Trade Ledger’s AI Offer to Bankers

More and more corporate executives are climbing aboard the artificial intelligence bandwagon, with 45% of senior decision-makers telling Gartner their firms are expanding AI investments.

Of those executives who haven’t deployed AI, 70% say their companies are actively investigating AI uses, especially with generative AI.

“The generative frenzy shows no signs of abating,” said Gartner analyst Francis Karamouzis. “Organizations are scrambling to determine how much cash to pour into generative AI solutions, which products are worth the investment, when to get started, and how to mitigate the risks that come with this emerging technology.”

68% of executives also told Gartner the benefits of generative AI “outweigh the risks”, compared with just 5% that feel the risks outweigh the benefits.

“Initial enthusiasm for a new technology can give way to more rigorous analysis of risks and implementation challenges,” said Karamouzis. “Organizations will likely encounter a host of trust, risk, security, privacy, and ethical questions of trust, as they start to develop and deploy generative AI.”

One way financial services companies can gain access to existing and successfully deployed AI tools is through testing programs, especially at the beta level.

Take the SAS financial technology company Trade Ledger, which is now accepting applications from banks to join its new generative AI-enabled Working Capital Copilot platform beta program. The beta testing program is being deployed in partnership with Accenture.

Copilot, which is built on top of Trade Ledger’s data platform, “is the last component of the tech stack required to effectively crack open the $120 trillion embedded lending opportunity for working capital finance”, says Trade Ledger CEO Martin McCann.

London, U.K.-based Trade Ledger is only allowing a select volume of banks to participate in its beta program. That program is designed to give financial companies “exclusive early access to the world’s first generative AI interface for embedded complex business finance.”

The AI-based Copilot won’t be open to Trade Ledger customers until sometime in 2025, the company stated.

“The Trade Ledger data platform is already being used by banks such as HSBC and Barclays in 15 countries to cut the application to decision time for working capital finance to 48 hours,” Trade Ledger notes. “Copilot is built on top of the platform and will be available to banks participating in the beta program to distribute to their customers as a simpler way to understand and apply for working capital credit.”

The Working Capital Copilot beta program will work with participating banks to give business customers the ability to query their financial data to identify when and where they need capital. Via an API bank connection with the bank, the Copilot software digs up the bank lending products that clients require.

Cash Financing Dilemma for Small Companies

Most banking clients are small businesses with $10-50mm in revenues) “don’t have the resources or in-house expertise to analyze their cash-to-cash cycle and determine their working capital needs,” Trade Ledger notes. Copilot, which is built on the Azure OpenAI Service and accessed through Microsoft Teams, “uses advanced Large Language Models (LLM) to interpret conversational language queries about cash management and create algorithmic queries of the Trade Ledger database.”

The software handles a multitude of tasks, such as analyzing profit and loss statements, sales ledgers, supplier data, balance sheets, trading co-party behaviors, and credit bureau records, while providing actionable insights into invoices, payments, and other transactions impacting cash flow, Trade Ledger says.

By leveraging the bank and the API, small business clients can access real-time information on available working capital products, “with matched options based on cash flow status, creditworthiness, and specific business requirements,” the company adds.

The banking client company can move on to apply for capital funding via Microsoft Teams, with the decision process managed through the Trade Ledger platform.

“Applicants for the beta should see working capital lending as a core differentiator, and have an aggressive growth strategy for the assets on their balance sheet in the small to mid-market sector”, McCann says. “They should also have strong brand recognition, an appetite for change, and already be dedicating significant resources to digital transformation.”

“If growing the lending book two percent per year is OK, this program will not be right, nor will it be right for banks that believe transformation is just going from documents to optical character recognition (technologies),” he adds.

In other words, for Trade Ledger, which counts HBC, Microsoft, and Barclays among its client list, AI is the way – and it should be for banks and their clients, too.

Recent Posts

Leave a Reply

Your email address will not be published. Required fields are marked *