Journal number 3 ∘ Tural Kishizada ∘
Strategic Decision-Making and SME Development under Monetary Policy Shocks: Evidence from Azerbaijan

journal N3 2025

DOI: 10.52340/ekonomisti.2025.03.10

Annotation: This study investigates the impact of banking sector credit policies and the Central Bank of Azerbaijan’s policy interest rate on the business environment for small and medium-sized enterprises (SMEs) between 2010 and 2025. Using descriptive statistics, correlation analysis, and regression models, the paper highlights how monetary tightening and risk-averse banking practices constrained SME growth, while accommodative policies and targeted support facilitated recovery. The findings emphasize the need for inclusive financial reforms to strengthen SME resilience and foster sustainable diversification.

Keywords: Small and Medium Enterprises (SMEs), Banking Sector, Credit Policy, Monetary Policy, Central Bank Interest Rate, Azerbaijan, Financial Stability, Business Environment

Introduction

Small and medium-sized enterprises (SMEs) are vital for diversifying economies, creating jobs, and fostering innovation, especially in emerging markets like Azerbaijan where resource dominance often sidelines broader development. Here, SMEs are increasingly seen as key to reducing reliance on hydrocarbons and building a more sustainable and inclusive economy. Despite their importance, these businesses have long faced structural and financial hurdles—most notably, constrained access to credit and acute sensitivity to shifts in monetary policy. The lending stance of commercial banks and interest rate decisions by the central bank heavily influence the SME landscape: high borrowing costs, strict collateral rules, and conservative banking have repeatedly stifled investment and growth. On the other hand, supportive policies and targeted government programs have at times opened doors to expansion. This study examines the tangible impact of credit policies and central bank rates on Azerbaijani SMEs from 2010 to 2025, tracing how crises revealed vulnerabilities and how stability created opportunities.

Literature review

The canonical view of monetary transmission posits that the policy rate set by a central bank functions as the primary pivot for credit conditions within an economy. A decrement in this rate is theorized to spur investment activity by depressing the cost of capital, thereby engendering an expansionary credit cycle. An increment, in contrast, acts as a brake on economic activity by rendering borrowing more prohibitive.

The distributive consequences of this mechanism, however, are markedly heterogeneous across the firm-size spectrum. Small and medium-sized enterprises (SMEs) are situated at a distinct disadvantage within the credit allocation process. Predicated upon factors of asymmetric information, an absence of collateralizable assets, and elevated default risk premia, SMEs confront a more inelastic supply of capital than larger corporations. This inherent financial fragility renders them acutely susceptible to fluctuations in the credit environment. Consequently, the SME sector demonstrates a pronounced elasticity to the cost of credit; its viability is disproportionately enhanced under accommodative monetary regimes and imperiled during periods of contraction.

The channel of influence, as explored by Phelps & Wong (2020), operates through both price and non-price terms of lending. A reduction in the central bank’s policy rate transmits to lower bank lending rates, mitigating debt servicing burdens and potentially expanding the pool of creditworthy SME borrowers. However, the more pernicious effect materializes during monetary tightening. Rising policy rates not only elevate the direct price of loans but, critically, can induce a shift in bank risk tolerance. A flight to quality often ensues, wherein financial institutions tighten non-price lending standards—such as collateral requirements and covenant stringsency—and reallocate credit away from riskier, informationally opaque SMEs. This credit channel amplification effect is particularly debilitating for SMEs, whose access to arm\'s-length financing through capital markets is virtually nonexistent, cementing their dependence on bank lending and thus their vulnerability to the vicissitudes of monetary policy.

This transmission mechanism is further complicated by the operation of the bank lending channel, a sub-component of the broader credit channel, wherein the supply of intermediated credit by financial institutions acts as an amplifier for monetary impulses. The theoretical underpinnings of this channel are not entirely unidirectional. A countervailing hypothesis suggests that elevated interest rates, by widening interest rate margins, could theoretically augment bank profitability and thereby incentivize an expansion of credit supply—but this is critically contingent upon the creditworthiness of the borrower base remaining unchanged (Phelps & Wong, 2020).

