Hey everyone,

If you’ve been following DeFa, you already know we’re all about pushing boundaries blending traditional finance with blockchain through invoice factoring and pioneering Real World Revenue (RWR) APYs. Today, we’re excited to share how we’re taking our InvoiceFi capabilities to the next level by embracing Large Language Models (LLMs).

In this article, you’ll see exactly how LLMs fuel our “Know Your Invoice” (KYI) system and streamline credit operations. We’ll also walk through parts of an Audit Report (the 22 images you’ve seen) to show how data analysis underpins everything we’re building.

In the world of invoice factoring, precision, speed, and trust are crucial. Our LLMs—trained on proprietary datasets specific to InvoiceFi—help us do everything from spotting anomalies in documents to generating parts of credit memos automatically. That means less manual work for back-office teams, faster turnaround times for businesses, and more consistent decisions for investors.

Much like our approach to DeFi (where real-world assets back stable yields), our approach to AI is about practicality. We’re not chasing buzzwords but targeting measurable improvements such as fewer errors, quicker credit approvals, or more transparent KYI reports.

1. Risk Assessment & Fraud Detection Our LLMs ingest data like invoices, transaction records, and supporting documents. If there’s a mismatch—say, an invoice date doesn’t align with the shipping date—the system flags it automatically. This helps us maintain the authenticity of invoices and ensures that the yields you see are backed by genuine economic activity.

2. Credit Decisioning By analyzing a company’s financials, LLMs can quickly generate a draft credit memo, highlighting key ratios, revenue growth, or red flags. A credit officer still reviews everything, but the heavy lifting—like extracting data and comparing it to typical thresholds—happens in the background.

3. Post-Credit Stage Once credit is approved, LLMs also draft legal contracts, handle routine follow-ups, and even communicate rejections with detailed explanations. In short, it lightens the load on our human team so they can focus on higher-level tasks.

To give you a sense of how deeply we rely on data, we’ve compiled a 22-page KYI Audit Report that breaks down how our LLMs assess a company’s financials. Each set of pages digs into distinct metrics—covering risk, liquidity, profitability, and more:

• Pages 1 – Cover & Intro (DeFa Audit Report, 4 September 2024)

• Pages 2–3 – Financial Score & Efficiency (asset management, inventory, receivables)

• Pages 4–5 – Liquidity & Solvency (current ratio, quick ratio, total debt levels)

• Pages 6–7 – Profitability & Growth (operating margins, net worth changes)

• Pages 8–9 – Financial Charts & DuPont Analysis (net sales, cost of goods sold, deeper ratio insights)

• Pages 10–11 – Altman Bankruptcy Prediction & Industry Comparisons (manufacturing vs. non-manufacturing)

• Pages 12–14 – Activity & Liquidity Ratios (DSO, DOH, cash conversion cycle)

• Pages 15–16 – Profitability Ratios & Growth (year-over-year margin trends)

• Pages 17–18 – Disclaimer & Balance Sheet (legal scope, breakdown of assets, trade receivables)

• Pages 19–21 – Liabilities, Stockholders’ Equity & Income Statement (debt, retained earnings, EBITDA)

• Pages 22–23 – Profit Before Tax & Final Note (net profit summaries, closing statement)

Click here to check DeFa’s LLM Generated Full KYI Audit Report

In addition to the main report, we’ve introduced a Financial Analysis Detection Report as a high-level snapshot. It offers:

• DuPont Analysis in a succinct table (ROI, net profit/sales, total assets/equity)

• Altman Z’ Score Comparisons for manufacturing vs. non-manufacturing

• Sector Averages for net sales growth, equity growth, net profit margin, and more

• Sidebars on Productivity, Liquidity, and Debt for instant performance cues

While the 22-page audit provides a deep dive, the Detection Report is closer to a cheat sheet—perfect for rapid decision-making. Both are generated by our DeFa LLM and serve the same purpose: making InvoiceFi more data-driven, transparent, and efficient.

Click here to check DeFa’s LLM Generated Financial Analysis Detection 1-Pager Report

We know AI can be a double-edged sword, especially when it comes to sensitive tasks like credit approval. That’s why we’re focused on responsible AI use. Our LLMs serve as a first pass—pulling key data, spotting irregularities, and drafting routine documents. Real humans remain in the loop for final approvals and for addressing complexities that an algorithm can’t handle alone.

That’s the crux of our long-term approach: automation where it makes sense, oversight where it matters, and constant iteration to make sure we’re delivering real value in InvoiceFi.

If you’re as excited as we are about the potential of LLMs to streamline invoice factoring, we’d love to hear your thoughts. Our platform is evolving rapidly, and your feedback—just like with the DeFa testnet—helps us refine our processes so we can offer a consistent, transparent, and user-friendly experience for everyone.

Check Out Our Full KYI Audit Report We’ve shared the 22-page breakdown (listed above). Take a look at the sections that pique your interest and see how LLMs handle everything from liquidity ratios to Altman scores. It’s all part of our mission to make InvoiceFi more intelligent, more efficient, and more accessible.

Thanks for Reading We genuinely believe combining the power of LLMs with real-world invoice financing is the future—and we’re eager to shape that future alongside you. If you have any questions, suggestions, or want to discuss any part of the KYI report, drop us a line or reach out through our community channels.

—The DeFa Team is Building a better InvoiceFi ecosystem, one innovation at a time.