Where Is Analytics Going in Financial Services?By Guest Author | Posted 2017-02-06 Print
There are a handful of broader analytics trends that have special implications for financial services institutions. These four are especially worth noting.
By John Lucker
Where will the financial services industry (FSI) take analytics (or vice versa) in 2017? There are a handful of broader analytics trends that have special implications for banks and other financial services institutions. While the trends themselves may already be familiar to you, their impact on financial services may surprise you. The following four trends are especially worth noting as the year gets under way.
Automation Continues to Grow
Does the rise of robotic process automation (RPA) and cognitive automation mark the beginning of the end for business process outsourcers, call centers and teams that handle high-volume transactions in FSI? Well, maybe.
Financial services companies—especially banking, investment management and insurance firms—are leading the way in using RPA to automate transaction-driven, rules-based processes. Some are even exploring cognitive automation, using natural-language processing and related technologies to improve engagement during customer conversations as they occur. Automated investment reports, enhanced fraud detection, customized automated customer service, the automatic interpretation of regulatory requirements are all real-world examples of automation in action.
At the same time, however, don’t plan on an abundance of humans to be replaced just yet. Instead, look for automation capabilities to augment what employees are already doing. RPA can also help address the shortfall in trained workers that is expected to continue as experienced workers retire.
RPA can perform some more mundane tasks that new workers may prefer not to do. However, it can also use sophisticated business rules repositories and cognitive logic to leverage retiring experts’ knowledge and experiences—without requiring significant training time for hard-to-find workers who are replacing the retirees.
The Talent Gap Sparks Creativity
These days, it seems like everyone is aware of the shortage of analytics and data science professionals throughout the business world. It’s a problem that is real, profound, and—in some industries—dire. Place financial institutions in the latter category.
For example, graduates entering the job force from some of the best university programs in the world still (understandably) lack the real-world experience required to solve end-to-end business problems. In response, many companies are turning to professional courses and certifications in order to build out the technical skill sets of their existing staff. Formal degree programs, defined training courses and self-directed certification programs are all part of the mix these days, giving participants a way to develop and grow their skill sets in different ways.
Some workers need a more holistic education. Others need topical or pinpointed learning. All of these approaches have value and should become even more important as analytics and data science not only grow in importance, but continue changing and evolving. Such programs should begin to pay greater dividends in 2017.
Mass Personalization Seeks the Next Phase
Financial services companies have made big investments in data lakes, mobile apps, social mining and other technologies in order to learn about their customers’ preferences and behaviors. But how has the customer experience changed as a result of these efforts? To date, it probably hasn’t changed enough.
As we are all customers ourselves, it’s easy and useful to ask to what extent companies have successfully connected with us, understand our needs and preferences, and provide us with useful information or offers. Chances are, the answer isn’t pretty. While companies may successfully place us in the right broad demographic bucket, they have a long way to go when it comes to recognizing us as individuals—and appealing to us in the most meaningful ways.
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