Financial exclusion

The debate on financial exclusion has typically taken place between financial industry participants, regulators, government agencies and consumers, whilst limited empirical academic research has been carried out within the remit of consumer policy, money management or in cross-national studies (Collard et al., Reference Collard, Kempson and Whyley2001; Devlin, Reference Devlin2005; Collard, Reference Collard2007; Rowlingson and McKay, Reference Rowlingson and McKay2017; Grohmann et al., Reference Grohmann, Klühs and Menkhoff2018). Prabhakar (Reference Prabhakar2019) notes that applied research on this subject rarely refers to theoretical social policy literature, while scholarly work has developed in isolation from the practical implications of the different facets of financial exclusion.

While a broad definition of financial exclusion refers to the lack of citizens’ participation with the financial system, empirical analyses need to recognise its different practical dimensions, linked to one another but undeniably distinctive – specifically, managing daily financial needs, using sustainable borrowing, smoothing income over time through savings and insurance. Short-term money management relates to accessing current and basic bank accounts to perform daily financial activities. Long-term planning refers to precautionary savings and access to insurance products to mitigate losses of income owing to retirement, ill-health or changes in employment and protect against negative unforeseen financial events. Sustainable borrowing refers to efficient debt management and avoiding problem debt (Rowlingson and McKay, Reference Rowlingson and McKay2017).

Undeniably, the definition above implies individuals’ engagement with financial services; the government’s drive towards greater financial inclusion has been the subject of criticism by some, notably Berry (Reference Berry2015, Reference Berry2016) and Marron (Reference Marron2013, Reference Marron2014), who perceive it to be a way of offsetting the effects of cuts to welfare systems by investing individuals with the responsibility for their own financial wellbeing. In the move towards ‘financialization of everyday life’ promoted by the shift towards neoliberal policies, individuals are encouraged to be active subjects in financial markets, often without adequate knowledge or information and so increasing their financial risk and vulnerability (Atkinson et al., Reference Atkinson, McKay, Collard and Kempson2007; Sherraden, Reference Sherraden, Birkenmaier, Sherraden and Curley2013; van der Zwan, Reference van der Zwan2014; Rowlingson et al., Reference Rowlingson, Appleyard and Gardner2016). Tackling financial exclusion may therefore be perceived to serve the purpose of increasing the influence of market logic on society with consequent proliferation of complex financial instruments unless effective regulation and independent financial advice are in place (Gloukoviezoff, Reference Gloukoviezoff2011).

However, it can be maintained that addressing financial exclusion would enable vulnerable groups to reduce the costs and stigmas associated with it, which often contribute to a wider sense of social exclusion (Warburton et al., Reference Warburton, Ng and Shardlow2013). An early UK study by Collard et al. (Reference Collard, Kempson and Whyley2001) highlights that those more likely to be excluded from financial services are often on low incomes, living alone and from ethnic minority groups. Poverty and deprivation are particularly relevant in preventing access to basic financial products (Bradshaw and Finch, Reference Bradshaw and Finch2003), precluding the most basic level of financial inclusion and social participation (Pantazis et al., Reference Pantazis, Gordon and Levitas2006).

Evidence on ethnicity

The importance of better understanding ethnic minorities’ financial circumstances is twofold. Firstly, ethnic groups represent substantial sections of the UK population; Nomis (ONS) reported that Asian groups constitute 6.23 per cent of the population, Black groups represent 3 per cent, while Chinese and ‘others’ represent 0.7 and 0.9 per cent respectivelyFootnote ¹ . Secondly, the persistence of significant gaps in financial wellbeing between ethnic minorities and White British has been reported by many valuable studies (see Ginn and Arber, Reference Ginn and Arber2001; Khan, Reference Khan2010a; Ginn and MacIntyre, Reference Ginn and MacIntyre2013; Gough and Adami, Reference Gough and Adami2013; Vlachantoni et al., Reference Vlachantoni, Feng, Evandrou and Falkingham2017). The disadvantages in terms of earnings, employment status and continuity experienced by some ethnicities are well documented – however, the considerable diversity within the ethnic population is worth noting. Pakistani, Bangladeshi and Black individuals are more likely to experience precarious employment conditions, hold lower levels of educational qualifications and have family values that may not prioritise paid work (Vlachantoni et al., Reference Vlachantoni, Feng, Evandrou and Falkingham2015). Heterogeneity between groups was confirmed by a recent report for the House of Commons (2020), showing persistent income inequality amongst ethnic minorities. Between 2016 and 2018, the median weekly household income for Indian respondents was above that of White British (£538 and £518 respectively), while for Pakistani, Bangladeshi, and Black groups it remained stubbornly low (£334, £365 and £408 respectively).

