PalletPal's analytics-fueled revenue-based inventory financing solution helps free up working capital for online sellers shipping in MENA
Supply chain finance (SCF)is a subset of trade finance (TF) aimed at lowering costs and easing the working capital burden on traders moving goods across borders. TF and SCF are instrumental in helping shippers and suppliers access capital. In case you missed it, here’s a brief primer on trade finance and supply chain finance from our last blog post.
This financing ecosystem, particularly in MENA, has been ripe for disruption for some time now. And so, we decided to delve a little deeper into: (a) the shortcomings of traditional financing; (b) why it’s time for some major changes in Know Your Business (KYB) and credit risk assessment protocols; and, (c) how we’ve been helping ease the working capital burden on digital-native SME shippers (e.g. Commerce sellers, D2C brands, etc.). Want to have the toolkit to worry less about financing your inventory and focus more on delighting your customers? Well, keep reading along and learn about how PalletPal can help you do just that.
Before we dive into this fascinating yet cumbersome topic, it might be useful to shed some light on the current state of the global trade finance space…
The global TF services ecosystem is worth $5.2 trillion with annualized financing transactions totaling $1.3 trillion in 2020 and growing at ~17% year on year. And, let’s not forget that ~4 out of 5 cross-border trade transactions rely on trade financing, according to the World Trade Organization.
Here’s the kicker… according to McKinsey & Company, the trade financing gap - the difference between the total number of trade finance requests made and those approved - sits at $1.7 trillion. That means, lenders rejected nearly $2 trillion worth of TF applications. HUGE problem. To put things in perspective, the value of rejected loan requests represents nearly 10% of global trade as a whole and 1.3 times approved TF transactions today. As one might expect, inadequacies in financing tend to disproportionately affect SMEs. In fact, the Asian Development Bank found that SME financing accounts for over 40% of rejected applications in 2020. Meaning, SMEs spend way too much time stressing about acquiring capital to stock up on inventory and not enough time building the incredible products their customers expect.
In MENA, trade financing activity accounts for nearly 3% of the global ecosystem. That’s $39 billion in successfully disbursed trade financing transactions in 2020. If we take the ratio derived from the simple math we computed in the above paragraph (i.e. rejected transactions are a 1.3x multiple of approved ones), we can reasonably interpolate that the TF gap in MENA sits at $51 billion. That’s not to say that this entire aperture is the market size or this gap can be filled imminently, but it certainly begs the question: Is there something inherently broken with traditional trade finance?
Did you guess it? Well, the answer is absolutely, unequivocally yes. KYB reviews and credit risk assessment methods are two critical components in a customer’s trade financing journey in dire need of an upgrade. When onboarding a customer, traditional lenders conduct preliminary credit checks and KYB reviews to determine an applicant’s credit eligibility. Once customers are pre-approved, financiers will evaluate risk, determine creditworthiness, and underwrite an applicant’s request. Some fintechs and progressive incumbents have broken strides in revamping KYB protocols and credit evaluations. However, the vast majority of financing companies still rely on siloed, often qualitative or parochial information and archaic processes.
Today, most lenders in MENA will often undertake the following activities to evaluate a potential client’s profile and creditworthiness:
Not only did we learn of this from our customers but also witnessed it firsthand while collaborating with financing partners for our initial pilot. Before building a fully fledged SCF solution, we launched a value add service (VAS) feature on our digital freight app. To do this, we onboarded 2 regulated lending partners: an incumbent bank and a nascent NBFC.
We ran the pilot for 4 weeks. We received 114 requests from customers, pre-approved a single one (an abysmal 0.9% conversion rate) and were ultimately compelled to reject the rest. Here are some interesting findings from our experiment:
The shocking results led us to spend an additional 3 weeks looking for a partner that used alternative credit assessment methods. NOTHING. Ironically, the launch of a new PalletPal feature ended up turning into a tremendously insightful study on MENA’s SCF ecosystem. We witnessed first hand what the TF gap represents, what its implications mean for SMEs, and how it can stifle their growth prospects. So, the question became: how do we reimagine credit underwriting for modern shippers in MENA?
