The global sharing economy continues to transform the online payments landscape, as we know it.
We spoke to YapStone, a payment platform taking the world by storm, and asked them how their new credit decisioning model has helped expand their company at a rapid rate, on a global scale. Through advanced analytics, model development has taken place quickly and effectively for YapStone. Here, they talk us through how credit scoring, open banking data, and credit risk models have facilitated their growth, allowing them to sit amongst industry leaders.
In a time when virtually anyone can sell goods or services on the internet, real-time merchant onboarding and risk and fraud monitoring capabilities have become imperative.
At YapStone, we know this very keenly because the bulk of our users are not simply selling products to strangers they will never meet – they are inviting consumers into their homes.
Twenty years ago, we couldn’t have imagined we’d be comfortable inviting complete strangers to stay in our home for extra income, but thanks to vacation rental marketplaces like HomeAway, airBNB, and Kigo, “living like a local” has become the preferred way to travel. As a result of this undeniable trend, YapStone now processes about $18 billion (and growing) in electronic peer-to-peer transactions every year.
Further challenges to marketplaces are emerging with the rise of Alternative Payment Methods (APMs). Consumers in different countries or regions have their APMs of choice, using them to pay securely with their local currency. As the payment partner, we have to ensure that these methods suit our customer’s lifestyle, and that they can securely pay using their preferred payment methods in their local currency, while sellers receive the funds seamlessly in their local currency.
YapStone has been able to capitalize on the growth of apartment and vacation rentals, where the average ticket size is large and the risk is high, by developing proprietary technology focused on reducing the risk of fraud and loss to our marketplace partners. YapStone’s trust and safety solutions are highly flexible and designed to service all marketplace types, allowing us to diversify our portfolio and grow our business beyond apartment and vacation rental marketplaces.
YapStone is unique in that we offer a full service, end-to-end payments acceptance, customer service, and risk management solution, including instant and advanced payments, to our marketplace partners. Therefore, it is a necessity for YapStone to verify the traveler and authorize their payment method, as well as verify the vacation property’s existence and ownership. Our goal is to deliver trust and safety to our marketplace partners, allowing them to spend more time focused on growing their business, while leaving risk management to the expert team at YapStone.
YapStone uses a layered, risk-based approach focused on the persona of any particular client interaction. Within the persona, we are continuously monitoring the purchaser of the good or service, the payment instrument being presented, and the asset or property they are renting. To accomplish this, YapStone utilizes proprietary data science and predictive analytics augmented with 3rd party data to achieve the most accurate risk scoring.
Given our scale, and the risk associated with high average tickets and the speed at which fraud can happen, it was critical for us to choose a tool that allows a risk analyst to react quickly to an escalating threat.
In 2017, we selected Provenir as a key strategic partner in the development of YapStone’s next-generation risk decisioning platform. The tool provides the ability to house our proprietary underwriting and fraud models, serve as the hub for our third-party risk vendor integrations delivering powerful adapters to augment our proprietary risk methodologies and data, and conduct A/B and regression testing for new or proposed model changes, all delivered through a simplified user interface that doesn’t require a PhD in computer science to use.
We maintain a highly competitive edge over other payment facilitators because of the way we mitigate risk for our marketplace partners and assume the liability for each transaction. Using our proprietary technology in partnership with Provenir, YapStone is able to provide marketplaces with high levels of automation for merchant onboarding and risk management aimed at improving speed to revenue and reducing losses for our clients.
We have a very exciting future ahead of us, made particularly bright by having partners like Provenir who help us deliver innovative solutions to our existing customers and new faces. As we expand into new territories, the demand for innovation in risk decisioning will be high. The team at YapStone looks forward to staying on the forefront of this new wave of marketplace payments.
Companies invest lots of time and money developing risk models to figure out which customers are the best bets for loans and credit, including auto lending, mortgages, credit cards, BNPL and more.
Operationalizing these models, developed in tools like Excel, SAS, Python, and R, within risk decisioning processes often turns out to be challenging. This is especially true with complex models built in R. Lots of risk decisioning ‘solutions’ demand that you manually translate the R model (or any other model that you are using) into code that it can understand. You need high-priced programming resources and lots of time to connect the R model to the risk decisioning process.
It’s much more efficient to use a risk decisioning solutions which are model-agnostic – in other words, a solution that doesn’t care how the model is constructed. Provenir’s AI-Powered Decisioning Platform is a great example of this model-agnostic approach. With this platform, models developed in a variety of tools can easily be imported, mapped, tested and validated using simple wizards.
Provenir automatically generates a list of the data fields; all users have to do is pick the data Provenir needs to send to the model, as well as the data the model should send back to Provenir to drive the decisioning. This entire process takes just a few minutes, which means you not only gain an effective way to maximize the value of your models, but can also instantly adapt risk decisioning processes whenever a model changes. Automating your risk decisioning not only saves you time and money – it improves your decisioning accuracy and allows you to focus your resources on growing and scaling your business.