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Distressed debt, the securities of companies facing severe financial difficulties, presents significant investment opportunities for private debt funds. However, identifying and evaluating these opportunities can be complex and risky. The integration of technology is rapidly transforming how private debt funds assess distressed debt, making the process faster, more efficient, and data-driven. In this blog, we examine some of the crucial ways in which technology is reshaping this investment strategy. Plus, we explore some of the specific features of AXIS by AIO Logic that allow lenders to transform their distressed debt analysis!

1. Data Aggregation and Analysis

Private debt funds need to sift through vast amounts of data to assess distressed companies, including financial statements, market data, and more. AI-powered data aggregation platforms have simplified this process by automating the collection of both structured and unstructured data, pulling information from multiple sources quickly and accurately. These tools use machine learning algorithms to detect early warning signs of financial distress, such as breaches of debt covenants or declining revenues. By reducing the need for manual data analysis, private debt funds can evaluate more distressed debt opportunities faster, giving them a competitive advantage.

Data aggregation and analysis are crucial to any type of financial investment, but this is especially true relating to distressed debt, due to the uncertainty surrounding borrower finances. Within AXIS by AIO Logic, data aggregation and analysis are both addressed in quite powerful ways. AXIS’s AI aggregates data from multiple sources, such as loans, payments, balances, and other metrics. This enables comprehensive data analysis and reporting, providing valuable insights for decision-making. Additionally, AXIS’s AI rigorously analyzes vast amounts of data quickly and accurately to automate real-time borrower financial health monitoring, collateral analysis, and portfolio risk.

2. Predictive Analytics

Predictive analytics helps private debt funds assess the future performance of distressed companies. By analyzing historical data and applying machine learning models, funds can forecast a company’s creditworthiness and potential for a financial recovery. These tools use financial and industry-specific data to offer a clearer picture of potential investment outcomes. This data-driven approach enables investors to make more informed decisions, reducing risks and improving the chances of identifying distressed debt with strong recovery potential.

Using predictive analytics to assess the creditworthiness of potential borrowers prior to issuing the loan is crucial when lending to borrowers in financial distress. AXIS’s AI can analyze a wide range of data points (e.g., financial statements, transaction history, market data) to assess the creditworthiness of borrowers, providing more accurate and dynamic underwriting. As part of this analysis, AXIS automatically performs vertical, horizontal, and trend analysis on borrower financials to calculate 42 financial ratios and score the borrower financial health.

3. Risk Management and Monitoring

Risk management is critical in distressed debt investing due to the uncertainties surrounding the borrowing company’s financial health and future. AI-powered tools can help lenders identify potential risks and vulnerabilities early, giving them the ability to potentially mitigate those risks proactively. These tools can also analyze financial and loan data to identify early warning signs that a borrower’s financial health may become an issue. By gaining a clearer understanding of the risks, funds can make better-informed decisions and adjust their strategies as new information becomes available.

When building AXIS by AIO Logic, we placed a heavy emphasis on helping lenders navigate and mitigate risk, both prior to and after issuing the loan. AXIS’s AI can identify unusual patterns and behaviors that may indicate fraud or other risks, enabling institutions to respond quickly to potential threats. Furthermore, AXIS’s AI identifies patterns and risk factors in financial, collateral, and loan data to proactively manage risk by identifying early warning signs. In short, AXIS helps lenders know what risks they may be facing so they can take action to mitigate those risks before they negatively impact the investment.

4. Automation in Due Diligence

Due diligence is a vital but labor-intensive part of evaluating distressed debt. Traditionally, private debt funds would manually review financial statements, legal documents, and operational data. Automation tools like Robotic Process Automation (RPA) and Natural Language Processing (NLP) streamline this process by quickly extracting critical data from lengthy and complex documents. These tools help funds assess more opportunities in less time, improving their ability to act swiftly on distressed debt investments. Automation also reduces the risk of human error, providing a clearer understanding of a company’s financial and legal standing.

Within AXIS by AIO Logic, we have included several automation and AI features in the due diligence process. Among these features are our AI Document Parser, which unlike traditional OCR technology, reads entire documents (e.g., financial statements, AR Agings, etc.) and translates the information into structured fields. This allows for more accurate data extraction and utilization within our platform. Additionally, AXIS provides robust integrations for automated diligence verification with D&B, Clear, Lexis, and many others.

5. Alternative Data for Deeper Insights

Alternative data sources such as transaction history and market data provide unique insights into distressed companies that traditional financial reports may not capture. By incorporating alternative data, private debt funds gain a more comprehensive view of a company’s real-time performance and potential recovery. This deeper understanding can help uncover hidden risks or opportunities, enabling funds to make more informed and timely investment decisions.

While AXIS offers powerful assessments of data in the underwriting process, we didn’t stop there. AXIS also provides ongoing analysis of data such as financial statements, transaction history, and market data to allow for ongoing financial health monitoring. Additionally, AXIS’s AI enables automated ingestion, structuring, and centralization of unstructured source data such as borrowing bases and loan tapes, reducing data entry costs and errors while also making automated downstream analytics possible.

Conclusion

Technology is revolutionizing how private debt funds assess distressed debt opportunities. With tools like AI-driven data aggregation, predictive analytics, scenario analysis, automation, and alternative data, funds can analyze distressed assets more effectively, reduce risks, and seize investment opportunities faster. As distressed debt continues to offer high-reward potential, funds that embrace these technological innovations will be better positioned to succeed in this competitive market. If your firm is seeking to transform its distressed debt analysis capabilities, please feel free to contact us today to schedule an intro call and learn more about all that AXIS has to offer.