The latest Experian study, carried out by Forrester Consulting, reveals that Machine Learning (ML) is transforming decision making in the financial services and telecommunications sectors in eleven countries in EMEA and Asia-Pacific. Specifically, in Spain, 109 senior managers in charge of making decisions related to the development and implementation of AI/ML in the area of credit risk have been interviewed. The results show how ML is helping businesses improve access to financial services, reducing risk, and accelerating automation, while also highlighting the barriers that still hinder broader adoption.
ML as a driver of financial inclusion and sustainable growth
The report shows how ML is enabling businesses to expand access to financial services for underserved segments, particularly for consumers with limited credit histories and the underbanked. By incorporating richer alternative data sources, ML models enable more accurate eligibility assessments, helping providers make fairer and more inclusive decisions.
According to the report, 75% of those who have adopted machine learning in Spanish companies agree that this technology allows them to expand access to financial services, responsibly serving new customer segments that are often excluded by traditional credit scoring models.
At the same time, 86% of Spanish respondents declare that ML improves profitability by optimizing risk prediction and reducing delinquencies. This dual impact, expanding access while improving financial results, positions ML as a strategic asset for organizations seeking to grow sustainably.
Automation, efficiency and cost savings, main benefits of ML
Nearly three-quarters (74%) of ML users cite improved accuracy and operational efficiency as key benefits. These capabilities enable financial institutions to increase automation with confidence, with more than two-thirds agreeing that ML allows them to automate more credit decisions – reducing manual workload and speeding up response time. Looking to the future, 66% of Spanish managers believe that, within five years, the vast majority of financing decisions will be fully automated.
Generative AI is emerging as a powerful productivity tool in credit risk management
Generative AI (GenAI) is emerging as a powerful productivity tool, particularly in particularly time-consuming areas such as model documentation and business intelligence. Nearly three-quarters (73%) of respondents believe GenAI can significantly reduce the time and effort required to develop and implement new credit risk decision-making models.
59% agree that the biggest advantage of GenAI lies in simplifying regulatory documentation, enabling faster validation cycles and improving collaboration between risk and compliance teams.
Organizational resistance to ML adoption persists
Despite these benefits, some organizations remain cautious. The report shows that cost, regulatory uncertainty and lack of internal knowledge are the main barriers to ML adoption. Nearly two-thirds (65%) of non-users believe that the cost of implementation does not outweigh the perceived benefits, while 59% admit that they do not fully understand the value that machine learning can bring.
Concerns about explainability and regulatory compliance also persist, as 69% of those who have not adopted the technology in our country are concerned about the transparency of the models, and a similar percentage (62%) fears not aligning with regulations. These challenges are compounded by legacy IT and data infrastructures, which 67% consider unprepared to support machine learning implementation. However, the report also notes that many of these concerns stem from misconceptions, as modern machine learning models can be explainable and regulatory compliant, and third-party platforms can help close skills and infrastructure gaps.
“The report highlights that improving profitability is a key priority for managers.” the ability to improve accuracy in decision making and reducing financial risk is key to achieving this. And machine learning enables this by leveraging richer data sets that were not possible before. This offers financial institutions to grow responsibly, become more inclusive and support social progress.”adds Jorge Hernández, General Manager Experian in Spain.
