July 19, 2018
The total addressable US small-business lending market is $186 billion, which accounts for only 1% of the total loan market. Today, big banks (assets of $10 billion+) are granting more than one-quarter of the small-business loan applications they receive. The 25.3% approval percentage is another new benchmark for big banks.
However, FDIC reports the total dollar-volume of small-business loans outstanding across all FDIC-insured institutions is down 13% since 2008. According to the Federal Financial Institutions Examination Council (FFIEC), the number of small-business loan originations is down 41.4% since 2008. For comparison, the US economy has grown almost 25% over the same period, according to the US Chamber of Commerce.
Although the approval rates of small-business loans by large institutions is at an all-time high in the US, it’s still only a quarter of applicants that get the necessary funds. As for the developing world, estimates suggest that 65 million, or 40% of micro, small & medium-sized enterprises (MSMEs) have unmet financing needs, resulting in an MSME finance gap in developing countries at $5.2 trillion.
Despite the fact that approval rates from large institutions are at all-time high, about 75% of small-business loans are denied by large institutions in the US, forcing a change in the marketplace – small businesses are actively exploiting other available options, whether it’s loans from smaller institutions, credit unions or online lending platforms. The emergence of online marketplaces is laying out the options of the balanced accessibility of information on the loans that serve small businesses’ interests best.
With the democratization of financing, the business of lending was bound to become a low-barrier, highly competitive space. Newcomers are filling the void and reshuffling the roles in the ecosystem. The new main actors in the lending industry – consumer and business – are the likes of Amazon, Google, Facebook, Apple, Baidu, Tencent, Alibaba, Uber, Ola, Grab, Square, PayPal, and, of course, a grand variety of online lending platforms operating around the world.
Many of the newcomers stepped into a void left by crisis-scarred banks and the traditional rigidity of existing risk assessment/scoring frameworks that no longer allowed for an adequate extension to credit to under-financed entities.
Source: CNBC
If you look at the small-business hierarchy needs, they need access to cash (and) funds; they need time, and they need more sales. And what if you were able to provide an efficient system that gave them more time to do all their work, access to capital, and something that boosts their sales line? You could see how that player could win over a traditional player or even a new FinTech. – Karen Mills, the 23rd Administrator of the US Small Business Administration (SBA)
It’s simple – data. Lending has become a pure data play (transactional data & past behavior).
The power is going to those who have the data. That used to be the banks. Now it is the retailers, Matt Burton, former CEO of Orchard, a New York-based provider of analytics to online lenders, told FT.
Tech/internet companies have a unique advantage over FIs when it comes to precious data defining the standing of any actor in their vast ecosystems. Data is the foundation of adequate risk assessment and risk management: internet finance companies often use big data processing, and mobile payment applications to enable them to underwrite loans.
FIs can gather data and they have been doing it for decades – no question about it. But today, the approach to qualifying entities and consumers for loans used for decades is no longer adequate mainly because of cheap technology, mobile, increased mobility, transforming employment frameworks, and changing consumer behavior.
Not only is the stream of data that defines a business/individual highly diversified but the capability to capture it has also significantly improved with the introduction of cheap and outstandingly effective business software, wearable devices, smarter smartphones, smart home equipment, etc.
While growing internet and smartphone penetration coupled with the rise of FinTech has challenged incumbents to go digital and look to incorporate innovative technologies in the way they do their businesses, the newer, nimbler business models are looking to bridge the gap in the traditional lending ecosystem by serving the underserved, thin-file customer segments such as SMEs and unbanked customers. – Diwakar Mandal, MEDICI
In his recent article, called Anyone Can Lend! With a Customer Base, Their Data (Lots of it), and Ability to Create Immersive Experience written for MEDICI Inner Circle, Amit Goel paints a vivid picture of how exactly that happens, emphasizing immersive experiences built by tech/internet companies and explains in deep detail why & how two particular companies are leading the way.
Let’s explore some example of tech companies that have acquired an advantage to allow them to enter the business of lending (even if they haven’t already).
Tech/internet companies have a unique advantage: they can collect a diverse stream of rich data by creating immersive, sticky, experiences.
