Betterment is providing robo-advisory services so consumers can manage their money without needing a traditional financial institution, and it's working, says president Michael Reust.
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.
Personalization, cybersecurity and artificial intelligence are just a few use cases for quantum computing that Truist and IBM will research.
Popular Articles within Data Analytics in Banking:
Community financial institutions share artificial intelligence tactics that help them optimize their sales and marketing efforts.
Banks will make better use of data to enhance decision making, automate processes and personalize CX. Here's how they can get there.
By investing in digital tech, banks can address evolving customer preferences, mitigate risk, and achieve regulatory compliance, says AutoRek's business development manager Nick Botha.
Data and information overload is real, especially in the age of artificial intelligence. Advanced Human Technologies' chairman Ross Dawson talks through how banks can digest the data and get valuable insights.
Keeping consumer (and business) data is at the crux of trust in banking, especially during onboarding, says the CEO of IDology, Chris Luttrell. How can that trust be fostered as more institutions invest in new technologies?
Banks need to stop getting just hyped about AI integrations, and actually invest in the technology, says AI influencer Imtiaz Adam, who emphasizes the technology is critical across an entire enterprise.
The way forward for banks and credit unions is to lean into lessons from fintechs, and use data to put their own spin on the best ideas.
Traditional segmentation models are woefully inadequate. Here's how banking personas and qualitative data improves targeting.
To help customers navigate financial decisions, top-performing bank marketers must be able to extract — and act on — insights instantly.
Continuous product design — along with real-time data — can be institution-changing for banks and credit unions struggling to keep up with new back-end technologies, says Quantum Metric's founder and CEO Mario Ciabarra.
Despite emphasis on data and the deployment of many artificial intelligence solutions, banking is far from achieving the full benefits of AI.
Nontraditional data enables bank marketers to enhance retail and small business account acquisition. Here's how to make the data work.
Customer trends demand banks focus on personalization. The solution lies in machine-learning, data analytics and artificial intelligence.
New third-party data options can help bank marketers create a more precise picture of the most valuable customers and prospects.
Data and artificial intelligence are driving digital transformation in banking, and could help institutions grow their revenue — fast, says Segmint's Greg Gruning and Busey Bank's Brian Lindemann.
Successful bank marketing requires a holistic view of the customer, driven by effective use of data. Three competencies bring this about.
Nearly all marketers know they need to personalize, but few are sure of their ability to do so. It doesn't require AI, but data is key.
As financial institutions invest more in new technologies, they must also keep an eye on identify fraud and the solutions on the market to mitigate the risks, says TransUnion's senior director of global identity and fraud Chad Gluff.
The competitive pressure for banks to increase use of AI is running smack into growing pushback over model bias. 'Explainable AI' can help.
Without the right data and analytics tools — and a strategy for using them — 'customer-centric' will only be words.
Personalization is a key strategic priority for any financial institution wanting to distinguish themselves from other banks and fintech competitors. Jim Stapleton, senior vice president of Epsilon explains what goes into it.