72% of Spanish Executives See AI as Key to Gaining a Competitive Edge in the Market
Experian has released a new report analyzing the perspectives of decision-makers in four key areas: strategic priorities, data and analytics, technology, and risks. One of the key takeaways is the role of Generative Artificial Intelligence (GenAI) in helping business leaders enhance decision-making and focus on customer experience, especially in a challenging economic environment.
The report highlights two critical factors: the benefits of implementing AI to achieve competitive advantages and the need to invest in analytical tools and infrastructure. Jorge Hernández, General Manager of Experian Spain, points out that many companies still face challenges in developing AI models.
Technology Disruption and Competitive Advantage
According to the report, technological disruption is seen as the third most influential external factor for companies over the next two years. Executives emphasize the importance of AI in boosting efficiency and reducing costs. In fact, 72% of Spanish respondents believe that competitive advantage will depend on their ability to leverage AI, compared to 68% globally. Furthermore, 77% of tech leaders in Spain are exploring GenAI applications for the upcoming year, slightly above the global average of 73%.
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AI's Impact on Risk Assessment
Additionally, 74% of Spanish executives (67% globally) believe GenAI will significantly improve risk assessment. The use of alternative data sources through AI is the main focus for 67% of Spanish executives, showcasing its potential to extract valuable insights from non-traditional data sets.
Access to centralized data platforms is also considered crucial for optimizing risk strategy. Half of the Spanish executives (50%) anticipate increasing credit pressures in the next year (47% globally), though only 41% have recently tightened their lending criteria.
Identifying Financially Vulnerable Customers
In Spain, 42% of risk managers prioritize identifying financially vulnerable customers. This is vital because integrating data and analytical tools, along with AI, provides a more comprehensive view of customers and accelerates risk analysis and credit decisions, leading to stronger relationships and fairer lending practices.
Challenges in AI/ML Model Development
Data managers are prioritizing the integration of datasets into a single platform to improve their analytical capabilities and reduce the time required to develop AI/ML models. Currently, 70% of Spanish respondents (55% globally) believe that the development of AI/ML models is too slow. Meanwhile, 66% are updating their models more frequently to adapt to changes in credit behavior.
A key challenge highlighted is the lack of alternative data sources, which limits the success of analytics programs. However, advanced cloud-based AI capabilities can efficiently process and analyze complex data sets, improving the accuracy of predictive models and enabling a more comprehensive assessment of credit risk.