The concept of the metaverse has been around for decades, but it's finally gaining a foothold as a reality, especially in banking. Ray Wang, founder and chairman of Constellation Research explains why.
Data Analytics in Banking
Articles about data analytics in banking, including data analytics tools, big data, how to leverage data to personalize the digital banking experience, and other advanced data analytics strategies to drive business decisions.
Updated: What does OpenAI's disruptive week mean for responsible and beneficial AI adoption in the financial services industry?
Popular Articles within Data Analytics in Banking:
Personalization strategies not only support improved results in customer acquisition and cross-selling. They are now a basic expectation.
Tapping AI's banking potential has barely begun, but its impact on CX, operational efficiencies, and lending will be profound.
Personalization of banking services isn't a one-time event. It's a continuous process that only AI can deliver consistently.
Bank marketers considering decision engines to deliver personalized CX must understand they are just one part of a modern marketing stack.
Fintech competitors are grabbing wallet share. It’s critical banks mine first-party transaction data to retain customer relationships.
Consumers want personalized, tailored products that work for them and provide them with the insights they need to succeed. Joe Welu, founder and CEO of Total Expert walks banks through how to offer customer what they want.
Open banking — and open finance even more so — is the key to creating personalized banking experiences and driving financial innovation.
A modern AI-supported loan platform can help community banks be competitive and grow, but requires care in deciding which features to use.
Experts from Amperity and Microsoft explain why a customer data platform is at the heart of the most cutting edge digital banking programs.
Rising fraud undermines trust and threatens digital banking progress. Fighting back demands finding the right identity solution.
Financial institutions must use data, analytics, machine learning and new technologies to understand and build engagement with customers.
The payments battle grows hotter as it ranges from mobile technology to digital currency to invisible payments via the internet of things.
Turning existing customers into primary accounts is a key goal for financial institutions — largely unmet. It requires a new data framework.
The 'cost of funds' metric under-reports revenue for checking accounts and especially for rewards checking. There is a better measure.
The future of the banking industry relies on advanced data analytics, says Segmint's Nate Shahan, but few banks are applying it correctly.
Data and AI in banking will improve back-office systems, decisioning, customer engagement, and financial institutions' operating model.
Back office operations impact efficiency and innovation. Automating finance and accounting departments in particular brings big benefits.
Small institutions now have an edge — if they update their business model. Five traits mark the successful bank and point the way forward.
Many of the skills that Olympic champions possess are the same skills that can help banks and credit unions be successful.
Every bank is wrangling technology to help them be innovative. Here's an inside look at how Chase tackles digital with a unique strategy.
The ability to share deep insights across the organization is seen as essential for successful digital banking transformation.