Trade Ledger: A Disruption in Trade Bureaucracy
Martin McCann, CEOThe same report also states that an increment of 10 percent in trade finance would enable SMEs to recruit in average, 1 percent more employees. Therefore, since trade finance has additive effects on employment, in absence of its underlying support, trade opportunities that create growth and jobs are lost.
Answering these questions and addressing the socio-economic development issue of unmet trade finance demands is Sydney-based fintech firm, Trade Ledger.
The company has developed a unified digital business-lending operational platform that creates a channel to support all major types of cash flow lending products, from invoice funding to debtor financing, to supply chain financing. According to Martin McCann, CEO of Trade Ledger, “A highly problematic reality is that most of the world’s SMEs are considered credit-unworthy when the truth is that the credit modelling and underwriting processes are simply set up to deal with MN’s and large corporations and cannot address the SME market. We are solving that market problem with technology.”
Trade Ledger is reimagining the future of business lending technology—Banking as a Service
Trade Ledger offers a unique range of solutions for corporate lending in its platform-as-a-service model. One of its components, Credit and Fraud Analysis, calculates the entire depth and breadth of credit and financial metrics, directly from the business’s financials system. It also provides definitions of each metric, along with the relevancy and parameters considered behind calculation, creating a truly accurate picture of credit worthiness in real time. On the other hand, Trade Ledger’s B2B e-commerce platform also allows banks to customize risk and credit processing variables according to policies that suit their needs. The platform, which runs on AWS, can autonomously update invoice status, offer transparent credit rating summary, and collect requisite customer details for a seamless approval and instantaneous transfer of business loans. Cumulatively, the digital lending platform covers every aspect of business lending, from customer application and on-boarding, to due diligence, settlements and payments.
To better elaborate the applicability and efficiency of Trade Ledger, McCann cites a case study of an Australian alternative lender, who was amongst the first adopters of the solution. The firm previously had to execute manual and time consuming processes, owing to its dispersed and non-connected credit decision-making, customer engagement, CRM, and financial data systems. Moreover, their legacy systems failed to guarantee consistency of applying risk and credit policies country-wide, which caused grave financial risk for the business. To mitigate these ever-growing challenges, Trade Ledger digitized the company’s complete array of offerings, and automated their back-office operations. This resulted in a much-improved lending facility, structurally speaking, at a far lower cost. Trade Ledger also implemented new and numerous automated risk controls in their operations, which significantly raised the client’s profit margins, while reducing risk.
Advancing its platform for future, Trade Ledger is now incorporating AI, machine learning, Distributed Ledgers and service bots, which would substantially add to the platform’s predictive capabilities and banking industry utility. With further expansion plans in Singapore, New Zealand, Hong Kong, Malaysia, Europe and the USA, Trade Ledger is definitely re-imagining the future of business lending technology— Banking as a Service.
Trade Ledger News
Small and medium-sized businesses often lack the resources or in-house expertise required to access and interpret information for optimizing the cash-to-cash cycle. To address this challenge, Trade Ledger has developed the Working Capital Copilot, leveraging Azure OpenAI Service. This solution employs advanced Large Language Models (LLM) to understand conversational language queries related to cash management, generate algorithmic queries, and provide actionable insights.
The new Generative AI interface interacts with the data securely collected by Trade Ledger about a business and its trading practices. Users can access this interface conversationally within the Microsoft Teams platform. It will also be made available through banks, simplifying the process for their customers to comprehend and apply for working capital credit.
Martin McCann, CEO and co-founder of Trade Ledger, emphasized the importance of delivering working capital solutions via a conversational interface within Microsoft Teams, as it represents a scalable approach to embedded business lending.
The Working Capital Copilot assesses various financial data sources, including profit and loss statements, sales ledgers, supplier data, balance sheets, trading partner behaviors, and credit bureau records. It then provides actionable insights related to invoices, payments, and other transaction data.
Through API integration with banks, real-time information about available financial credit products is made accessible, along with matched options based on cash flow status, creditworthiness, and specific business requirements. This enables users to apply for the optimal solution directly within the Microsoft Teams chat.
Bill Borden, Corporate Vice President, Financial Services Industry at Microsoft, highlighted the significance of Trade Ledger's Bank solution, which integrates Trade Ledger's data model and solutions with Azure OpenAI Service, providing commercial banks with the opportunity to harness Generative AI in a powerful, compliant, and secure manner for the benefit of their business customers.
The Working Capital Copilot solution is scheduled for general availability in 2024 via the Microsoft Commercial Marketplace. Banks interested in participating in the beta program can get in touch with Trade Ledger representatives.