An explosion of cheap technology convinced platforms that if they gathered enough data—from cash flows to zip codes to likes on Facebook—they would be able to predict the future. – Lessons of mortgage crisis go unheeded in small-business lending market, Financial Times
Facebook (social media)
Let’s look at Facebook, which counts a group of companies, including Jibbigo (a translation app that uses speech recognition software & offline translation capabilities), Atlas Solutions (allows companies to track the effectiveness of their social media campaigns), Onavo (helps improve app & data performance on Android and iOS devices), PrivateCore (data security), FriendFeed, Messenger, Face.com (pioneered facial recognition technology), Instagram, Oculus VR, and WhatsApp.
Facebook alone tracks 98 personal data points for each of its 2.19 billion monthly active users to target ads. Facebook has admitted that it tracks people around the internet, looking at what they are looking at. The site even tracks people who don’t actually use the site and are not logged in. In 2015, the company introduced a P2P payments service through Messenger, but even that’s not the most exciting part here.
No particular service of Facebook is interesting on its own. It’s the combination of behavioral patterns tracked through various integrations and daughter services that creates an opportunity. Not only can Facebook collect transactional data to evaluate your profile as a prospect for financial products but the company can also overlay it with a variety of other types of data – social, in particular– to be able to sharpen the image about any actor in its ecosystem for risk assessment. Theoretically, Facebook has everything it needs to starts extending loans within its ecosystem.
They’ll be in perfect position to extend credit and become a financial services company, said Jeff Stewart, chairman of Lenddo (helps lenders score applicants using 12,000 data points including social media), about Facebook in 2016.
In 2015, Facebook was granted a patent for authorizing and authenticating a user based on their social network on Facebook. Though the document details multiple applications for the patent, including filtering out SPAM and helping with search queries, it also explicitly states that it could be used to approve a loan based on a user’s social connections. It matters who your Facebook friends are.
When an individual applies for a loan, the lender examines the credit ratings of members of the individual’s social network who are connected to the individual through authorized nodes. If the average credit rating of these members is at least a minimum credit score, the lender continues to process the loan application. Otherwise, the loan application is rejected.
There are very few obstacles for social media platforms to get close to lending, but one is particularly important. The Federal Trade Commission has made hints that if social media platforms were to use their data for loan criteria purposes, it could then regulate the companies as a consumer-reporting agency. The FTC could also consider expanding what constitutes criteria as well – expanding the definition to include non-specific information, like social media patterns of people in a given area.
Amazon (e-commerce)
The situation is even more interesting with e-commerce/tech companies. Tech behemoths Google and Amazon are poised to put competitive pressure on traditional banks in the small-business lending arena.
Mills, who served as the 23rd Administrator of the US Small Business Administration (SBA), believes that the tech giants would probably push to disrupt the market and deal a blow to established lenders.
I think they are going to dominate the market, and that is the next phase that’s coming, said Mills. If you think about what Amazon already knows about its merchants, and then you think what Google knows about everybody who is buying and selling through its platform, one can imagine a world where they have much more information about both on the credit side but also on the small business itself.
Sellers have an assessable history with Amazon. They already have the inventory in Amazon’s warehouses, the packaging & shipping have been figured out, the product is clear, the customer is clear, and the demand is clear. That’s all Amazon really needs to know to be able to safely and confidently extend a loan to the seller to expand his/her operations. What’s more interesting here is that it’s the ultimate win-win situation. The seller grows own business, effectively growing Amazon’s business.
Amazon has five million sellers on its platform, most of whom are SMEs. Amazon lending offers business loans from $1,000 to $750,000 to registered Amazon sellers.
We see the metrics, minute by minute. Are they shipping out on time? Is the product what they say it is? How well are they serving customers? – Peeyush Nahar, VP - Amazon Marketplace, told FT.
Taking it a step further, Amazon is now offering small-business owners to become Amazon’s wheels, literally. In a move to reduce its reliance on the U.S. Postal Service and other major delivery services as the number of packages it ships continues to climb, Amazon found yet another opportunity for sellers that benefits the company.
The online retailer, which last year shipped 5 billion+ packages through its Prime program is looking for hundreds of entrepreneurs with little to no logistics experience to set up their own delivery businesses – complete with Amazon-branded vehicles and uniforms, the Washington Post reported. Amazon will help keep startup costs to about $10,000 by offering discounts on vehicles, uniforms, fuel, and insurance coverage. Amazon is also setting aside $1 million to help military veterans interested in starting their own delivery businesses.
