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How Has Fintech Affected Unbanked Populations?
Digital financial solutions have steadily increased global access to banking. Here are the benefits and drawbacks.

Digital financial solutions have steadily increased global access to banking. Here are the benefits and drawbacks.
In recent years, fintech has emerged as a powerful force in the financial sector. But what does it mean for populations traditionally excluded from formal financial services?
In this blog post, inspired by Oxford’s Fintech Programme, we'll explore the impact of fintech on unbanked populations, how fintech for unbanked populations has evolved, and the benefits and drawbacks of fintech solutions now and in the future.
The impact of fintech on financial inclusion
In both emerging markets—particularly Africa, Asia, and South America—and existing markets, reliable mobile wireless access has helped unbanked populations access financial tools and services. As the Global Findex Database 2017 reports (Demirgüç-Kunt et al., 2018):
1.2 billion adults have obtained an account since 2011, including 515 million since 2014. Between 2014 and 2017, the share of adults who have an account with a financial institution or through a mobile money service rose globally from 62 percent to 69 percent. In developing economies, the share rose from 54 percent to 63 percent.
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How has fintech for unbanked populations evolved?
In the early 2000s, when countries like the Philippines and Kenya first started to launch mobile money payments, fintech faced a series of barriers. Governments worried about consumer protection and competition, big banks often used their influence to block fintech-friendly policies, and regulators didn’t know how to address mobile solutions.
Since the early 2000s, however, hundreds of millions of previously unbanked adults have opened accounts for the first time. Many specifically opened accounts to receive digital wage payments or government transfers. In Thailand, nearly one in five banked adults opened their first account to receive government benefits. In Georgia, Uzbekistan, and Kazakhstan, that number was even higher—close to 30 percent.
Now, mobile money accounts have spread from East Africa to West Africa and beyond, dramatically increasing the share of adults who use digital payments. In some countries where mobile money is widespread, like Kenya, more than 90 percent of account owners make digital payments.
Fintech’s benefits for unbanked populations
For historically unbanked populations, fintech can help provide more convenient and affordable access to the global financial system. With fintech apps and services, unbanked adults can gain:
- Easy access to financial services. Mobile banking apps allow users to conduct transactions without visiting a physical bank branch. Apps can help unbanked adults manage their finances without taking the time or spending the money to travel to a long-distance banking location.
- Emergency funds. During Covid-19, governments used digital financial services to disperse quick and secure payments to citizens and businesses in Peru, Zambia, Uganda, and Namibia (Agur et al., 2020). Likewise, fintech can help unbanked individuals rapidly collect money from family and friends in a crisis.
- Improved administrative services. Fintech can digitise government salaries, pensions, and social transfer payments, helping governments like Mexico save upwards of US $1.3 billion per year. Clear online transactions can also help reduce costly errors, overpayments, and government corruption, funnelling money back into important public services.
- New opportunities for small business. Peer-to-peer fintech platforms can make it easy to send and receive money without going through a traditional financial institution. Crowdfunding platforms help low-income founders launch startups, projects, and platforms with help from a broader global community.
Fintech’s drawbacks
Despite fintech’s benefits, unbanked adults are still vulnerable to being taken advantage of or excluded from critical services. When using fintech solutions, they often face risks similar to those they might face in the formal financial system:
- Predatory lending. As discussed in Oxford’s Fintech Programme, unbanked individuals often lack access to strong consumer protection laws. Companies can offer pricey loans through mobile phones, leaving unbanked individuals struggling to pay off their loan balances and landing them in heavy debt.
- Expensive rates. While some fintech offerings are free or inexpensive, others can charge higher lending or payment fees. These higher rates can be written into disclaimers and go unnoticed until the payments are insurmountable.
- UX design flaws. Many fintech products are designed for people who are already comfortable with technology. Poorly designed interfaces or system architectures can put off those who are not as familiar with computers and smartphones and make transactions impossible to complete.
Build fintech solutions for unbanked populations
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Inversions, Bear Steepening Dis-Inversions, and Recessions
Does it matter if spreads are dis-inverting because short yields are falling, or long yields are rising? MacKenzie and McCormick (Bloomberg) say yes. With…

Does it matter if spreads are dis-inverting because short yields are falling, or long yields are rising? MacKenzie and McCormick (Bloomberg) say yes. With long yields rising…
If it looked at first glance as though the shift in the yield curve was a solidly positive sign — one indicating that the economy is now at less risk of a recession than it was — that’s probably not the case. True, it shows traders aren’t expecting the Fed to shift into firefighting mode soon. Even so, it’s almost certain to further dampen the economy as it ripples through to mortgages, credit cards and business loans. That will tighten financial conditions further, which may be a welcome development to the Fed. The risk, though, is that it hits the brakes so hard that the economy stalls completely.
Does having a bull steepening prevent a recession? Figure 1, covering the Great Moderation, is somewhat conducive to that hypothesis, at least eyealling it. h
Figure 1: 10 year-3 month Treasury spread, % (blue, left scale), and 3 month change in 10yr-3mo spread, ppts (green, right scale). October observation for data through 10/13. NBER defined peak-to-trough recession dates shaded gray. Red arrows when 3 month change is positive during period when dis-inversion is occurring. Source: Treasury via FRED, NBER, and author’s calculations.
The evidence in favor of the bear steepening hypothesis is stronger when evaluating the proposition formally. I estimate probit models for (i) spread only, (ii) spread and short rate, and (iii) spread, short rate and 3 month change in spread. The 3 month change in spread is statistically significant and adds to the pseudo-R2.
(ii) Pr(recession=1)t+12 = 0.813 – 76.11spreadt + 9.80itshort
Pseudo-R2 = 0.28, Nobs = 241, bold denotes significant at 5% msl.
(iii) Pr(recession=1)t+12 = 0.736 – 98.37spreadt + 11.99itshort + 98.28Δ3spreadt
Pseudo-R2 = 0.34, Nobs = 241, bold denotes significant at 5% msl.
The recession probabilities are shown below.
Figure 2: Recession probability 12 month ahead estimated over the 1986-2023M10 period for spread (blue), for spread and short rate (tan), and spread, short rate, and 3 month change in spread (green). NBER defined peak-to-trough recession dates shaded gray. Source: NBER, and author’s calculations.
The bear-steepening specification implies 90% probability of recession in 2024M09, while it’s only 66.4% using the spread + short rate (peak probability for this specification is May 2024). Does this make me more pessimistic about avoiding a recession? Not really; the Ahmed-Chinn specification with the foreign term spread (but no steepening measure) was about 90.8% probability for September 2024.
recession yield curve fed recessionUncategorized
Inversions, Bear Steepening Inversions, and Recessions
Does it matter if spreads are dis-inverting because short yields are falling, or long yields are rising? MacKenzie and McCormick (Bloomberg) say yes. With…

