Data has a fundamental role in establishing a common understanding of the current state of financial inclusion. It can be used by regulators, policymakers, and financial services providers. Data is present in all policymaking processes: diagnosis of the state of financial inclusion, designing appropriate policies, setting financial inclusion targets, monitoring and evaluation which provide a feedback loop to adjust targets and initiate policy reforms. The main stages for measuring financial inclusion are:
1) Country specific definition of financial inclusion
2) Identification of data needs and data gaps
3) Data gathering
4) Data analysis and dissemination
Country-level data on financial inclusion inform the national policymaking processes and are more detailed than global-level data, e.g. due to disaggregation by administrative units. Global-level data on financial inclusion are mostly used for country-to-country comparisons as well as for assessing trends on financial access around the world. Harmonization of definitions and standardization of data collection methodologies are necessary to generate useful global-level data and benchmarks.
There are numerous freely available international databases relevant for financial inclusion. The most comprehensive global supply-side data source is the Financial Access Survey (FAS) of the IMF. One of the most prominent demand-side data sources is the Global Findex of the World Bank. Several initiatives aim to reach a consensus on standardising basic indicators of financial inclusion, notably the Global Partnership for Financial Inclusion (GPFI), the OECD SME indicators and the Financial Inclusion Data Working Group of AFI. The main target of these initiatives is to offer a benchmark of common and basic indicators to be considered for measuring financial inclusion and to encourage countries to supplement the basic indicators with relevant indicators for the country specific context.
Once the definition of financial inclusion is clear, it is easier to determine what kind of data is needed to measure the current state of financial inclusion, track changes over time and impacts of inclusion. Financial inclusion is a multidimensional concept. Each country is unique and should determine its own definition given the specific characteristics of the country and its financial sector. Although there is no common definition for financial inclusion there is a consensus on the basic dimensions that must be considered for measuring financial inclusion: financial inclusion indicators measure various aspects of access, usage, quality and impact. In addition, they consider specific target groups, especially SMEs, women and other vulnerable groups.
The proper application of good data is paramount to promoting evidence-based financial inclusion policy. Financial inclusion measurement is more than just numbers and statistics. FID is ultimately about people and how best to understand and communicate their financial needs and design appropriate products and services.
There is an increasing availability of high-quality supply and demand-side data within AFI members. The AFI data portal shows that over 40% of AFI members have undertaken at least one national demand-side survey within the last 3 years. These data, combined with the application of new innovative analytical and diagnostic tools and techniques has enabled policymakers and regulators to gain insights to the financial needs and behaviour of previously unserved populations, and develop targeted policy solutions.
The proper application of good data is paramount to promoting evidence-based financial inclusion policies. FID policies are not an end in itself but tools designed to allow policymakers and regulators take better informed decision-making in the different policy dimensions related to financial inclusion.
Parallel global trends include: national data frameworks and financial inclusion indicators and indices; a proper data segmentation including sex-disaggregated data, activity, age and location; measuring quality and social impact; innovative measurement tools and frameworks including the use of RegTech and Big Data; Regulatory Risk Assessments; Data reporting and dissemination; Monitoring and Evaluation principles and tools.
Fundamental and emerging topics under financial inclusion data (FID) are explored in-depth through AFI’s Financial Inclusion Data Working Group (FIDWG).
The collection and analysis of sex-disaggregated data is essential to bridging the financial inclusion gender gap, as it can both inform evidence-based financial inclusion policymaking and track the effectiveness of efforts to address barriers faced by women. Increasingly members are segmenting data to understand key aspects related to gender-led policies, and disseminate indicators to inform regulators, policymakers, and market implementors about important gaps financially impacting women in different contexts and the identify actions to reduce them.
Member institutions are increasingly making Maya Declaration commitments that fall under FID’s mandate. As of 2019, 111 commitments have been set that aim to improve the measurements and indicators for assessing financial inclusion. Form these 45 percent have already been completed.
|PRIMARY THEMATIC AREA||2012||2013||2014||2015||2016||2017||2018||2019||2020|
Financial Inclusion Data
|Maya Declaration Targets||20||40||48||49||64||79||86||111||106|
AFI’s Financial Inclusion Data Working Group (FIDWG)
A platform dedicated to promoting and sharing practical knowledge and recommendations on financial inclusion measurements including core set indicators, measurement methodologies, policy models and other good practices by AFI member institutions.
FIDWG aims to develop a common framework for measuring financial inclusion and sharing lessons learned on topics such as target setting, quantitative and qualitative measurement methodologies, and data analysis and dissemination to better inform policymaking and changes in regulation. Members actively promote the use and adoption of a framework within the AFI network at the international level.
View the FinNeeds toolkit, a measurement framework by insight2impact. This toolkit outlines the FinNeeds indicators to track and discusses the data sources and measurement approaches relevant for each element, as well as how to analyze the data for policy-ready insights.
Alex Ochan, Bank of Uganda
Akata Taito, Reserve Bank of Fiji
Co Chair & Gender Focal Point
Dr Settor Amediku, Bank of Ghana
Monitoring and Evaluation Subgroup (jointly with FISPLG):
Policymakers need to ensure the limited resources that are available to address financial exclusion are spent on the interventions likely to have the greatest impact. The goal of an NFIS must be achieved within a specific time frame, and setting priorities involves the “selection of policies, strategic measures and target groups to which relatively high importance needs to be attached in the effort to achieve the goal(s) articulated in the strategy”.23 A proper monitoring and evaluation strategy is central to demonstrate the expected impact of an NFIS.
