4
Predictive Model and ML Deployment Delays
Many companies report that their risk teams only deploy a small percentage of models they build. Why? Because businesses often find that their risk team and their decisioning technology—whether it’s a home-grown or vendor solution—speak different languages. For example, your risk team prefers Python, but your technology solution only supports Excel. This means that every model will need to be “translated” before they can be put into production. With 70% of FIs using ML to improve risk decisioning accuracy, easy model deployment is essential to power your ability to respond to market threats or opportunities.
5
Poor Case Management Delays Customer Credit Approvals
When all your data isn’t in one place, you can easily lose track of it. This can be especially true when it comes to tracking customer credit approvals that have manual stops on them because of an issue like missing documents or borderline credit. Your team might not have an efficient way to view all the pending cases at one time or easily drill down into the case details. Without effective case management, you’re basically asking customers to “stay on the line” for days hoping they don’t take their booking elsewhere.
6
Your Technology Can’t Scale and Grow with Your Business
The vacation many young families take verses trips business people or luxury travelers select can be very different, much like the technology you need when you’re powering from startup to unicorn. 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.
Made with FlippingBook Digital Publishing Software