AI Tools Can Uncover Hidden Risks in Private Credit, Says Eltech.ai CEO

Structural Issues in Private Credit

• 💡 Private credit has historically faced collapses due to issues within actual companies and specialty finance lenders attempting to defraud investors.
• 📌 A major problem lies in the complex "true sale" structures, often off-balance sheet, making it difficult to analyze the entirety of assets like receivables and inventory.
• 🎯 Despite these complexities, private credit continues to attract investors due to the yields it provides.

Credit Quality and Fraud Concerns

• 📊 The overall economy and strong interest rates have supported credit quality in private credit.
• ⚠️ However, a significant concern is fraud, with billions of dollars disappearing from investors' pockets in recent years.
• 🚀 The rise of AI technology and creative solutions makes it easier for bad actors to defraud lenders, who are often slower to adopt innovative underwriting and analysis methods.

Detecting Early Signs of Distress with AI

• 🔍 AI is highly effective at repetitive tasks, such as verifying invoices backed by supporting documents like shipping or customs information.
• ⚡ By plugging in various data types, AI can determine the authenticity of an invoice in milliseconds, a task that would require thousands of people manually.
• ✅ This capability offers a tremendous opportunity for the private credit and trade finance industries to understand the scope and transactional documents of investments, provided there is sufficient domain expertise in the data.

The Role of Technology in Underwriting

• 🧠 Lenders, whether non-bank or traditional banks, must acknowledge and understand that technology is crucial for analyzing investment risks.
• 📈 AI agents can be trained on specific tasks to analyze the entirety of a picture and investment risk before lending.
• 🧩 Understanding supply chain, shipping, and invoicing documents is paramount for effective underwriting in this evolving landscape.