Digitising Trade transactions for MSMEs – through Graph based AI

India’s MSME sector, a critical part of India’s vast economy, often struggles with one issue: securing finance, especially when they don’t have the documentation that banks usually seek. This issue gets even more difficult for businesses that are offline and have built their foundations on interpersonal relationships and trust rather than through a strong digital presence. But what if we could harness technology to quantify these trust-based relationships for financial evaluation? This is where Graph-based AI makes it more relevant for MSME Financing.

Leveraging Graph-based AI for Trade financing for India’s Micro and Small businesses

This actually means ‘Credit Rating of Transaction using Graph-based AI’. And this process does not need traditional documents.

Digitising trade transactions helps MSMEs access fast trade financing  

While urban cities and towns  see a growing digital adoption, a sizable chunk of MSMEs, particularly, those who are operating from semi-urban or rural parts of India, remain predominantly offline. Their operational ethos are built on long-standing community ties, word-of-mouth reputation, and direct customer interactions. In the eyes of conventional financial institutions, these businesses often appear as high-risk entities as they don’t have a digitized transactional history. These MSMEs would have had a hard time to get ‘finance for Cash Flow’ through traditional financing methods.

The Power of Graph-based AI for MSMEs

At its core, Graph-based AI, especially in the form of knowledge graphs, is designed to map and represent complex relationships between business entities in a networked environment. When applied to an offline business context, this technology can outline relationships with various stakeholders like suppliers, customers, and neighbouring businesses.

Knowledge graphs, with their detailed web of connections, can provide a multidimensional view of a business’s operations. By analysing the strength, frequency, and quality of these connections, financial institutions can draw invaluable insights into the business’s reputation, reliability, and overall creditworthiness.

A Practical case : A MSME in Madurai

Consider ‘Local Looms’, a cherished handloom enterprise that has been the pride of a bustling market in Madurai, for generations. They are not big on Digital space, but this does not mean that they are not reliable and smart in terms of business. In contrast to possible quick perceptions, they enjoy a strong community trust that is built over years.

Using Graph-based AI for this MSME in Madurai

1.Mapping the Relationships 

Through Public dataset and available Financial dataset like GST and other similar datasets, we can create a comprehensive knowledge graph for ‘Local Looms’. This graph would capture their interactions with raw material suppliers, collaborations with local artisans, regular customers, and even affiliations with neighbouring businesses.

2.Quantifying Reputation 

 Instead of a vague idea of trust, the AI system would analyze the depth and breadth of ‘Local Looms’ connections. A long-standing supplier relationship could indicate reliability, while endorsements from other businesses is proof of their community standing.

3.Transactional Health in Focus

Even in the absence of digital transactions, the graph can be enriched with data about offline transactions. For instance, details about recurring orders, payment timelines, and business agreements can provide insights into the business’s financial health.

4.Risk mapping and Mitigation  

By scrutinizing the health and stability of ‘Local Looms’ connections, potential risks can be flagged. A diversified and robust network might signify a lower risk profile, whereas over-dependence  on a few entities could be a potential vulnerability.

The Future of MSME Financing 

With Graph-based AI & LLM (Large Language Model), the future of MSME financing in India appears brighter and more inclusive. This technology promises to transform the very culture of credit evaluations, moving away from a rigid paper-based approach to one that genuinely understands and appreciates the rich and extensive network of relationships that define businesses like ‘Local Looms’. As we move forward, technologies like these promise and enable a more equal and fair financial ecosystem for MSMEs across India.

Credit  : Pradeep Kumar, Head – Strategic Data Solutions & Analytics 

(You can read our one more article on ProFinTech’s Knowledge Graph and how we leverage data-driven approach that allows 360 degree visibility to trade-based cash-flows and business performance of a MSME/an entrepreneur, in order to establish his/her creditworthiness and risk profile, here )