AI in Credit: 5 Tips for Corporate Credit Analysts

GICP Expert View / 15 May, 2023

In the fast-evolving world of credit, staying ahead of industry trends and leveraging cutting-edge technologies is more than a competitive advantage—it's a necessity. One of the most transformative forces in the industry today is artificial intelligence (AI), with its ability to process vast amounts of data, uncover hidden patterns, and make predictions with unprecedented accuracy.

The utilization of AI goes beyond the mere automation of tasks. It facilitates deeper insights into clients' financials, industry trends, and market movements. By providing a more comprehensive understanding of a company's creditworthiness, AI enables analysts to make more informed decisions, manage risks more effectively, and even predict potential defaults before they occur.

Furthermore, AI-powered tools can process and analyze both structured and unstructured data from diverse sources, offering a more holistic view of a company's financial situation. This ability to leverage alternative data sources opens up new avenues for credit analysis, enabling analysts to consider factors that were previously difficult to quantify or analyze.

AI's real-time monitoring and early warning systems can help analysts stay alert to changes in a company's creditworthiness, allowing for proactive risk management. AI’s ability to identify industry-specific trends and risks adds another layer of depth to the analysis.

However, to fully leverage the benefits of AI, it's essential for corporate credit analysts to understand how to effectively integrate these technologies into their workflows. Here are five ways corporate credit analysts can make the most of AI in credit analysis:

Embrace AI-powered tools: Explore and integrate AI-driven platforms that can help you streamline processes, access diverse data sources, and enhance risk assessments. These powerful tools can significantly improve your workflow. For example, AI tools can automate the collection and processing of financial data, allowing analysts to focus on high-level analysis instead of tedious data gathering.
Leverage alternative data sources: AI can process vast amounts of structured and unstructured data, including unconventional sources like social media, news articles, and online reviews. Tap into these alternative data sources to gain a more comprehensive understanding of your clients' creditworthiness. For instance, AI can analyze social media sentiment to provide insights into a corporation's brand strength and customer satisfaction, which can indirectly impact creditworthiness.
Stay ahead with real-time monitoring: Utilize AI-based early warning systems and real-time monitoring to proactively identify potential issues and changes in creditworthiness. By staying alert to evolving risks and opportunities, you can mitigate credit risk and make better-informed decisions. As an application, AI can continuously analyze real-time financial data to provide instant alerts on potential credit risks, enabling timely response.
Deepen sector-specific insights with AI: Harness the power of AI to discern trends, risks, and opportunities unique to specific sectors. By interpreting vast amounts of industry data, it uncovers nuanced patterns, thereby enabling the generation of precise, insightful credit recommendations. For instance, AI can sift through extensive supply chain data and flag potential disruptions that could impact a manufacturing company's credit profile. This level of detail is often not feasible with traditional analysis methods, enhancing the precision and depth of credit assessments.
Continuously learn and adapt: The world of AI is constantly evolving, so it is important to stay updated on the latest developments and best practices. Attend webinars, workshops, and conferences, and network with industry peers to exchange knowledge and experiences to stay up-to-date with the latest AI tools and techniques for credit analysis.

About the Author

Aneta Buchert is a Senior Director at the Global Institute of Credit Professionals. She has over 15 years of capital markets experience, including 10 years in Debt Capital Markets origination at Merrill Lynch and Lloyds Banking Group. She also worked at the Bank of England, where she was a contributor to the AI Public Private Forum, and a participant in the AI in Financial Services working group at the World Economic Forum. Aneta holds an MSc in Management and Economics from ESCP Europe and City University London.