Inclusive Green Finance Subgroup:
An increasing number of AFI members voiced interest in scaling up peer learning on ways to develop and implement financial inclusion policies that also have positive environmental outcomes. This momentum culminated in September 2017 with the launch of the Sharm El Sheikh Accord on Financial Inclusion, Climate Change and Green Finance, endorsed by an overwhelming 94% of the AFI membership. The Accord commits AFI members to work together and with partners to identify, understand and implement financial inclusion policy solutions that also have positive outcomes for the environment, focusing on communities that are most vulnerable to climate change.24 As a preliminary step, FIDWG members agreed to work on an effort to define taxonomies: what counts as ‘inclusive green’ finance, how do we measure its impact, what is the role of climate data in financial regulation and policy making.
SMEF Data Subgroup (jointly with SMEFWG):
The Alliance for Financial Inclusion is committed to supporting the development of MSME access to finance, and continuing with the approach of evidence-based policy formulation within AFI through more robust data collection practices leading for more informed and impactful policies and policy interventions with a strong gender inclusive finance approach, following the 2010 Sasana Accord related to evince-based policies, following the 2015 Maputo Accord on SME support and the 2016 Denarau Action Plan to close the gender gap in financial inclusion.
RegTech Taskforce (jointly with DFSWG and GSPWG):
Any FinTech/RegTech-based approach to financial inclusion must recognize that technology is not perfect and can have unanticipated consequences. Until technologies are sufficiently advanced to police the effects of technologies, providers will need to test the outcomes of algorithmic interpretation of data continuously and retroactively. Second, technology may do exactly what developers anticipate, but the issue may be with the developers themselves. Financial history is replete with fraud and every new technology will be abused by some individuals. Third, technology is always accelerating and creating space for groups of new entrants, which makes the role of the regulator ever more challenging. In many cases, this will require regulators to respond using technology. RegTech includes automation and data-driven analysis of internal control systems (compliance, risk management, audit) and internal and external reporting. FinTech also raises broader issues of how to approach the regulation of innovation.
Sex-Disaggregated Data Subgroup:
After the 2014 Findex28 was released several initiatives for reducing the gender gap emerged increasing the demand for sex-disaggregated information. The 2017 Findex revealed an unchanged gender gap of 7 percentage points. All Global Findex indicators can be disaggregated by age, by income. However, the main issue with Global Findex is its lack of detail which is necessary for making informed policy decisions on country-level. Some regulators have made efforts of including sex-disaggregated questions in demand-side surveys or gathering relevant data from national institutions. But it becomes a challenge when the regulators don’t have the will to invest in collecting these data, which are more needed on the supply-side (the demand-side already include this component).
|Events||1st: Kuala Lumpur, Malaysia|
2nd: Bali, Indonesia
|3th: Lima, Peru|
4th: Riviera Maya, Mexico
|5th: Livingstone, Zambia|
6th: Cape Town, South Africa
|7th: Manila, Philippines|
8th: Kuala Lumpur, Malaysia
|9th: Casablanca, Morocco|
10th: Port of Spain, Trinidad & Tobago
|11th: Kuala Lumpur, Malaysia|
12th: Maputo, Mozambique
|13th: San Salvador, El Savador|
14th: Nadi, Fiji
|15th: Dushanbe, Tajikistan|
16th: Sharm El Sheikh, Egypt
|17th: Merida, Mexico|
18th: Sochi, Russia
|19th: Cairo, Egypt|
20th: Kigali, Rwanda
|21th: Virtual Meeting|
22th: Virtual Meeting
|23th: Virtual Meeting|
24th: Virtual Meeting
In this webinar, the speakers are highlighting key steps in designing and developing a demand-side survey: how to identify the key objectives, streamline the indicators/questions to be defined and included in questionnaires, the validation of the structure and language of the instruments, and how should the end-resulted be used for analysis and effective policy decision-making.
Financial inclusion demand-side data and specifically face-to-face demand-side surveys are considered one of the key tools to measure access, usage, and quality of services from a user’s perspective. These tools are flexible instruments that allow to measure specific characteristics, perceptions, and preferences from the financial services and products (FSP) user’s perspective.
They can capture critical information from partially and unserved markets. More recently, additional policy needs have been identified to be measured by these instruments: access, usage, quality of services, but also Micro and SME finance aspects, individual financial needs, the gender angle of financial inclusion, resilience and adaptation processes in climate emergency responses, and additional nuances linked to digital financial services and financial technology.
In this webinar, the speakers are highlighting the main objectives, characteristics, advantages, and limitations of demand-side surveys. The webinar explained how policymakers can use surveys to inform their policies while taking advantage of other measurement tools. The tools are both from the supply and the demand side and complement the overview of the financial inclusion landscape for timely decision-making.
Financial inclusion demand-side data and specifically face-to-face demand-side surveys are considered one of the key tools to measure access, usage, and quality of services from a user’s perspective. These tools are flexible instruments that allow measuring specific characteristics, perceptions, and preferences from the financial services and products (FSP) user’s perspective. They can capture critical information from partially and unserved markets. More recently, additional policy needs have been identified to be measured by these instruments: access, usage, quality of services, but also Micro and SME finance aspects, individual financial needs, the gender angle of financial inclusion, resilience and adaptation processes in climate emergency responses, and additional nuances linked to digital financial services and financial technology.