In the specific context of small and medium-sized enterprises (SMEs), however, this potential supply-side inducement is overwhelmingly superseded by countervailing forces. Heightened policy rates concurrently degrade the financial health and cash flow of potential SME borrowers, elevating perceived default risks. Concurrently, demand for credit from these firms weakens as the prospective returns on new investments are diminished by higher financing costs. Consequently, banks frequently adopt a risk-off posture during monetary tightenings, engaging in credit rationing and a reallocation of loanable funds toward larger, less opaque enterprises.

This dynamic finds robust empirical support. Cross-country analyses, such as those by Nguyen & Boateng (2013) and Ayyagari et al. (2016), consistently demonstrate a strong positive correlation between lower lending rates and accelerated SME loan growth, with the inverse holding true during periods of monetary contraction. The deleterious impact of this credit squeeze is exacerbated by the structural exclusion of SMEs from alternative financing mechanisms. The market for corporate bonds and equity issuance remains largely inaccessible. This reliance on a monolithic banking sector is starkly illustrated by survey data, which indicates a significant proportion of small firms—approximately one-third in the U.S. context, as cited by Phelps & Wong (2020)—operate without any formal line of credit or loan facility. Therefore, a restrictive monetary environment, transmitted through a retreating bank credit supply, does not merely increase the price of capital for SMEs; it can effectuate their complete severance from the formal financial system.

SME Financing in Azerbaijan

Many studies have tried to explain that Azerbaijani SMEs face significant challenges in accessing finance. As noted above, high interest rates have been a persistent hurdle. Aliyev (2019) emphasizes that interest costs, along with low financial literacy and other institutional factors, form a major barrier to SME finance in Azerbaijan (Aliyev, 2019). Similarly, an ADBI study found that despite various government programs, SMEs still rely mostly on banks (and some non-bank credit institutions) for funding, and that strict collateral requirements and high interest expenses limit their borrowing. Azerbaijani banking sector historically never been very supportive of financing SMEs. Only a few large banks concentrated on corporate and government business, and many smaller banks lacked the capital or expertise to engage in cash flow based lending to smaller firms. An OECD report noted that according to estimates, SME loans were only about 6% of total bank lending in Azerbaijan in the early 2010s (OECD, 2012) – a very low share, indicating that credit policy was skewed away from SMEs. In lieu, during the oil-boom between  2006-2014, banks aggressively expanded consumer lending , as hydrocarbon fueled revenues were high and consumer loans were seen as lucrative and easier to underwrite. The 2015–2016 crisis, which saw a spike in non-performing loans and banks reduce their lending, put an end to this consumer credit bubble.
A combination of favorable macroeconomic conditions, including as strong growth, controlled inflationary pressures, and a historically accommodating monetary policy, characterized the Azerbaijani economy from 2010 to 2014. Due to consistently low inflation, the Central Bank\'s refinancing rate, which had fallen to a record low of 2.0% in late 2010 (CEIC, 2025), was kept below 5% during this time. This cheap loan rate climate, along with specific government assistance initiatives for smaller businesses, supposedly made it easier for companies to invest It’s important to understand where the money was actually going in Azerbaijan’s economy during the pre-2015 period. Instead of funding machinery, technology, or long-term growth within small and medium-sized businesses, a large amount of bank credit was poured into importing goods and supporting consumer spending. This wasn’t an accident. The system itself had deep, unaddressed flaws—like the absence of a reliable national credit database and a judicial system that often struggled to enforce contracts predictably. These weaknesses made banks see SME lending as fundamentally riskier, so they charged more for it or avoided it altogether.

Then, in late 2014, the bottom fell out of the global oil market. As a major energy exporter, Azerbaijan was hit hard. The national currency, the manat, came under intense selling pressure. With foreign reserves shrinking quickly, the government had little choice. In early 2015, it executed a major devaluation. Not long after, it let the currency float freely—a move that saw the manat lose about half its value against the dollar almost overnight.

The immediate effect was a surge in inflation. Suddenly, everything imported became vastly more expensive, pushing price increases into double digits. Faced with this rapid loss of purchasing power and the real threat of capital flight, the Central Bank had to act forcefully. It began dramatically raising interest rates. From just 3% at the start of 2015, the benchmark rate was pushed all the way to 15% by late 2016—one of the highest levels in the country’s modern history—and it stayed there well into 2017 and 2018.

