Five Key Features for Creating the Optimal Risk Decisioning Solution

This is a sponsored article by Kim Minor, Senior Vice President Global Marketing at Provenir.

To compete successfully in our digital-first, instant gratification world, you need a risk-decisioning ecosystem designed to intelligently serve customers. A solution that not only connects every piece of credit decisioning and AI/ML software you own, but also enables you to access any external and internal data source in real time to auto optimize decisions—along with the impact of those decisions—across your entire customer lifecycle.

But many financial services providers are unable to tie all these elements together because legacy risk analytics offerings just weren’t built that way. So, as a user you’ve had to look to multiple products when you want world-class solutions for data and AI-powered decisioning. You’ve relied on vendors to make changes. You’ve relied on multiple user interfaces (UI) to keep control. You’ve waited months for solutions to go live, and… you’ve needed to replace technology a few years later when it can’t expand and scale with your business.

Whether you’re a startup with a single product line, or a unicorn offering a range of financial solutions, you need to create a financial ‘home’ for your customers, which means delivering a great customer experience from start to finish, regardless of changing dynamics.

Here are the five key features of a risk decisioning platform that will enable you to create world-class customer experiences:

No-Code Management: to integrate systems, change processes and launch new products

In a survey of 400 decision makers in fintech and financial services organizations across the globe, 78% of respondents cited low/no code UI as a feature they have or that would be most important when selecting an automated risk decisioning system. Inflexible solutions that require a vendor or your IT department to connect to a new data source, make workflow changes or launch a new product hinder time to market, increase costs, and put you behind your competitors. Look for a solution that has pre-built data integrations and a visual, drag-and-drop interface to easily and quickly make changes to respond to evolving consumer needs.

Connected Data: easy access to real-time and historical data

Through our survey of decision makers, we discovered that credit risk decisions rely more on historical than real-time data. Sixty-one percent of respondents use both historical and real-time data when making credit risk decisions yet only 11 percent mostly use real-time data. To make accurate credit risk decisions, easy access to data across the whole credit lifecycle is a must. And all teams must have access to the same data sets to ensure big picture decisioning. Without it, the insights needed to get new products and processes to market faster and to make intelligent risk decisions remain hidden in silos of data.

Centralized Control: data and AI-powered decisioning across the customer lifecycle

To power continuous innovation across the customer lifecycle, organizations need to be able to launch, learn, and iterate with ease, but separate solutions for data and AI-decisioning slow innovation down. Consumers expect their experiences to be seamless, giving them access to tailored financial services products while also protecting them from financial fraud. To support this consumer need and business strategy, financial services organizations need to combine data and decisioning into one cohesive solution that can provide the technology to access, analyze, and action data across fraud, identity, and credit decisioning processes.

Auto-Optimization: decisioning that gets more accurate every time it’s used

Do you know how your current risk models are performing? Or whether model drift is occurring and unhealthy? How long would it take you to respond to performance changes once they’re spotted? Traditional decisioning has relied on human intervention to spot model performance changes and identify efficiency improvement options, meaning improvements happen on an ad-hoc basis, if at all.

To operate at maximum efficiency and run the most accurate models possible, your AI-powered decisioning and data solution needs a centralized UI that connects all necessary data so it can be used to power a continuous feedback loop, where both historical and real-time data are used to auto-optimize performance on an ongoing basis. Model performance and accuracy can be monitored and adjusted in real time.

Grow and Expand with Confidence: Technology that scales and grows with your business

One of the biggest obstacles financial services companies face is having technology that can support their business as it evolves and grows. For example, people often find it a challenge to support decisioning as application volume grows and their offerings expand. Sometimes the impact can be from delays waiting for vendors or in-house teams to make changes; often it means procuring or building new solutions to fill in technology gaps or completely replacing existing solutions. Whatever the path forward, the impact is the same… delayed growth, limited agility, and user frustration. To preempt future technology challenges, look for options that empower you to grow, expand, and change direction.

To truly thrive in an increasingly competitive industry, you need to provide consumers with world-class customer experiences. A unified data and AI-powered decisioning platform lets you make smarter decisions, faster. Use your technology’s powerful data integration and automation capabilities to create streamlined user experiences and drive real-time decisioning.

About the Author: Kim Minor is Senior Vice President, Marketing at Provenir, which helps fintechs and financial services providers make smarter decisions faster with its AI-Powered Risk Decisioning Platform. Provenir works with disruptive financial services organizations in more than 50 countries and processes more than three billion transactions annually.