Data-Driven, Analytics-Driven Decisioning
Slowly but surely, businesses are starting to realize the importance of offering more data-driven, analytics-driven techniques in order to render more real-time decisions for their customers.
No longer is the old “set-it-and-forget-it” approach to decisioning enough.
Across various industries and use cases, the interest in data analytics and decision management as a tool for keeping pace with the competition and delivering on customer expectations is growing.
Joe DeCosmo, chief analytics officer at Enova International, shared that using predictive analytics and data to build automated decision flows is a service that many businesses want but aren’t able to build.
It’s a hard job to do right, and it can be difficult to have the infrastructure in place to do it well, he added. It also requires having the right talent and teams in place to build the right models and the infrastructure.
This is exactly where Enova has observed an increasing interest in third-party solutions.
The Rise Of Analytics As A Service
If a business doesn’t have the robustness in terms of data sets, the data scientists needed to analyze that data or even the technology infrastructure to run analytics properly and perform real-time decisioning in house, then they may be better off leveraging the scale of a platform that does.
As DeCosmo explained, it’s hard to have all of the pieces needed to do those things well, which is where analytics as a service (AaaS) comes in.
Many companies have good analytics and good data scientists that can analyze the company’s data to build good models, but they lack the technology and technical infrastructure to be able to turn those into automated decision flows, he noted.
In these cases, the company has the analytics talent but not the IT or infrastructure capabilities to make the most out of the analytics they have.
And there are some companies that are lacking on all of those fronts.
“With technology and analytics being our core DNA and our heritage, we provide solutions that help companies move faster in that respect when it comes to model-driven, automated decisioning,” DeCosmo said.
Whether it’s decisioning models used for fraud, credit risk, customer operations or marketing, AaaS can be a powerful tool in helping a company address whatever it is trying to solve.
Though leveraging a third-party solution sounds like a good option, companies need to know that the AaaS solution they are getting will actually create a decisioning model that is both helpful and meaningful in the automated decisioning they are looking to deploy.
Understanding whether to build in-house or buy is significant decision for any company, but especially when it comes to decision analytics and management.
DeCosmo explained that Enova’s approach is to always recommend that a company work backward in order to first determine the outcome it hopes to gain in the particular decision it is solving for.
If it’s solving for credit risk or underwriting, he noted, then the outcome is likely seeking to have a better credit decision with customers, ideally one that is done in an objective, automated and real-time way as opposed to a manual, slow approach.
An institution or business must first know the outcome it wants and then think about all the data it will need in order to render that decision. DeCosmo also pointed out the importance of understanding any existing rules or policies that will also go into the decisioning model and could possible impact the outcome.
With a clear understanding of those policies, a company can then look at the decision flow and identify where a model in automation would improve the outcome.