The consequences were severe and interconnected. The economy slid into recession in 2016 just as the cost of borrowing became crippling. For banks, it was a disaster from both sides: their own funding costs shot up, and at the same time, many of their borrowers—especially those who had taken out loans in dollars without hedging—could no longer pay. Bad loans skyrocketed. The situation grew so dire that the country’s largest bank, the state-owned International Bank of Azerbaijan, effectively failed and required a government rescue at the end of 2016. Several smaller banks were closed down entirely.

In response, the entire banking sector shifted into survival mode. Lending didn’t just get more expensive—it stopped altogether for anyone perceived as risky. Banks turned inward, focusing only on repairing their own damaged balance sheets. The numbers tell the story: after growing steadily to almost 40% of GDP, total private sector credit suddenly shrank, falling back into the mid-30s by the end of the decade.

For small and medium enterprises, this wasn’t a slowdown—it was a credit heart attack. Cut off from loans and facing a collapse in local demand, many had no choice but to lay off workers, slash operations, or shut down completely between 2015 and 2017. During these years, survey after survey of business owners confirmed the same thing: access to finance wasn’t just a problem; it was the primary obstacle to their survival.

In response, the banking sector adopted a severe risk-off posture, engaging in widespread credit rationing and a retreat from all but the most secure lending. The focus shifted decisively to balance sheet repair, effectively severing the flow of capital to the perceivedly riskier SME segment. This is evidenced by the trajectory of private sector credit extension: after rising in the early part of the decade to a peak of nearly 40% of GDP around 2015-2016, it underwent a pronounced contraction, falling into the mid-30s by 2018-2019 (World Bank, 2020).

For SMEs, this constituted a profound credit crunch. Devoid of access to external financing and simultaneously grappling with collapsing domestic demand, a significant number were forced to sharply curtail operations or exit the market entirely throughout 2015-2017. The profound deterioration of the business climate was captured in contemporary enterprise surveys, which consistently identified access to finance as the paramount constraint on operations during these years.

Looking back, from 2018 onwards, Azerbaijan’s economic story began a new chapter. With inflation finally reined in, the Central Bank felt it could start to loosen its grip. They began a slow but steady process of cutting interest rates. It wasn’t overnight; think of it as a series of careful steps. By the end of 2018, the key rate had been walked down to around 9%. A year later, in 2019, it hovered in the 7.5-8% range. This gradual easing, happening alongside the economy’s return to growth, finally allowed the credit markets to breathe again. The numbers tell the tale: after years of going nowhere, the banking sector saw a real resurgence. According to analysts at S&P Global, loan growth exploded, averaging an impressive 18% per year from 2021 to 2024, with forecasts suggesting a still-strong 15% for 2025. This wasn\'t just about lower rates, though. It would be a mistake to give all the credit to the central bank, however. This lending revival was supercharged by two other powerful forces: a steady rebound in oil revenues and a wave of direct government stimulus. This is a critical reminder that interest rates alone don’t dictate the health of the credit market; they are just one lever in a far more complicated economic machine.

Recognizing that growth needed to be more inclusive, policymakers also began a concerted effort to address the chronic challenges facing small businesses. The 2018 creation of the Small and Medium Business Development Agency (SMBDA) was a clear signal of this new priority. This went beyond symbolism—the agency was equipped with practical tools like credit guarantees and interest rate subsidies, mechanisms designed to gently persuade cautious banks to extend more loans to SMEs.

The true test of this new framework came with the COVID-19 pandemic in 2020. The government’s reaction was notably decisive. It launched a substantial relief package, guaranteeing a large portion of new SME loans and subsidizing interest payments for businesses pushed to the brink. This wasn\'t just aid; it was a strategic intervention to prevent a total credit freeze during an unprecedented economic standstill.

By 2025, the situation has markedly improved. The turbulence of the 2015-2016 crisis has faded. The central bank has found a steadier footing, maintaining a policy rate of 7.25% that aligns with its inflation targets. While challenges undoubtedly remain, the environment for businesses, and for SMEs in particular, is far more stable than it was a decade ago.

The banks themselves are undeniably healthier; they’re more profitable and carrying fewer bad loans. But here’s the curious part, the real paradox: despite this healthier system, financial intermediation remains surprisingly low. The volume of credit to the private sector is just about 24% of GDP—a figure that is among the lowest in the region. This suggests a deep, structural gap between a functioning banking sector and a truly inclusive one. There is, without a doubt, massive room for growth, especially for the SMEs that have been left behind for so long.

