The Infor Blog

Machine learning lets finance turn data insights into action

By Duncan Angove, Infor president

With the explosion of data, we have an explosion of insights. What kind of insights? Well, think about the recommendations you get when you search for or purchase a book on Amazon. Your email spam filter, autocomplete in Google searches are other examples. More complex usages of machine learning include self-driving cars.

And in finance, where every bit of information is critical, new applications for machine learning include credit card fraud detection, loan and insurance underwriting, and even trading. Now, many leading investment firms are “pouring money into technology and data management, snapping up computer scientists to help them build and develop next-generation investment systems that can outperform any human,” reports the Financial Times.

It’s too bad then that data scientists are already in high demand. As McKinsey observes, there are roughly 9.5 million US graduates in STEM fields each year, and “20% to 40% of these graduates would need to go into business translator roles to meet demand.” Since there aren’t enough scientists for the ever increasing data, we need to find other ways to make data more accessible—and useful—to the average business user.

At Infor we’ve found four key factors that can help you derive actionable information when applying machine learning to big data. Your choice in a technology solution should provide:

  1. Controls that take any user into consideration

Information should no longer be owned by a select few, who dole it out in hard-to-read reports. Virtually anyone inside of your organization should be empowered to improve your business’s performance with access to the right financial data and analytics tools.

  1. Elegant, modern, and simple UI

Data must be usable. Well-designed tools enable any user can analyze, understand, and act quickly, efficiently, and confidently on relevant data.

  1. Mobility and availability

Wherever your financial teams are located, they need to be able to create new business models, generate real-time insights, and help drive organizational change. Mobile devices with applications available in the cloud can enable this flexibility and productivity.

  1. Security

Leading cloud providers have made security a priority with massive investments in the most advanced tools and procedures available. Companies that choose cloud deployment can benefit from a higher level of data center and virtual system security than almost any organization could build on its own.

It would be great if every company could have its own team of data scientists to distill insights. But even if you can’t, you can still take full advantage of all your data with technology solutions and analytical techniques. With that investment, the data you collect, analyze, and use today will help you create a perpetually more strategic, proactive, and competitive organization tomorrow.


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