Other examples (tech/internet)
There are many more examples. MEDICI Research recently outlined some of the lending efforts by tech/internet companies in a single infographic:
Source: Diversification of the Global Lending Landscape – Courtesy Non-Traditional, Non-FinServ Tech & TechFin Players, MEDICI Research
Even though an extension of funds to small businesses is a positive development from e-commerce/tech/internet companies & small businesses alike, there are always risks to evaluate. There are both Eastern and Western examples:
Baidu’s risk profile (internet/search)
Back in 2014, along with the rebrand, Baidu Finance introduced a personal loan service, allowing users to borrow up to 10X their monthly income and pay it back over a maximum of three years. At the time, Baidu was limited to 500,000 concurrent applications, which were divided into credit loans and mortgages. In 2014, the company claimed it can approve a loan application in as little as five minutes. Baidu uses big data, machine learning and facial recognition technology to help it vet a borrower’s eligibility for its loan. Borrowers make repayment of the loans through its mobile wallet payment application.
In 2015, the Chinese government launched a pilot program to establish five private (rather than state-owned) banks, out of which two were Alibaba and Tencent’s projects. The aim was to help small-and-medium-sized enterprises get access to loans.
Baidu and other China’s other internet giants have been actively moving into the financial services industry with a variety of efforts, but credit-rating companies aren’t so sure it’s a good idea. Fitch, one of the three big credit rating agencies, placed Baidu on negative watch in 2017, citing significantly higher business risks as the company moved into making unsecured consumer loans and selling uninsured investments known as wealth management products, *WSJ *reported in Summer 2017.
At the end of 2017, Baidu’s loss-making consumer-loan unit (licensed as a non-bank microfinance company, focuses primarily on granting private tutoring loan), has applied for a quota to raise up to 4 billion yuan (US $602 million) through issuing a form of securitization (asset-backed note) in China’s interbank bond market. In the first six months of 2017, it had a net loss of 44.6 million yuan (US $6.69 million). In China, licensed non-bank microfinance companies have been filling the gap left behind by banks in lending to the underserved segments, such as micro-enterprises and SMEs. In December 2017, the IFC considered a senior loan investment of up to $194 million through its own account as well as a syndication facility in Baidu’s microloan company.
Baidu emphasized in its 20F form that the Chinese government is continuously revamping the regulations over the internet finance industry, particularly those governing credit lending. For example, in December 2017, the PRC authorities issued a series of new rules to strengthen regulation on the microloan business and online microcredit industry, which require, among others, that online microcredit companies suspend providing microloans without a specific consumption scenario or specified use of loan proceeds and refrain from obtaining funds by transferring its credit assets through an online transaction platform or a local financial asset exchange, or through an online lending intermediary service agency.
The Uber financing debacle
Opportunities come with risks for everyone – banks and tech companies alike, not mentioning the end user. From the West, Uber financing is an interesting example. The Simple Dollar, a platform that offers advice on financial products, emphasizes Uber’s financing program as a vivid example of what could go wrong.
With a 22.75% APR loan, a particular driver was paying $1,000 monthly for his Kia Optima. Car payments were automatically deducted from the monthly earnings, which could potentially work well for some drivers. Active Uber drivers who took advantage of Uber financing were paying for their cars all along – but without having to actually write the check. But when someone with a loan stopped driving for Uber, they still had to make monthly payments, whether they were earning money driving or not. High-interest rates and high payments offered via the Uber financing program made it harder for drivers to earn money using the ride-sharing app, which is why they needed a car in the first place.
At one point, the Federal Trade Commission (FTC) lodged a complaint against Uber, which pointed out the insanely high rates charged via subprime auto loans.
Long story short, Uber financing became a thing of the past in the US after the ride-hailing company discovered it was losing 18X more money per vehicle than previously thought. The Xchange Leasing division – begun two years ago to attract drivers whose credit prevented them from getting their own cars – had been estimating relatively modest losses of $500 per vehicle on average.
In January 2018, Fair and Uber announced a new partnership that will provide drivers in the US with flexible and long-term access to vehicles through Fair. With a mobile app and straightforward monthly payments, Fair allows customers to have a car for as long as they want and turn it in at any time. Concurrently, Fair will be acquiring the active lease portfolio of Uber’s subsidiary Xchange Leasing, which includes existing lease contracts and vehicles.