AI-driven insights: The cornerstone of supply chain finance

Supply chain finance comprises innovative financing products that offer businesses the opportunity to optimize their cash flow by lengthening their payment terms with suppliers while also enabling their suppliers to get paid early. With the expansion of global supply chains, where buyers and suppliers from different countries work with each other, corporations face the challenge of unlocking trapped working capital within these complex networks.

Supply chain finance serves as a win-win solution, enabling buyers to optimize their working capital and suppliers to generate additional operating cash flow. It also allows businesses to extend payment terms while offering early payment options to suppliers, making it an approach that minimizes risk and fosters a mutually beneficial relationship across the entire supply chain.

Proactive credit risk and supplier risk assessment and monitoring
For the growth of Supply Chain Finance as a method of financing, proactive Credit Risk and Supplier Risk Assessment and Monitoring of buyers and sellers constituting modern complex Supply chains is imperative.

Traditional credit and supplier risk assessment of B2B counter-parties relied on historical financial data, credit scores, and manual evaluation processes. Artificial Intelligence (AI), with its ability to process vast amounts of data quickly and uncover hidden patterns, is changing the paradigm because it can integrate structured data from a wide variety of data sources such as financial statements, payment history, market trends, and even unstructured data from news articles and social media, transforming B2B risk assessment and monitoring in a multitude of ways.

• Risk analytics models help supply chain finance platforms, banks, and Non-Banking Financial Corporations (NBFCs) assess and quantitatively score the credit and supplier risk of customers and suppliers, respectively. This helps them make informed decisions on whether to fund transactions between specific business entities or not.
• Early warning signal data is gathered on a near-real-time basis through time risk monitoring platforms to help supply chain finance platforms, banks, and NBFCs monitor changes in the risk profile of all players whose supply transactions they have funded.
• AI can provide scenario analysis to assess the potential impact of changes in different risk factors on the buyers and sellers in the supply chain, helping supply chain finance platforms, banks, and NBFCs proactively predict and mitigate their risk exposure.

Fraud detection
As per the Association of Certified Fraud Examiners (ACFE), 97% or more of fraud examiners consider analytics to be an indispensable tool in increasing the efficiency of their fraud detection programs. Little wonder then that AI is revolutionizing fraud detection in supply chain finance.

By harnessing advanced algorithms and machine learning techniques, AI systems can meticulously analyze massive volumes of data associated with transactions in the supply chain. These systems excel at identifying intricate patterns, anomalies, and irregularities that may indicate fraudulent activities, such as invoice manipulation, fictitious orders, or unauthorized fund transfers.

AI models learn from historical data and continuously adapt to the evolving tactics of fraudsters, thereby enhancing fraud detection capabilities over time. By bolstering the accuracy and efficiency of fraud detection, AI not only safeguards financial integrity but also fosters trust among supply chain stakeholders, ensuring smoother operations and sustained growth.

Optimization of working capital management
The importance of supply chain finance lies in its ability to optimize working capital for both buyers and suppliers and AI can transform working capital management in supply chain finance. AI-powered systems provide critical insights that empower organizations to streamline their working capital strategies by analyzing intricate networks of transactions, inventory levels, payment cycles, and market trends.

These systems forecast demand patterns, enabling precise inventory management and reduction of excess stockpiles that tie up capital. Additionally, AI assists in predicting cash flow fluctuations, enhancing the accuracy of budgeting and liquidity planning. Through real-time data analysis, AI helps in identifying bottlenecks, optimizing payment schedules, and negotiating favorable terms with suppliers. The result is an efficient approach to working capital management.

Invoice and payment processing
AI offers a transformative solution to the cumbersome process of invoice processing in supply chain finance. It automates data extraction from a variety of invoice formats, minimizing errors and accelerating the entire lifecycle from receipt to approval. Additionally, AI-enabled systems can cross-reference invoices against historical data, supplier agreements, and market benchmarks, ensuring accuracy and compliance.

When it comes to payment processing, AI optimizes cash flow by predicting payment cycles, flagging discrepancies, and prioritizing payments strategically. By swiftly identifying potential delays or anomalies, AI aids in mitigating operational disruptions and late fees. The combined impact of AI in both invoice and payment processing results in streamlined operations, reduced costs, and enhanced financial transparency, fostering a resilient and efficient supply chain finance ecosystem.

AI's multifaceted impact on supply chain finance
The positive impact of AI spans efficiency gains, better credit and supplier risk assessment and monitoring, and a quicker invoice-to-cash cycle for businesses. For Supply Chain Finance platforms, banks, and NBFCs, AI is a vital tool that helps manage risk and minimise fraud, enabling them to grow their portfolios confidently.

-- Mohan Ramaswamy, CEO and Founder, Rubix Data Sciences.