If you are a credit union still waiting on the data analytics sidelines, you’re already too late. Data analytics is not a fad – it is a major opportunity for credit unions to gain deeper insights and improve decision making to create a strong and competitive future. However, it is not always clear where credit unions should begin. To help answer these questions, John Best recently spoke with Clay Yearsley, SVP of Data Analytics at Texas Trust Credit Union about getting started on the analytics journey, the skills needed, and the value of data in the podcast, “Catching a Unicorn – Discussing Data Analytics with Clay Yearsley”.
In my previous blog, “What is a Data Lake? Part 1”, I discussed how to define a data lake, and how it differs from a data warehouse. To briefly recap, a data lake is a massive data repository for raw data in its native format. To better understand the idea, let’s dive a bit deeper and get to know the advantages and disadvantages surrounding data lakes.
To start, there are a number of advantages data lakes serve for financial institutions:
Financial institutions all over are working to build effective data strategies and improve decision-making. With so many new technologies and innovations out there, it can get very difficult to keep up with the industry and even keep straight the buzzwords we hear throughout the day. In this piece, let’s dive in to better understand what makes a data lake.
Last month, Mediachain Labs, a blockchain operator, was acquired by Spotify, a popular audio streaming service. The goal of the acquisition is to utilize the new technology to help track and appropriately pay the correct people when songs are played on Spotify. This is especially challenging with Spotify’s impressive growth in both users and song selection.
In the first part of this blog, we learned about who Generation Z is. Now that we have a better understanding of who we are talking about and realize that we need to be prepared, let’s look at what it means for your financial institution.
OnApproach CEO, Paul Ablack, and Mike Lawson of CUbroadcast caught up at the NACUSO Network Conference in Orlando to discuss credit union industry trends and the upcoming 2017 AXFI Conference.
The interview covers credit union collaboration, fintech disuption, enterprise data integration, predictive analytics, data pooling, member experience, Identity and other exciting topics relevant to today's financial services industry.
In the sixth and final Data Analytics Series BIGcast, That’s a Wrap, John Best speaks with Paul Ablack, OnApproach CEO, about key themes and trends we are experiencing in the credit union industry, and how credit unions can get started with data and analytics.
There has been a major emphasis on making banking friendly for millennials. Of course, this is a necessity as millennials make up a larger percentage of the workforce and have different expectations for their financial institutions than previous generations. However, there are bigger changes to prepare for. If you are struggling to please millennials, a generation of adults who were impressed by the ability to send text messages and pictures as high schoolers, how will you be able to meet the needs of Generation Z – the generation who has been operating smart phones and tablets (and in some cases coding) before they could walk or talk?
Data continues to prove itself as a necessity for decision-making in financial institutions. For years, major banks and innovative companies such as Google and Amazon have taken advantage of “Big Data” to gain better insights into their customer base and make business decisions to position themselves for the future. The credit union industry is finally beginning to take advantage of their data and utilize new technologies. However, credit unions are much smaller than major banks and simply don’t have the same quantity of data that banks are able to collect from their customers. Fortunately, data pooling serves as a great solution to this problem. Here are 5 reasons your credit union should participate in data pooling: