What are the challenges of this industry?
Microfinance institutions' main objective is to improve access to credit, especially in rural areas and low-income sectors. However, they face significant challenges in expanding their services due to the growing rate of default and the difficulty in obtaining new accounts.
some numbers
In 2024, 51% of companies in the region claim to have experienced delays in payments from their customers according to the latest edition of Coface's 'LATAM Corporate Payment Survey 2024'. This context limits the growth of microfinance institutions and reduces opportunities to promote financial inclusion.
Decision engines for efficient portfolio management and collections
The use of decision engines optimizes the risk assessment process and enables comprehensive credit management. This type of technology enables microfinance institutions to analyze historical and real-time data to make accurate assessments of each client's creditworthiness and automate decision-making. In addition, decision engines help mitigate over-indebtedness by combining different variables that identify risk patterns and financial overload, allowing microfinance institutions to offer more sustainable alternatives aligned with their clients' real payment capacity. Automating bill collection also frees up time for the sales team, allowing them to focus on attracting new clients and strengthening the user base.
Commercial focus on attracting new customers
Automating credit assessment for better portfolio management allows the commercial team to focus on creating new business opportunities and growing the client base. This is key to the sustainable growth of microfinance institutions, as it encourages the expansion of financial services to underserved segments of the population. By diversifying the client portfolio and reducing dependence on credit relocation, institutions are able to improve their performance indicators and respond to changing market needs.
The crucial role of AI and advanced analytics in microfinance
Artificial intelligence (AI) and advanced analytics in decision engines offer microfinance institutions a powerful tool to adjust their strategy in real time. These systems allow institutions to adapt their credit assessment policies, design customized payment schemes, and develop flexible financial products that align with their clients’ economic circumstances. AI also helps identify client segments that can benefit from preventive care and additional assistance, thereby reducing the risk of default before it becomes a problem.
Smart banking, supported by digitalization, self-service and automation of credit assessment, represents a significant evolution for the microfinance sector. With advanced tools such as decision engines, microfinance institutions can reduce non-performing loans, improve operational efficiency and increase their reach. In addition, they have the ability to easily implement AI models, therefore, they are key tools for agile model application. These solutions not only optimize credit management, but also promote financial inclusion and sustainability of the sector, adapting to the demands of the current financial environment and strengthening access to financial services for all segments of the population.
