In the past, lending has been difficult and expensive. According to Trade Ledger Ledger, 200 million companies globally have struggled to get the credit they needed, when they needed it.

Five years ago Matthias Born and Martin McCann got their heads together over a beer in a Sydney pub to tackle banking's most challenging technology puzzle – how to streamline lending and credit decisioning in a highly regulated, risk averse and competitive industry.

They created Trade Ledger as a lending Software as a Service (SaaS) tool, embedded within customers’ online credit application process, that transforms their ability to lend to any growth business in need of capital. Matt and Martin pioneered a shift in mindset for the finance industry towards data-driven lending and the adoption of the document data model as the most powerful way to manage and use financial data.

By rethinking lenders’ approach to managing data, the company has signed global and regional banks and alternative lenders, and grown exponentially, tripling in size over the past year. It now employs over 120 people in Australia and the UK. Trade Ledger is backed by venture capitalists Point72 Ventures, Foundation Capital and Hambro Perks, and individual investors such as Court Lorenzini (the founder of DocuSign).

“The past few years have been transformational. We've demonstrated to the finance industry that there is a better way to use data. MongoDB provided us with a great foundation for our data strategy. We've been helping financiers to lend more, at lower risk, faster and for greater profit.” said Matt Born, CTO and co-founder of Trade Ledger."

Businesses poised for growth, both large and small, are the backbone of the global economy, providing the lion’s share of employment and driving productivity. However, often they find it difficult to access the funding they need to realize their full potential.

Trade Ledger addresses this challenge and unlocks capital by gathering and analyzing data to facilitate credit decisions for banks and non-bank lenders.

According to Matt: “Lending is about having quality data sources to make informed decisions regarding the provision of lending facilities to businesses, and to enable lenders to enhance their credit risk profiles on an ongoing basis as they lend.”

Trade Ledger discovered three big technology challenges that hinder lenders from providing more credit:

• Transparency - Siloed data sitting within spreadsheet and text documents across the financial institution and across multiple different departments;
• Auditability and traceability -There are frequent data changes across the different data sources, new copies are created, and it’s difficult to keep track of the data changes over time as well as constantly evolving data sources.
• Enforcement of business rules - There are very strict regulatory and security landscapes in each market, and different products adding layers of complexity into the lending process; manual activities do not comply with regulatory requirements.

Neither Martin nor Matt are professional bankers. ”As technologists and entrepreneurs, we were able to look at the problem space completely differently - through the lens of data. We started challenging all the elements of the underwriting and decision-making processes that could be enhanced and simplified using technology, and more importantly using access to digital data sources,” Matt said. The team has grown significantly since and attracted banking experts across the globe, which provide the banking lens into the technology solution.

Trade Ledger’s software meshes together different digital datasets to get a much clearer understanding of a borrower’s finances. This leads to better decisions faster, as well as lower costs, with a better customer experience.

To build a better way, Trade Ledger had to overcome some significant technology hurdles. And that’s where MongoDB came in, providing the document database that is the backbone of Trade Ledger’s solution.

The document data model stores data as a single document, which is more flexible and natural for a developer to work with. Given the massive variety of data types and data sources, the rows and columns of a traditional relational database would have been too restrictive and brittle as the product evolved.

The flexibility of the document model allows Matt’s team to bring data from multiple sources with different schemas into a single data source without writing long lines of code or breaking the database. The data sources can change, and MongoDB can accommodate these changes automatically. Matt also wanted this flexibility within a managed service which could take the operational and management burden off his small team. “We’ve always been firm believers in the benefits of document-oriented storage as a means to rapidly drive and enhance the product offering,” said Matt.

Matt Born, CTO and co-founder of Trade Ledger

Trade Ledger launched the first version of its products within six months of the pub conversation. From the earliest days, the entire platform has been underpinned by MongoDB Atlas, the fully managed cloud database service, running on AWS.

“Our focus is building the core lending systems and we are really good at that, which frees the banks and other lenders to focus on their core strengths,” Matt said

However, Atlas does more than helping Trade Ledger build faster with a smaller team. MongoDB Atlas's fine-grained data management tooling allows Trade Ledger to give its customers and partners full confidence that data is secured, isolated from other data sets and stored in specific regions, in compliance with local data laws.

The data-driven business lending revolution is only just beginning, but Trade Ledger is already proving how much of an impact it can have across multiple credit products. MongoDB Atlas's flexibility, adaptability, and speed to market is helping Trade Ledger deliver incredible improvements – customers are reporting a 50 per cent increase in conversions with a 50-70 per cent reduction in costs.

The lending experience for businesses has also been fully transformed. It can now take as little as four minutes for a borrower to apply for a loan online, compared with 30 hours via traditional credit applications. Loans can be approved within an hour, and first drawdown time has been reduced to as little as a day, down from typically 90 days previously.

The enormous progress Trade Ledger has made pioneering data-driven lending is paving the way for it to innovate with other new products, including services to provide an end-to-end credit management system.

“Data and data-driven lending is becoming accepted as the best way to enhance credit decisioning. To deliver that, we don’t want to spend time thinking about the mechanics of how we acquire the data, it’s much more important to focus on what we can do with the data and how we can improve the lending experience overall. Which is why Atlas is such a good fit for us.” Matt Born, CTO, Co-Founder

Matt Born, CTO and co-founder of Trade Ledger