AI Transforms the Credit Market Lending Process

Empresas & Negócios

Sep 30, 2024

When discussing artificial intelligence (AI), it often brings to mind associations with science fiction scenarios, where autonomous robots replace humans in various tasks and,

Transforming the Credit Market: The Strategic Role of Artificial Intelligence

Cristiano Oliveira – Associate Professor at the Federal University of Rio Grande and Head of Research at Rivool Finance

When talking about artificial intelligence (AI), associations often arise with science fiction scenarios, where autonomous robots replace humans in various tasks and, in extreme cases, take control of the world. Although this scenario is still far away, recent advances in AI are undeniably impressive. Large-scale language models (LLMs) are automating complex tasks with high accuracy, security, speed, and efficiency.

AI's potential to revolutionize processes and decisions in the credit market is difficult to predict accurately, but its transformative impact in many industries, especially in the business world, is already evident. The credit market, dealing directly with large volumes of data and essential information, is a clear example of AI's potential to revolutionize.

The credit market plays a key role in the global economy by facilitating access to capital for businesses and individuals. However, it faces persistent challenges, such as information asymmetry, where lenders often lack complete and up-to-date data to assess risks properly. In addition, traditional methods of credit analysis are known for their slowness and high costs. AI emerges as a solution to these challenges, transforming credit decisions.

One of the most promising applications of AI in the credit market is the automation of credit-granting processes. Traditionally, this process involves the detailed analysis of large amounts of data and documents, which can be time-consuming and prone to human error. However, AI tools can quickly review documents, identify fraud, detect missing data, and perform automated analysis, thereby automating and optimizing the credit-granting process.

AI also significantly increases the accuracy of credit risk models. Using predictive algorithms, known as machine learning, financial institutions can identify patterns in vast volumes of data that would otherwise go unnoticed by traditional methods. This improved analytical capacity results in safer decisions with lower default rates.

After credit approval, AI can streamline and speed up contracting processes by drafting legal contracts and automatically communicating with customers about credit decisions and next steps. In portfolio monitoring, AI tools can automate performance and risk reports and proactively identify borrowers or segments that need special attention using real-time data.

Financial institutions can expand their operations with more efficient processes and faster credit decisions without increasing costs proportionately. This benefits the institutions and makes credit more accessible and competitive for borrowers, promoting financial inclusion.

Several institutions are already leading the implementation of AI to transform their credit processes. A recent McKinsey study, which surveyed credit risk executives from 24 financial institutions, including nine of the ten largest banks in the United States, revealed that 20% have already adopted AI in at least one area of their operation, while another 60% plan to do so within a year. Even the most cautious executives believe that AI will be essential to their credit risk management processes in the next two years.

In summary, artificial intelligence's application in the credit market offers significant advances, allowing for faster and more accurate analyses and reducing operating costs. With the continuous development of AI, new opportunities arise, such as the creation of innovative credit models and advanced risk analysis forms. Institutions that adopt these technologies strategically will be at the forefront of the technological revolution, shaping the future of credit and ensuring its competitiveness in the coming decades.