The most obvious place to start was to understand the needs of our customers. One of the most positive findings from our experiment is the 80% resemblance rate between our existing customer base and those that signed up primarily for financing. An overwhelming majority of both cohorts were eCommerce sellers and new-to-market D2C brands. While we didn’t have access to critical data points yet, we knew that financing these companies required an analytics-driven approach. So, we started thinking about a broad set of variables these companies could make easily available, how this information, synthesized, might help accurately evaluate credit risk, and what type of lending facility such a model could support.
Since the majority of demand came from online sellers looking for inventory (or supplier) financing, we figured it was best to first build a solution tailored to their needs. One form of short-term lending that seemed well suited to addressing this gap recently emerged in fintech. That is, revenue-based financing (RBF). Here, providers lend capital that gets paid back as a percentage of future sales for a given credit limit and payback period. Coupled with a data analytics framework and bespoke customer success model, RBF can enable inventory financing solutions conducive to customers’ working capital cycles.
Unlike models employed by traditional lenders, an analytics-fueled RBF model has a more comprehensive understanding of online seller economics. Not only is RBF friendlier to customers because it doesn’t require any money guarantees or ownership dilution but it is also much faster and more efficient to set up and use.
Only interested in how we can help? Skip to the next section.
An RBF-inspired inventory financing solution would need to incorporate the below metric buckets to ensure that employing such an underwriting model generates robust insights:
Such a credit assessment mechanism would serve as the perfect alternative for financing modern, digital-native online sellers. It eliminates the need for an overly cumbersome and archaic KYB process as well as a practically irrelevant traditional credit check. In other words, it checks all the boxes while simultaneously reducing the risk of default. The best part about leveraging a software-powered methodology is that it can be tweaked regularly as more data feeds into it and enhanced continuously using machine learning.
(Note: For you blockchain and Decentralized finance aficionados out there, projects like SuperFluid are enabling programmable payment streams that will serve as the building blocks for DeFi-enabled RBF - a journey we may very well embark on in the not too distant future.)
At PalletPal, we finance eCommerce and D2C shippers’ inventories in a matter of days instead of weeks. Using our very own take on RBF, customers can get approved for lending by connecting their financial, customer and advertising data almost instantaneously via APIs. All we need is a minimum of 6 months of sales transaction data and average MRR of $10k.
(API = Application Programming Interface, which is a type of software interface that allows for sharing of services of information between two or more independent applications)
Our underwriting model can pre-approve customers in a few hours by securely synthesizing data from the following sources:
(Note: More data source options such as Noon plug-ins as well as bank account APIs will be made available over time)
Our credit assessment model automatically generates a report that lets customers know their approval status, credit limit, and cadence of draws. The kicker is, since our app is connected to the aforementioned sources, the credit approval report evolves with customers’ business performance and borrowing activity. In the future, we plan on collaborating with credit bureaus so that SMEs can leverage their credit scores with PalletPal across other facilities irrespective of the lender.
Once approved, a customer can make a draw request by submitting a brief questionnaire and a copy of the invoice for the inventory they’d like to finance. They immediately receive the proposed discount rate (i.e. PalletPal’s 4-10% take rate), repayment schedule (i.e. daily, weekly or monthly revenue) and, if applicable, maturity date (i.e. maximum payback date). And, voila… the capital can be disbursed in 48 hours.
Let me share a basic example of how this would work to make this concept a little more digestible:
Now that we’ve covered how inventory financing works with PalletPal, it’s important to keep a few things in mind before engaging with us. After all, Inventory financing, even when enabled by software, advanced analytics and RBF, is still debt. So, when should a shipper leverage inventory financing?
And, what should customers be wary of?
Interested in getting financed with PalletPal? Want to learn more about our software, suite of lending solutions or eligibility requirements? Sign up today or book a demo with one of our financing experts. We’re always just a click away!
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