Market Insights Financial Capital Raising Digital Capital Raising

CrowdLending (Business) - Latvia

Latvia

Latvia is expected to witness a total transaction value of US$1.3m in the Crowdlending (Business) market market by 2024.
When compared globally, it is evident that China leads with a transaction value of US$15,970m in 2024.
Latvia's CrowdLending market in Capital Raising is witnessing a surge in peer-to-peer lending platforms, offering diverse investment opportunities to local businesses.

Key regions: China, United Kingdom, Brazil, Israel, India

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Analyst Opinion

The CrowdLending (Business) market in Latvia has been experiencing significant growth in recent years, driven by customer preferences, trends in the market, local special circumstances, and underlying macroeconomic factors. Customer preferences in the CrowdLending (Business) market in Latvia have shifted towards alternative financing options, such as peer-to-peer lending platforms.

This is due to the ease and convenience of accessing funding through online platforms, as well as the potential for higher returns compared to traditional banking products. Additionally, businesses in Latvia are increasingly seeking out alternative financing options to diversify their funding sources and reduce their reliance on traditional banks. Trends in the market show that the CrowdLending (Business) market in Latvia is becoming more competitive, with an increasing number of platforms entering the market.

This competition has led to lower interest rates and more favorable terms for borrowers, making CrowdLending an attractive option for businesses looking for affordable financing. Furthermore, there has been a growing demand for sustainable and socially responsible investments, with some CrowdLending platforms in Latvia focusing on funding projects that have a positive environmental or social impact. Local special circumstances in Latvia have also contributed to the development of the CrowdLending (Business) market.

The country has a relatively small banking sector, with limited access to financing for small and medium-sized enterprises (SMEs). This has created a gap in the market that CrowdLending platforms have been able to fill, providing much-needed funding to businesses that may have otherwise struggled to secure financing. Underlying macroeconomic factors have also played a role in the growth of the CrowdLending (Business) market in Latvia.

The country has experienced steady economic growth in recent years, which has led to increased confidence among businesses and investors. Additionally, low interest rates and a supportive regulatory environment have made CrowdLending an attractive option for both borrowers and lenders. Overall, the CrowdLending (Business) market in Latvia is developing rapidly due to customer preferences, market trends, local special circumstances, and underlying macroeconomic factors.

As more businesses and investors recognize the benefits of alternative financing options, the market is expected to continue to expand in the coming years.

Methodology

Data coverage:

The data encompasses B2C enterprises. Figures are based on transaction values / revenues / assets under management and user data of relevant services and products offered within the FinTech market.

Modeling approach / Market size:

Market sizes are determined through a combined top-down and bottom-up approach, building on a specific rationale for each market segment. As a basis for evaluating markets, we use annual financial reports of key players, industry reports, third-party reports, publicly available databases, and survey results from primary research (e.g., the Statista Global Consumer Survey). In addition, we use relevant key market indicators and data from country-specific associations, such as GDP, consumer spending, population, internet penetration, smartphone penetration, credit card penetration, and online banking penetration. This data helps us estimate the market size for each country individually.

Forecasts:

In our forecasts, we apply diverse forecasting techniques. The selection of forecasting techniques is based on the behavior of the relevant market. For example, the S-curve function and exponential trend smoothing are well suited for forecasting digital products and services due to the non-linear growth of technology adoption.

Additional notes:

The market is updated twice a year in case market dynamics change. The impact of the COVID-19 pandemic and the Russia-Ukraine war is considered at a country-specific level.