BLOG

Personalized experiences are everything these days, and the world of financial services is no exception. We expect our Netflix recommendations to be spot on, we download apps to preview what a new hairstyle would look like, and we trust our Instagram feeds to offer up relevant ad content… but some traditional financial services institutions are missing the boat on personalized, meaningful customer experiences. And their growth is suffering as a result. Why? In part, because legacy systems (including data infrastructure and decisioning platforms) just can’t handle making more personalized offerings. To truly enhance the customer experience from end-to-end, financial services institutions, both big and small, need to look to an all-in-one, unified decisioning platform.

In times of economic uncertainty, banks and fintechs may be looking for ways to cut costs. But improved customer engagement is key to both creating long-term loyalty and acquiring new customers – both of which can help you weather any economic storms. Sometimes, you need to invest strategically to react appropriately to market disruption. As the Financial Brand shares, “No matter what the future brings, financial institutions need to develop a strategy that can recession-proof and future-proof their current business models. The banking industry has a once-in-a-generation opportunity to transform legacy business models to become more competitive and more resilient during economic upheaval. By integrating data, analytics, advanced technologies, automation and an up-skilled workforce, banks and credit unions can become more future-ready and agile in a crisis.” 

So, what exactly does the oft-overused term Customer Experience really mean? And why is it so critical to an organization’s success? Broadly, customer experience is the impression your customers have of your brand and your solutions as they interact with you – at all stages of the buyer’s journey, from first view of an ad or consuming your content all the way through to purchasing, onboarding and renewals. Customer experience matters in everything we as individuals consume – think about how you feel about your favorite grocery store, smartphone, hair products or exercise program (is Peloton actually a cult?). Now think about how you feel about your banking apps, your credit cards, your mortgage company, your last auto financing application. Are those everyday financial transactions memorable (in a good way)? Do you feel seen? Do you feel like your needs are being met in a personalized way?

Consumers want instant answers and tailored offers with their lending/banking experiences, with far less waiting and paperwork. With the rapid increase in digital-only banking and fintech innovations like buy now, pay later (BNPL) and embedded financing apps, providing anything less than a stellar customer experience means fewer repeat customers and a decrease in brand value.

Accenture reports that 5% of traditional banks’ revenue is at risk as millions of consumers are enticed by the transparent, tailored offerings of fintechs and neobanks. A 2020 survey of credit union/bank marketing leaders found that personalized approaches are the most effective for engaging people and expanding share-of-wallet. But 44% of those same organizations only send a couple of targeted marketing emails per year. Why? “Limited data insights make it difficult to truly understand a consumer and what they need in the moment.”

What does your risk decisioning platform have to do with the customer experience? In one word… everything. While some financial institutions are still using siloed environments and separate vendors or partners for data, decisioning workflows, analytics models and business insights, the more agile, adaptable organizations are looking at unified, all-in-one decisioning platforms. One solution that integrates real-time data, advanced analytics, artificial intelligence and machine learning (AI/ML), and decisioning automation can help accelerate digital transformation for a more customer-centric experience. With a unified solution, you can:

• Make smarter, more accurate decisions
• Shorten the product development lifecycle and get new products/offerings to market faster
• See real-time views of decisioning and performance data to uncover actionable business insights
• Create streamlined user experiences across the customer lifecycle
• Scale and grow your business to respond to market trends and consumer demands (with fewer growing pains for your loyal customers along for the ride)
• Democratize data access for more holistic views of your customers
• Optimize pricing and product offerings
• Expand your customer relationships with personalized upsell/cross-sell offers

McKinsey doesn’t hold back: “Predictive customer insight is the future.” Their article on ‘Future of CX’ predictions states that “those with an eye toward the future are boosting their data and analytics capabilities and harnessing predictive insights to connect more closely with their customers, anticipate behaviors, and identify CX issues and opportunities in real time.” While customer success teams and feedback surveys will always have a place in understanding the consumer experience, it’s clear that real, actionable data that can be analyzed in real-time is a game-changer.

But accessing, integrating, and analyzing data is not the only challenge facing financial institutions who desire a better experience for their customers. In today’s ultra-competitive landscape, doing so at speed is critical. As the Financial Brand shares, “Speed is a competitive weapon. The ability to see market trends, adjust strategies, innovate, create new solutions, make tactical decisions, and deploy resources quickly provides a business advantage… Banks and credit unions can no longer respond to opportunities and challenges with a legacy banking timetable.” But being able to adapt your offerings and pivot to new products or strategies quickly is next-to-impossible without an integrated, unified solution.

If you’re overwhelmed by the idea of choosing yet another technology partner, don’t fret. We’ve looked at some key factors to consider when evaluating decisioning platforms.

• No-code Management: Can you easily integrate systems, change processes, and launch new products, without relying heavily on your IT team and/or your technology vendors? Is your team empowered with a low/no-code UI (see, the customer experience matters in absolutely everything!) that can offer you things like pre-built data integrations and drag-and-drop functionality?
• Connected Data: Do you have easy access to both real-time and historical data, including alternative data sources? Can you centralize your data sources (goodbye silos) so users can more efficiently manage various data sets across the credit lifecycle and make smarter decisions?
• Centralized Control Across the Lifecycle: Can you bring together data and decisioning to better manage identity, fraud, and credit decisions across the entire lifecycle of the customer? Are you able to efficiently connect all systems to fully understand customer needs and personalize user experiences? When consumers are expecting seamless experiences, with tailored financial services and protection from fraud, can your technology deliver?
• Auto-Optimization: Does your decisioning platform get more accurate each time decisions are made? Are you able to see how your current risk models are performing, and can you respond to these performance shifts once you’ve spotted them? Instead of relying on humans or individual systems to uncover opportunities for improvements, can you connect all systems and power a continuous feedback loop that keeps optimizing your decisions?
• Ability to Scale: Your systems may be working well enough for now, but as the industry continues to grow more and more competitive… can they adapt and scale with you in the future? Does your decisioning solution simplify your growth or inhibit it?

A unified decisioning platform not only powers more accurate decisions across the entire customer journey, but it enables rapid growth and innovation opportunities. Instead of waiting for vendors to make workflow changes or sifting through siloed sets of data, you can spend more time focusing on what matters – your customers. Adapt as the market shifts, diversify to meet your customers’ needs, personalize offers to encourage engagement and brand loyalty. The opportunities for enhancing the customer experience are endless – and with a holistic, unified view of your data and decisioning, you don’t have to compromise your risk strategy to do so.

Ready to get smarter?

BLOG

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.

What is a decision engine and how does it help your business processes?