Certainly! Here’s the translation into American English:
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A recent study by Experian has highlighted how Machine Learning (ML) is transforming financial services in Spain, particularly in credit risk assessment. The research, conducted by Forrester Consulting, interviewed 109 senior executives involved in decision-making related to artificial intelligence and ML, showcasing the growing importance of these technologies in optimizing financing processes.
The data is striking: 93% of companies that have adopted ML have seen an increase in loan approval rates for small and medium-sized enterprises (SMEs). Additionally, 87% have reported improvements in credit card delinquency rates. For 73% of respondents, this trend not only represents a technical advancement but also a crucial competitive advantage that could redefine credit assessment in the long term.
Financial inclusion is a key pillar of this evolution. The study reveals that 75% of companies that have implemented ML agree that this technology provides them with the opportunity to offer access to financial services to previously underserved segments of the population. This includes consumers with limited credit histories, for whom ML allows for a more fair and equitable evaluation of their eligibility.
In terms of profitability, 86% of executives in Spain emphasize that ML facilitates better risk prediction and helps reduce delinquency. This combination of access and performance positions ML as a crucial strategic tool for the sustainable growth of the financial sector.
However, the automation and efficiency that ML brings could also lead to a future where many financing decisions are completely automated within five years, according to 66% of the executives surveyed. Generative artificial intelligence, in turn, is seen as a key tool for increasing productivity in credit risk management, with 73% of participants indicating its potential to simplify the development of new models.
Nevertheless, the report also points out that there are significant barriers to the adoption of ML. The cost of implementation, regulatory uncertainty, and the lack of internal expertise are major obstacles. Among those who have not adopted this technology, 65% doubt that the costs are justified by the benefits, while 69% express concerns about the transparency of ML models, and 62% fear failing to comply with relevant regulations.
In light of this situation, industry leaders have stated that improving profitability and reducing financial risk are prime objectives that can be achieved through the use of ML and richer datasets. Jorge Hernández, General Manager of Experian in Spain, emphasized that this technology not only assists financial institutions in their responsible growth but also plays a key role in creating a more inclusive and sustainable financial system. Mariana Pinheiro, CEO of Experian EMEA & APAC, highlighted how ML can expand access to financial services for millions of historically excluded individuals, underscoring its importance in designing a more equitable financial future.
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Referrer: MiMub in Spanish