Concerns about the levels of financial exclusion experienced by some ethnicities were expressed by Khan in his notable studies published in 2008 and 2010. Khan’s key findings show that financial exclusion amongst ethnic minorities is the result of disproportionate numbers of individuals below the poverty line (including in-work poverty) compared to the rest of the population and a persistent disadvantage in the labour market even for qualified workforce. Interestingly, lack of trust in financial institutions and scepticism towards mainstream banking practices are also key in low financial engagement (Pensions Policy Institute, 2016; Salignac et al., Reference Salignac, Muir and Wong2016). Khan highlights the importance of impartial money advice services and draws attention to the provision of complex financial products, often unsuitable for low-income households.

Crucially, there is little up-to date evidence on ethnicity and financial exclusion. This study uses the Family Resources Survey, a most comprehensive source of socio-economic data, to gather key financial and demographic information in a sample that reflects the composition of the UK’s adult population. The article evaluates the extent of financial exclusion by using multiple logit regressions on its distinctive dimensions.

Data and methodology

The Family Resources Survey

Every year since 1992, on average, over 20,000 households take part in the Family Resources Survey (FRS). The survey is conducted by a consortium including the Office for National Statistics and the National Centre for Social Research on behalf of the Department for Work and Pensions (DWP) and it provides information about living standards of those aged sixteen and above, resident in the UK. The FRS is used to assess the effectiveness of social security reforms and monitor the impact of policy changes. Information is available on a range of topics related also, but not exclusively, to individuals and households’ demographic traits and financial circumstances. The Survey provides an extensive, nationally representative dataset that uses a two-stage stratified random sample drawn from the small users’ Postcode Address File (PAF). The sample size has varied over the years, with just over 19,000 households interviewed in 2018/19 (DWP, 2020 Footnote ² ).

The FRS is the most suitable large-scale dataset available for this study, providing extensive, financial, socio-economic information and detailed demographic data. The empirical analysis refers to data collected on a total of 13,477 respondents in 2018-19, of which 88 per cent are of White British origins, 2.5 per cent are Asian-Indian, 1.8 per cent Asian-Pakistani, 0.7 per cent of Bangladeshi origins, 0.60 per cent are Chinese, 2.6 per cent are Black/African/Caribbean/Black British while 3.8 per cent belong to other ethnicities. These values are in line with those provided by the Office for National Statistics’ Nomis (Office for National Statistics, 2014), which combines data collected in the censuses for England and Wales, Northern Ireland, and Scotland. The final sample includes over 1,600 individuals from ethnic minorities, beside the reference group of White British respondents. Those aged over State Pension Age of sixty-five and anyone in receipt of a pension were not included to enable a clearer assessment of retirement planning. The sample obtained can be considered adequately large when compared to similar studies (see Warren, Reference Warren2015; Vlachantoni et al., Reference Vlachantoni, Feng, Evandrou and Falkingham2017) and with sufficient cell counts to allow for the empirical analysis. Table 1 shows the summary of data by ethnic group across the four variables used in the study.

Table 1 Summary of sample by ethnicity

Results on ethnicity

A preliminary analysis is performed on ethnic groups to establish whether there are any observable differences within each area of financial exclusion. Figures 1 to 4 show percentages of those holding bank/building society accounts; those with problem debts; members of private pension schemes, holders of home contents insurance.

Figure 1. Bank accounts

Source. Family Resources Survey 2018/19, Values as percentages.

Figure 1 indicates that most respondents hold current accounts – however, 6 and 9 per cent of those of Pakistani and Indian origins respectively do not hold any account at all, compared to 3 per cent of White British respondents. The lack of access to basic financial products is likely to affect the efficient management of short-term financial transactions, making every-day money management more expensive, reducing the opportunities to gain regular, stable employment, and receive benefits. These initial findings are in line with Khan’s (Reference Khan2008) and can be attributed to factors including the reluctance to provide identity documents necessary to open bank accounts, language barriers and a general mistrust of financial institutions.

Figure 2 shows that other Asian, Chinese, and Bangladeshi respondents exhibit the highest percentages of finding debt repayments a heavy burden (44, 33 and 30 per cent respectively), while 47 and 46 per cent of Mixed Ethnic and Black respondents define debt as a slight burden. The numbers point to greater difficulties in debt management amongst some ethnic minorities. Financial knowledge and engagement but also, transparency, regulations and market structures can affect the costs of debt and the associated levels of financial vulnerability (Kus, Reference Kus2015; Lusardi and Tufano, Reference Lusardi and Tufano2015; Ottaviani and Vandone, Reference Ottaviani and Vandone2018). Crucially, individuals from ethnic backgrounds are more likely to be low-income borrowers (Khan, Reference Khan2008), which increases their exposure to poverty premiums such as higher loan fees and interest rates, due to restricted access to credit.

Figure 2. Loan repayments

Source. Family Resources Survey 2018/19, Values as percentages.

Figure 3 shows participation in employers’ pension schemes and individual personal schemes. Participation to employers’ schemes is high, due to a significant increase in membership following the introduction of auto-enrolment and the implementation of the National Employment Savings Trust (NEST) – however, there is pronounced variation amongst ethnic groups, where participation varies between 79 and 92 per cent for Bangladeshi and Chinese respondents respectively. Membership to personal pensions is extremely low for Pakistani, Black, and Bangladeshi groups (with 1, 2 and 4 per cent respectively) compared to White British (11 per cent). The findings point to an ethnicity gap in traditional retirement planning and are in line with existing evidence on the persistence of financial disadvantage amongst some minorities, likely to originate in the workplace and exacerbating in retirement (Ginn and Arber, Reference Ginn and Arber2000, Reference Ginn and Arber2001; Vlachantoni et al., Reference Vlachantoni, Feng, Evandrou and Falkingham2017). Low levels of retirement savings amongst minority ethnic groups have often been attributed to persistently higher rates of part-time work, self-employment, and unemployment than the rest of the population – however, scepticism towards financial providers may be a contributing factor to the extremely low take-up of personal pensions (Khan, Reference Khan2010b; Gough and Adami, Reference Gough and Adami2013).

Figure 3. Pension scheme participation

Source. Family Resources Survey 2018/19. Values as percentages. Notes. Employers’ Pension Scheme participation is defined as membership to one or more of the following: ‘Any employer-sponsored pension’, ‘Occupational pension’; while Individual Personal Pension participation is defined as holding one or more of the following: ‘Group personal pension’, ‘Group stakeholder pension’, ‘Personal pension’ or ‘Stakeholder pension’

Figure 4 shows that the levels of those holding insurance amongst ethnic minorities are comparable to the White British population’s, with the only exception of Chinese respondents (only 51 per cent hold home insurance). Interestingly, 24 per cent of Chinese respondents stated that they did not want or need home insurance while 16 per cent declared not being able to afford it. The purchase of home insurance products is positively related to the levels of risk aversion and usually associated to the value of one’s possessions, so to those in low incomes it may seem an unnecessary expense (Rowlingson and McKay, Reference Rowlingson and McKay2017). It is noteworthy that one in five amongst Indian, Bangladeshi, and Pakistani respondents affirms ‘not to be able to afford insurance’.

Figure 4. Home contents insurance

Source. Family Resources Survey 2018/19. Values as percentages.

Whilst the preliminary breakdown of the data is valuable to identify key traits amongst ethnic respondents, the analysis of the results from the logistic regressions presented in Tables 2 to 5 is essential to gain a deeper understanding of the factors associated with the probability of disadvantage within each area of financial exclusion. For this purpose, four variables were separately regressed against relevant socio-economic and demographic factors, with focus on ethnicity. The significance of the regression results provides valuable information on the financial difficulties experienced by sections of the populationFootnote ⁴ .

Table 2 Regression results on Not holding a bank account, based on a sample of 13,477 respondents

Notes. Ref: Reference Category

Source. Family Resources Survey (2018/2019), author’s calculations

Significance levels: * p<0.05, ** p<0.01, *** p<0.001

Table 2 shows that those of Pakistani and Black origins are respectively 11.5 and 12.6 per cent more likely to be unbanked than White British. Importantly, employment and family type are also significantly associated with the probability of not holding a bank account. Unemployed are 55 per cent more likely to be unbanked than those in full time jobs, while single respondents (no children) are nearly twice more likely not to hold a bank account than couples with children. These are important findings as being unbanked is the most basic and fundamental dimension of financial exclusion, bank accounts allow for more efficient daily management of financial resources, are essential for gaining employment and can function as gateways to other financial services, with easier access to cheaper forms of credit, savings, insurance products. A social stigma is also often attached to being unbanked, as this can preclude access to social activities (Khan, Reference Khan2008; Warburton et al., Reference Warburton, Ng and Shardlow2013).

