The Five Habits of Successful Data-Driven Financial Institutions
Here is what banks and credit unions must do to be successful in a digital world dominated by data and advanced analytics.
Here is what banks and credit unions must do to be successful in a digital world dominated by data and advanced analytics.
Many executives in the banking industry aren't just out of touch with consumers and the external market. They are out of touch internally... with each other.
The success of any AI initiative hinges on the data collected — from channel usage and geolocational data, to consumer beliefs and behaviors.
Succeeding as a digital lender goes beyond a great loan app to include a complete transformation of the lending process internally.
A bank's data strategy must focus on the quality of data, and improving data generation and acquisition if the quality of data falls short.
Personalization and context are more important than ever. That's where data analytics and business intelligence come in.
With the rise of data analytics, the burden for growth falls increasingly to marketing. CMOs are now in the crosshairs, but is all the pressure placed on them fair?
What's your financial institution's level of proficiency with big data? Take this six-question self-test to see how your advanced analytics efforts measure up.
Will everyone be able to harness the power of predictive analytics — including community banks — or just a privileged few?
While banks and credit unions believe data can help them create a competitive advantage, their analytic capabilities lag behind other industries.
Predictive analytics combined with advanced digital delivery options can offer consumers financial solutions at the exact time of need.
Despite the availability of more data sources and advanced analytics, most marketers can't respond to customer journey opportunities.
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The customer data flywheel effect is an ongoing and iterative process, allowing financial organizations to improve personalization over time.
Predictive analytics provides insights that can drive sales, increase satisfaction, predict and stem attrition and maximize lifetime value.
Banks are testing open banking and partnering with fintech firms as ways to improve customer acquisition and retention.
Personal financial management (PFM) tools are becoming an integral component in many of the best mobile banking applications.
The key to creating the best possible experience and the most engaging customer journey is building a solid foundation on data.
One of the most important uses of data and analytics is for measurement of marketing effectiveness and campaign results.
The banking industry must leverage consumer data to improve marketing messaging, increase sales and reduce costs.
When bankers make sales calls, you shouldn't have to guess what works and what doesn't. Moneyball-style sales management is now a reality.
Predictive analytics helps financial institutions to better understand consumer needs and to provide personalized and contextual experiences.
Financial institutions must use data-driven insights to improve the consumer experience, increase sales effectiveness and improve operational efficiency.
Manual tasks across channels is costly. And while AI is hot, there’s a simpler way to bring efficiency that many bankers have overlooked.
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