Case Study: Using financial data enrichment to close data gaps in underwriting with Wayflyer

Technology has shaken up every industry as well as creating new ones.  Nowhere is this more prevalent than with commerce.  No longer restricted to physical brick and mortar shopping, “e-commerce” has exploded onto the scene, initially during the 1990s with the adoption of the internet and has only accelerated from there with the introduction of smartphones and mobile shopping.‍

Whilst it has never been easier to create an ecommerce business due to platforms like Amazon and Shopify, scaling those businesses is increasingly a challenge because of a capital gap.  ‍

Ecommerce businesses typically have to purchase stock or commit capital before they can make sales, meaning they have high working capital needs and often long working capital cycles.  But ecommerce companies do not fit the traditional underwriting processes of legacy financial institutions, who are slow to adjust to new business models, which leaves a gap in the market. Existing lenders often want personal guarantees or other collateral and can take weeks or longer to make a decision. Their terms are often not flexible or suited to the working capital cycle of ecommerce businesses and getting access to funds, even if you are accepted, can also take days.‍

This is where companies like Wayflyer come in.  Wayflyer is a revenue-based financing platform that focuses on ecommerce companies and provides businesses with working capital of between $10,000 and $20m to improve their cash flow and drive growth. Wayflyer uses analytics and financial data from merchants to assess business performance and will provide funds to buy inventory or to invest in other initiatives to increase growth. Wayflyer also provides free insights and recommendations to its customers to help them improve their marketing activities and drive sales. Unlike traditional funding which is done via the selling of an equity interest in a business, or via loans, Wayflyer provides funding to its customers in return for an agreed percentage of their future revenue. ‍

However, when Wayflyer was attempting to increase both the scale and speed at which it underwrites merchants, especially when expanding to new markets, they faced a number of challenges and they looked for an outsourced solution.

Prospective customers provide Wayflyer access to their bank account data via open banking aggregators so that the Wayflyer underwriting team can assess the business performance and creditworthiness.‍

However, as we know well, data from open banking has a number of challenges.  In its raw form, the data from open banking APIs is messy, making it difficult for humans or ML models to understand.  This issue is compounded when using multiple open banking aggregators with no common standard approach, meaning Wayflyer finds it difficult to underwrite a customer using this messy and unstructured data.  ‍

One of the key issues was identifying what prospective customers are spending money on, a crucial step to being able to understand the customers financial situation. Spending at Amazon or spending at restaurants mean two very different things to the underwriters at Wayflyer.‍

Whilst Wayflyer had built their own internal models to try and do this, they struggled to find enough data to improve the accuracy of their own models and wanted a solution to scale their operations quickly.

This is where Ntropy comes in.  Ntropy makes it easier to build better products with financial data and is the most accurate financial data standardisation and enrichment API.

Ntropy has processed over one billion transactions from many data sources and across many geographies, which is what makes it the most accurate enrichment provider and the perfect solution for Wayflyer to improve their accuracy and to scale their underwriting capabilities.

Through integrating with Ntropy, Wayflyer was able to improve the accuracy and quality of the merchant identification and enrichment, quickly enter new markets and spend valuable resources on its core product instead of gathering data and training its own in-house models.

As mentioned previously, the Ntropy models have been trained on a large amount of financial data from diverse data sources and are therefore very accurate.  Wayflyer was able to leverage our capabilities to enrich the financial data they receive from their customers to improve their accuracy in identifying and enriching merchants from below 30% to around 80% in a short period of time.‍

By partnering with Ntropy, Wayflyer was able to focus its resources on its core product, where it seeks to differentiate itself and not on improving their own model which would have been a never ending task.  Improving their existing in-house models would be expensive and time consuming and ultimately a distraction from its mission, supporting ecommerce merchants in growing their business. The straightforward integration of the Ntropy API made the decision to integrate easy.‍

A final impact of integrating with Ntropy was that it enabled Wayflyer to enter new markets quickly.  Ntropy’s models have been trained on data across the world and in many different languages and with that global focus, as Wayflyer expanded beyond its US roots to Western Europe, they were able to rely on Ntropy to be able to enrich bank data in these new markets which they had not seen before.

Wayflyer Data Scientist Michael O’Boyle summed it up very succinctly

The value we get from Ntropy is the ability to scale quickly and iterate quickly on enriching our banking data with accurate merchant information

If you are an ecommerce customer looking to grow, sign up and get funded with Wayflyer.

To learn more about how you can scalably improve your financial data enrichment accuracy and accelerate your speed to market, start building with Ntropy or get in contact with us.