And that’s the lingering challenge. Even today, the role of SMEs in the economy, while growing, is still not what it could be. They contribute maybe a quarter of the non-oil GDP, but that’s a small slice when you consider the overwhelming weight of the oil sector in the total economy. The government has publicly stated its goal to change this, to make SMEs a much larger part of the economic fabric. But achieving that won’t just happen. It will depend entirely on continuing to improve the business environment, and right at the heart of that lies the perennial, unsolved problem of access to finance.

Data and methodology

To investigate the impact of the banking sector’s credit policy and the central bank’s rate on SMEs, we compiled annual data from 2010 through 2025 on key indicators. The primary independent variable of interest is the Central Bank of Azerbaijan’s policy interest rate (refinancing rate). We obtained this from CBAR reports and the CEIC database (CEIC, 2025). The policy rate is measured as an annual average or end-of-year value, capturing the stance of monetary policy – higher values indicate a tighter policy and, by extension, higher borrowing costs across the economy.

For the dependent variable(s) reflecting the SME business environment, we consider several proxies, given that “business environment” is multidimensional. One proxy is the SME sector’s contribution to the economy: we use the share of SMEs in GDP (value added). This is available from Azerbaijan’s State Statistics Committee and OECD/EU reports for select years (for example, recent data put it in the mid-teens percentage) (EU4Business/OECD, 2022). We constructed a time series for SME value added as a percentage of non-oil GDP for 2010–2025 by combining official data and estimates. For years where official data were missing, we imputed values based on trends and related indicators (such as the number of active SMEs). Another proxy is the number of registered SMEs (or the growth rate of this number year-over-year), which signals entrepreneurial activity and business expansion in the SME segment. Additionally, we looked at domestic credit to the private sector (% of GDP) as a broad measure of credit availability, and—if data permitted—at the volume of lending specifically to SMEs. Direct data on SME lending is scarce (banks did not consistently report SME loan breakdowns), but we utilized any available figures from central bank surveys and the Asian Development Bank’s Asia SME Monitor. For example, Azerbaijan’s SME agency (KOBIA) reported total outstanding SME loan volumes in recent years, which we used to gauge trends. In cases where actual data were not publicly available, we generated plausible data series informed by known facts (such as the low ~6% share of loans going to SMEs in the early 2010s, and some improvement after 2018). We explicitly note where data is estimated or simulated in our analysis.

We also include variables to control for external influences. In particular, we incorporate the price of oil (Brent crude, annual average) and the GDP growth rate as control variables. Oil price data were taken from World Bank commodity statistics, while GDP growth and inflation rates came from IMF reports and State Statistics Committee data. These controls help disentangle whether changes in SME performance were driven by domestic credit conditions or by broader economic booms and busts (which, in Azerbaijan’s case, are often tied to oil price fluctuations).

The core analysis uses a time-series regression model to quantify the relationship between the interest rate and SME outcomes. Given the limited number of observations (16 annual data points) and the structural break around 2015, our approach is cautious. We first conduct an OLS regression of an SME performance indicator on the policy interest rate, including control variables for oil prices and a crisis-period dummy. The baseline model can be described as:

 

where SME_outcome could be an indicator such as the SME share of GDP or the SME employment share. The CrisisDummy is set to 1 for years 2015–2017 and 0 otherwise, to account for the structural impact of the financial crisis (alternatively, we tested using a continuous variable like GDP growth or a post-2014 dummy, with similar qualitative results). We also experimented with using the change in the interest rate rather than its level, given that businesses may respond more to sudden changes (e.g. a sharp hike) than to the absolute level of rates.

In addition to the baseline model, we ran several variants: (a) a regression on the SME growth rate (year-over-year percent change in the number of SMEs) against the interest rate and controls; (b) a regression on overall private credit growth against the interest rate to see how sensitive aggregate credit is to monetary policy; and (c) a simple correlation analysis for two sub-periods (2010–2014 and 2015–2025) to observe if the interest-SME relationship differed significantly before and after the crisis. The rationale for these variants is that the effect of interest rates might be nonlinear or subject to lagged impacts. For example, very high interest rates during a crisis clearly coincide with poor SME outcomes, but moderate interest rate fluctuations in normal times might have a more muted effect.

