Access to Credit for SMEs in Latin America: 6 Challenges that Technology Promises to Overcome

    Technology, alternative data sources and AI are increasingly providing solutions to expand the financial inclusion of SMEs and contribute to their growth and financing

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    Slow financial inclusion is a common problem faced by small and medium-sized businesses in Latin America. Provenir, the world’s leading company in risk decision-making software through Artificial Intelligence (AI) and Machine Learning (ML) for the financial sector, explains what the main challenges that fintech and banks face to offer services for businesses are, and how AI and alternative data help to overcome these challenges.

    According to data from Small Business Lending Statistics and Trends (2021), 48% of SMEs need financing to meet their operating obligations, and 56% seek credit to develop new projects and expand their business. Despite this, applications that are processed through traditional methods can be difficult to process and take longer than expected without positive responses.

    José Luis Vargas, Executive Vice President of Provenir for Latin America, comments that, “Expanding access to credit is essential for the growth and survival of companies, especially small or medium-sized ones, allowing them to finance their operations, achieve their objectives, expand and create jobs. Technology has provided new sources of data that enable lenders to get a more accurate view of their customers and overcome the challenges that make it difficult for SMEs to access credit. In addition, the automation of processes through AI can help reduce costs and increase efficiency in the evaluation of credit applications, making it easier for businesses to access products and with more affordable rates”.

    Some of the most common challenges that fintechs have managed to overcome through next-generation technology are:

    Lack of financial information- Many SMEs do not have adequate financial records or have difficulty sharing them with financial institutions and lenders, making credit risk assessment difficult. To solve this limited information, alternative data sources provide valuable strategic data that help build much more accurate profiles of unbanked or new credit companies.

    Long approval processes- The credit application process can be complicated and require a large amount of documentation, which discourages SMEs from applying for loans, since they do not have many of the traditional requirements. The implementation of technological solutions streamlines the application, analysis and approval processes, allowing small and medium-sized companies to obtain resources in a timely manner through innovative processes.

    Risk- Unlike large companies, SMEs can pose a greater risk to lenders due to their size and structure, making it difficult to obtain financing for their businesses. However, the use of models powered by AI and ML can help to assess credit risk more accurately and take advantage of opportunities for growth and scalability over time of ventures.

    Lender Limitations- Many lenders do not have the capacity to assess the credit risk of SMEs or adapt to their growth and evolution, therefore they do not feel able to lend them money. One of the benefits of technological innovation in granting credit is real-time decision-making and constant feedback on its results, which allow Know Your Customer (KYC) models to be executed, and easily and quickly adapt to their needs over time.

    Lack of financial infrastructure- In some regions or countries, the lack of a strong financial and technological infrastructure can hinder decision-making and access to credit for SMEs, leaving a lack of financial services and products available to businesses; searching for alternatives with data, that is within reach of these scenarios, enables greater financial inclusion and improves financing opportunities for new businesses.

    Changes in economic conditions- Changes in economic conditions, such as recession, can negatively affect access to credit for SMEs, due to increased risk aversion on the part of lenders. Traditional decision-making models often have difficulties adapting to new dynamics, so opting for models that respond to changes in a short time and reduce the risk associated with uncertainty have been essential factors for the competitiveness of fintech in the financial system.

    “A large number of financial institutions have risen to the challenge, thanks to streamlined application processes and fast approvals that have established themselves as an optimal option to meet their SMB needs. However, it is not only about offering a better customer experience, but about staying competitive in the market, so it is important to make smarter decisions and keep risk under control. This has been possible with efficient and advanced analysis through AI and reliable sources of data that build the path to advance in the financial inclusion of such important actors for Latin America as small and medium-sized companies”, concludes José Luis Vargas.

    Resonance Costa Rica
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