeting each need. For example, the percentage who classify into different degrees of resilience, or the percentage of people maintaining liquidity. We then overlay the usage measurement framework to infer insights on the overall “success” of financial services in achieving positive need outcomes. For example, are those who have formal insurance more likely to be resilient than those who are not insured? Or are those with formal credit able to meet the same goal faster than those without? The answers to these questions have implications from a policy perspective. It can help to inform (a) an assessment of financial inclusion and financial sector welfare impact and (b) where the primary challenges are and what can be done to change the situation.

As outcomes are fundamentally different across the four financial needs, separate outcomes measurement frameworks must be created for each of the four needs, or even at a specific use case level. For example, measuring whether one is resilient (is able to recover from unexpected financial shocks in a timely manner) is different in scope from measuring whether a person is able to meet his or her goals (is able to save a large amount of money to pay for an expected expense). So far, i2i has developed initial indicators for liquidity and resilience outcomes. Further refinement is needed.

Outcomes measurement framework at a glance

  • Indicators
    • Proportion of adults who experienced liquidity distress in the last year
      • Proportion of adults who experienced a shock in the last year and have not yet recovered
  • Overlay device uptake portfolio between different distress outcome categories to infer insights on relevance of device choice to outcomes.
  • Example outputs from our pilot studies

The chart below gives an indication of the percentage of the sample population in one of our pilot studies classified into one of three liquidity outcome categories: Those who experienced no instances of illiquidity (being unable to meet expenses in a regular income cycle) over the past 12 months were classified as having experienced “no distress”. Those who were unable to maintain liquidity once in the past year were classified as having experienced “some distress” and the rest were classified as being under “severe liquidity distress”. The diagram also shows which types of financial devices those with distress took up to deal with the shortfall experienced. For the no distress category, the bars denote overall device uptake. The blue line indicates the percentage of adults in the sample classifying in each category:

100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
35%
14%
52%
No Distress
48%
29%
69%
Some Distress
31%
29%
80%
Severe Distress
Formal
Informal
Social/Personal
% of adults
39% 14% 48%

By comparing device uptake across the three segments, it was interesting to see that those with distress are relatively high credit users but also, counterintuitively, have higher incomes than those without distress. This suggests that the middle class is overextended. Also telling is that those with distress are more likely to turn to social devices than those without, a tendency that increases as the level of distress increases. This suggests that, even if people have formal devices, it is not their first port of call when they are struggling to balance the books and may therefore not serve the intended liquidity outcome-of-use purpose.

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