Table 3 presents the results on struggling with debt repayments and indicates that ethnicity is significant in holding unsustainable debtFootnote ⁵ . Those of Black origins are over 18 per cent more likely to struggle with debt than White British while respondents in the lowest income quartile are 86 per cent more likely to hold problem debt than those in the top quartile. The odds of struggling with debt are also significantly higher for respondents in social and private renting (68 and 54 per cent respectively) than for those who own their property. Lone parents are twice more likely to incur problem debt compared to couples with children, which confirms their financial vulnerability. This finding is in line with prior evidence on the difficulties experienced by single parents in keeping up with bills, as reported by Bridges and Disney (Reference Bridges and Disney2005) and by Hurst (Reference Hurst2011). As expected, income and age are negatively related to the odds of struggling with debt, this helps explain results on Black respondents, who tend to be over-represented amongst those in poorer and younger cohorts. The Report from the Select Committee on Financial Exclusion (2017) found that the propensity of poorer sections of the population to rely on expensive, unsuitable loans intensifies their financial hardship, but it can also be argued that the lack of availability of more suitable products means that there is little alternative to paying the ‘poverty premium’.

Table 3 Regression results on Debt repayments are a heavy burden based on a sample of 10,240 respondents

Notes. Ref: Reference Category.

Source. Family Resources Survey (2018/2019), author’s calculations.

Significance levels. * p<0.05, ** p<0.01, *** p<0.001

Results on Table 4 suggest that ethnicity is significantly associated with the probability of not participating in an employer or personal pension scheme, as respondents from Black and Other Ethnic minorities are 5.6 and 4.5 times respectively more likely to fall in this category than White British. Although statistically not significant, it is worth noting that results on Bangladeshi and Chinese respondents show confidence intervals with very high upper values, indicating that they may also hold greater odds of lacking pension participation. This finding supports recent evidence on household wealth which shows that Bangladeshi, Black and ‘other’ groups feature extremely low levels of private pensions and property wealth (Office for National Statistics, 2020). Findings show that women are nearly 22 per cent more likely to lack retirement planning than men, providing further evidence that a gender gap still exists (Foster, Reference Foster2013; Grady, Reference Grady2015). For lone parents the probability of not participating into a private pension is 38 per cent higher than for couples with children, while self-employed respondents are over three times less likely to contribute to a private retirement scheme than those in full-time employment. There is a positive relationship between income and retirement planning, with those in the second lowest quartile over twice more likely to lack private pensions compared to those in the top quartile. Unsurprisingly, respondents aged thirt-five and above are significantly more likely to engage in retirement planning than their younger counterparts.

Table 4 Regression results on Lack of pension scheme participation, based on a sample of 13,477 respondents

Notes. Ref: Reference Category.

Source. Family Resources Survey (2018/2019), author’s calculations.

Significance levels. * p<0.05, ** p<0.01, *** p<0.001

Sufficient values were not available for Pakistani.

Table 5 shows that the odds of not holding home insurance are respectively 37 and 63 per cent higher for Chinese and Other groups than for White British, while Pakistani respondents are nearly twice as likely not to hold insurance than their White counterparts. The reluctance to pay into financial products that may be perceived costly and unnecessary helps explain these findings to some extent; this is also evidenced by the significance of housing tenure, whereby respondents in social renting are 81 per cent more likely not to have home insurance. Women are nearly 27 per cent less likely to hold home insurance than men, which, together with the lack of retirement preparedness can, to some degree, be explained by women’s general reluctance to engage in financial planning (Fonseca et al., Reference Fonseca, Mullen, Zamarro and Zissimopoulos2012; Foster, Reference Foster2012, Reference Foster2013).

Table 5 Regression results on Not holding home contents insurance, based on a sample of 13,477 respondents

Notes. Ref: Reference Category.

Source. Family Resources Survey (2018/2019), author’s calculations.

Significance levels. * p<0.05, ** p<0.01, *** p<0.001

Unsurprisingly those unemployed are considerably more likely not to hold home insurance than full-time workers, while respondents in the two lowest income quartiles are over twice more likely to be uninsured than those in the top income quartile. Lastly, similarly to retirement planning, respondents in the middle and pre-retirement age cohorts are less likely to lack home insurance than younger respondents.