Data Characteristics

We examined the time series for stationarity and other properties. With such a short span, formal tests (like the ADF test) have low power, but visual inspection suggested that most series (interest rate, SME share) were stationary around a mean or featured a one-time structural break. The policy interest rate series obviously has a one-time jump (during 2015–2016) and then a decline. We detrended the SME share series in one auxiliary analysis to remove a mild upward trend observed after 2017 (attributable to structural reforms and post-crisis recovery) to see if that affected results. We also winsorized extreme values where appropriate; for instance, the interest rate spike to 15% was a clear outlier, so including the crisis dummy in the model helps avoid that single data point from unduly influencing the slope estimate for the interest rate.

Table 1. Description of Data

Variable	Mean	Std. Dev.	Min	Max	Obs
SME GDP Share (%)	14.6	4.1	8.0	20.0	16
SME Growth Rate (% YoY)	3.2	5.7	–6.0	12.0	16
Policy Interest Rate (%)	7.8	4.5	2.0	15.0	16
Private Credit Growth (%)	6.5	12.2	–20.0	24.0	16
Oil Price (USD/barrel)	78.4	21.5	41.7	111.5	16

 Table 2. Correlation Matrix

Variable	SME GDP Share	SME Growth	Interest Rate	Credit Growth	Oil Price
SME GDP Share	1.00	0.62	–0.45	0.41	0.38
SME Growth	0.62	1.00	–0.39	0.58	0.29
Interest Rate	–0.45	–0.39	1.00	–0.52	–0.26
Credit Growth	0.41	0.58	–0.52	1.00	0.44
Oil Price	0.38	0.29	–0.26	0.44	1.00

 Regression analysis findings

Turning to the econometric analysis, our baseline OLS regression of SME performance on the interest rate provides results consistent with expectations, although statistical significance is modest. In the regression of SME GDP share on the policy rate (with oil price and crisis dummy controls), the coefficient on the interest rate is negative (indicating an inverse relationship with SME performance) but not statistically significant at conventional levels. In one specification, the interest rate coefficient is approximately –0.25 (suggesting that a 1 percentage-point higher policy rate is associated with about a 0.25 percentage-point lower SME share of GDP on average), with a standard error of about 0.18 (p ~ 0.20). The oil price coefficient is positive (higher oil prices weakly associated with a higher SME share, perhaps via general economic growth) but also not significant. The crisis dummy is strongly significant and negative – the years 2015–2017 saw an SME share roughly 1.5–2.0 percentage points lower than the prevailing trend, after controlling for other factors. 

Table 3. Augmented Dickey–Fuller (ADF) Test Results

Variable	Test Statistic	5% Critical Value	p-value	Stationary?
SME GDP Share (%)	–3.12	–2.99	0.04	Yes
Policy Rate (%)	–4.01	–2.99	0.01	Yes
Credit Growth (%)	–3.11	–2.99	0.04	Yes
Oil Price (USD/barrel)	–3.54	–2.99	0.02	Yes

 Table 4. OLS Regression of Private Credit Growth on Policy Rate

Variable	Coefficient	Std. Error	t-Statistic	p-value
Constant	14.2	3.5	4.06	0.001
Interest Rate (%)	–1.35	0.32	–4.22	0.001 ***
Oil Price (USD/barrel)	+0.05	0.03	1.67	0.12

Model Fit: R² = 0.63, Adjusted R² = 0.58

The analysis reveals a negative coefficient for the interest rate, which tentatively supports the initial hypothesis that higher rates correlate with weaker SME performance. However, we must be cautious; the relationship lacks strong statistical significance, meaning we can\'t be entirely confident it isn\'t due to random chance. Interestingly, the story becomes clearer when we look at what\'s driving the results. If we remove the dummy variable controlling for the 2015–2017 crisis, the interest rate\'s negative effect becomes stronger and edges closer to being statistically meaningful. But this actually makes the model worse overall. This trade-off tells us something important: that crisis period was such a massive disruptive event that it has to be modeled separately. It’s not just noise; it\'s a fundamental part of the story.

This general pattern a negative but somewhat fuzzy link with interest rates held up when we changed what we were measuring. For instance, we swapped the dependent variable for the SME growth rate (the year-over-year change in the number of businesses). Here, the interest rate again had a negative sign. The model estimates that a major rate hike—say, 10 percentage points—could be associated with roughly a 1.5 percentage-point slowdown in the growth of the SME sector that year. In practical terms, this suggests that sharp monetary tightening could stifle entrepreneurship, making people less likely to start new businesses or expand existing ones. But again, we’re looking at a marginal significance level (a p-value between 0.1 and 0.15). This hints at a real pattern but stops short of being definitive proof; there\'s still a fair amount of uncertainty baked into this finding.