Does it matter if spreads are dis-inverting because short yields are falling, or long yields are rising? MacKenzie and McCormick (Bloomberg) say yes. With long yields rising…
If it looked at first glance as though the shift in the yield curve was a solidly positive sign — one indicating that the economy is now at less risk of a recession than it was — that’s probably not the case. True, it shows traders aren’t expecting the Fed to shift into firefighting mode soon. Even so, it’s almost certain to further dampen the economy as it ripples through to mortgages, credit cards and business loans. That will tighten financial conditions further, which may be a welcome development to the Fed. The risk, though, is that it hits the brakes so hard that the economy stalls completely.
Does having a bull steepening prevent a recession? Figure 1, covering the Great Moderation, is somewhat conducive to that hypothesis, at least eyealling it. h
Figure 1: 10 year-3 month Treasury spread, % (blue, left scale), and 3 month change in 10yr-3mo spread, ppts (green, right scale). October observation for data through 10/13. NBER defined peak-to-trough recession dates shaded gray. Red arrows when 3 month change is positive during period when dis-inversion is occurring. Source: Treasury via FRED, NBER, and author’s calculations.
The evidence in favor of the bear steepening hypothesis is stronger when evaluating the proposition formally. I estimate probit models for (i) spread only, (ii) spread and short rate, and (iii) spread, short rate and 3 month change in spread. The 3 month change in spread is statistically significant and adds to the pseudo-R2.
(ii) Pr(recession=1)t+12 = 0.813 – 76.11spreadt + 9.80itshort
Pseudo-R2 = 0.28, Nobs = 241, bold denotes significant at 5% msl.
(iii) Pr(recession=1)t+12 = 0.736 – 98.37spreadt + 11.99itshort + 98.28Δ3spreadt
Pseudo-R2 = 0.34, Nobs = 241, bold denotes significant at 5% msl.
The recession probabilities are shown below.
Figure 2: Recession probability 12 month ahead estimated over the 1986-2023M10 period for spread (blue), for spread and short rate (tan), and spread, short rate, and 3 month change in spread (green). NBER defined peak-to-trough recession dates shaded gray. Source: NBER, and author’s calculations.
The bear-steepening specification implies 90% probability of recession in 2024M09, while it’s only 66.4% using the spread + short rate (peak probability for this specification is May 2024). Does this make me more pessimistic about avoiding a recession? Not really; the Ahmed-Chinn specification with the foreign term spread (but no steepening measure) was about 90.8% probability for September 2024.
recession yield curve fed recessionUncategorized
Latin America takes global lead in preference for centralized exchanges: Report
According to Chainalysis, Latin American crypto users show a significant preference for centralized exchanges, in contrast to the worldwide pattern.
…

According to Chainalysis, Latin American crypto users show a significant preference for centralized exchanges, in contrast to the worldwide pattern.
According to a recent report from blockchain analytics firm Chainalysis, Latin America has a distinct inclination toward centralized exchanges when compared to the rest of the world, as opposed to decentralized exchanges.
Published on October 11, Chainalysis stated that Latin America has the seventh-largest crypto economy in the world, trailing closely behind the Middle East and North America (MENA), Eastern Asia, and Eastern Europe.
However, it notes that crypto users in Latin America strongly favor using centralized exchanges:
Latin America shows the highest preference for centralized exchanges of any region we study, and tilts slightly away from institutional activity compared to other regions.

Furthermore, in some countries within the region, crypto activity by platform type significantly exceeds the global average. The worldwide average is 48.1% for centralized exchanges, 44% for decentralized exchanges, and 5.9% for other decentralized finance (DeFi) activities.
However, Venezuela shows a 92.5% preference for centralized exchanges, compared to a 5.6% preference for decentralized exchanges (DEXs).
Furthermore, it pointed out that Venezuela has a unique reason for its surging adoption, primarily attributed to a "complex humanitarian emergency."
Related: Crypto adoption is booming, but not in the US or Europe — Bitcoin Builders 2023
The report explains that amid the COVID-19 pandemic in 2020, crypto played a pivotal role in directly assisting healthcare professionals in the country.
Therefore, crypto became a necessary form of value as traditional payments were difficult, given the government's refusal to accept international aid, influenced by political reasons.
On the other hand, Colombia shows a 74% preference for centralized exchanges, while decentralized exchanges account for just 21.1% of their preferences.

Meanwhile, three Latin American countries secured positions in the top 20 ranks on Chainalysis' Global Crypto Adoption Index. Brazil stands at the 9th position, with Argentina following at 15th, and Mexico at 16th.
At the global level, India claims the leading spot, with Nigeria and Vietnam securing second and third positions, respectively.
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