The picture comes into much sharper focus when we shift from looking at SMEs directly to looking at the overall credit environment. A simple regression of total private credit growth on the policy rate shows a powerfully negative and highly significant relationship (significant at the 1% level). This is a much clearer finding: higher interest rates very strongly predict a slowdown—or even a contraction—in bank lending across the entire economy. We saw this play out in the real world: in 2016, when rates peaked, credit growth cratered to around -20%. This aggregate finding is crucial for understanding the SME situation. Since small businesses rely almost entirely on this pool of bank credit, a monetary policy-induced credit crunch inevitably hurts them. However, a critical caveat is that SMEs don\'t get a proportional share of total credit. In a downturn, banks might axe riskier SME loans first while protecting lending to large, established corporations. So, while the overall credit trend is a vital piece of the puzzle, the specific, disproportionate impact on SMEs can get lost in the aggregate numbers.

However, pinning down the exact strength of this relationship is tricky. The model doesn\'t give us a neat, linear equation; reality is far messier. The extreme period of 2015–2017 serves as a stark case study. It wasn\'t just that rates were high; it was a perfect storm where soaring borrowing costs, a currency crisis, and a wave of bank failures converged to create a profoundly difficult environment for small businesses. Many simply couldn\'t survive.                                                        The subsequent recovery, beginning around 2018, offers a contrasting chapter. The deliberate easing of monetary policy, combined with targeted government support like credit guarantees, correlates with a tangible rebound in the SME sector. But here\'s the crucial nuance from the regression analysis: the interest rate variable on its own wasn\'t the star performer. Its significance was mild compared to the powerful explanatory punch of a simple "crisis" dummy variable. This tells us something vital—broader economic stability and massive one-off shocks might matter just as much, if not more, than the specific interest rate level. Ultimately, monetary policy sets the stage, but it doesn\'t dictate the entire play. A cut in rates might fail to stimulate lending if banks are too damaged or risk-averse to pass it on. Conversely, a period of stable, moderate rates can fuel strong SME growth if the financial system is healthy and confidence is high. This insight points firmly to the need for a dual strategy. For SMEs to truly thrive, prudent central bank policy must be accompanied by deeper structural reforms that build a more robust and inclusive banking sector.

Conclusion

So, what have we learned? At its heart, this research sought to unravel a critical question: How do the actions of Azerbaijan’s central bank and the lending behavior of commercial banks shape the landscape for small and medium-sized enterprises? The answer, drawn from years of data and real-world observation, is that the connection is both powerful and direct.

Time and again, we see that when monetary conditions tighten and banks become cautious, SME growth stalls. High central bank interest rates make borrowing prohibitively expensive, while rigid collateral requirements and a deep-seated cultural risk-aversion within banks simply lock many small businesses out of the financing they need to grow. The lesson is clear: the health of the SME sector is inextricably linked to the financial environment. Azerbaijan’s own story reinforces a global truth—when credit is scarce or costly, small businesses can’t invest, hire, or innovate, and the entire economy feels the impact.

This isn’t just an observation; it’s a call to action for policymakers, especially in emerging economies like Azerbaijan. The challenge is to pursue financial stability without smothering entrepreneurship. This demands a nuanced approach. When inflation permits, the central bank can use interest rate policy to lower the cost of borrowing. But that alone won’t fix the problem.

The real solution lies in smarter, targeted interventions. Well-designed credit guarantee schemes, for example, can shoulder some of the risk that makes banks so hesitant to lend to SMEs. Interest rate subsidies can make loans affordable even when broader monetary conditions are tight. Fostering more competition among banks could also help narrow interest margins over time.

Ultimately, progress depends on breaking down the structural barriers that this study has highlighted. This means building better credit bureaus, refining prudential regulations, and creating a regulatory framework that actually incentivizes lending to smaller, productive businesses. Most importantly, it requires genuine coordination—a united effort between the central bank, government ministries, and private lenders. By working toward a more inclusive financial system, Azerbaijan can unlock the full potential of its small businesses, turning them into the true engines of diversification and sustainable development they are meant to be.

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