Analytics and machine learning are all about data.  The quality and quantity of your data plays a critical role in determining the effectiveness of the models.  But even with reams of the best data, if your process doesn’t use it properly, your results will be dubious.

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Click above to listen to Martin Sykora, on DM Radio. Martin joins the discussion at the ten-minute mark, and for the roundtable discussion at the 49-minute mark!

In "The Great Wealth Transfer is Coming, Putting Advisers at Risk," an article in Investment News, they pointed out that 66% of heirs fire their parents' financial adviser after they receive an inheritance. Marketing Wiz's "The State of Independent Financial Marketing" whitepaper discusses how every day, $2 billion in assets move from Baby Boomers to Generation X and Generation Y heirs. Combining these two statistics paints a concerning picture for financial advisors. How can Wealth Management firms address the needs of these inheriting children, to prevent losing 66% of their asset base?

The customer experience, now more than ever, is the bar we use to predict the health and growth potential of a business. Most major financial institutions are taking this to heart by adapting their services to deliver the “delightful” customer experience we’ve come to expect as consumers (think Amazon, Netflix, and Uber.) I was reminded of the sea change that is moving our industry towards intelligent customer management while at the Chief Data Analytics Officers (CDAO) event in Boston last month. I contributed to a panel discussion about the emergence of machine learning in financial services, where I was joined by industry peers with first-hand experience transforming their business with data-driven insights. The efforts of fellow panelists and thought leaders, like José Murillo of Banorte, were on full display. Our lively exchange made clear that the disruptive forces of Artificial Intelligence (AI) and Machine Learning are here to stay.

Last week's CDAO presentation on Single-Family Data Governance & Management by Freddie Mac illustrated how traditional back office activities are aligning and impacting front office processes.  We continue our recap of lessons learned at CDAO with this week's focus on risk management. This April, we were delighted to attend as well as participate in the Financial Services-focused Chief Data & Analytics Officer conference in Boston.  This annual gathering brought together senior-level data practitioners in financial services to share their latest innovations, best practices, challenges and use cases.  The concept of monetizing or commercializing data assets is revolutionizing the Financial Services industry by using governed data strategies partnered with business initiatives to realize data-driven transformation benefits.

This April, we were delighted to attend as well as participate in the Financial Services-focused Chief Data & Analytics Officer conference in Boston. This annual gathering brought together senior-level data practitioners in financial services to share their latest innovations, best practices, challenges and use cases.

Our hard work continues to get noticed as Nucleus Research, a global research and advisory firm, has once again recognized us as an Expert in their most recent CRM Value Matrix.

It’s interesting that artificial intelligence is such a hot topic these days because AI itself is not new. The concept of an ‘artificial brain’ was discussed by scientists in the 1930s. In 1950, Alan Turing created the Turing Test to distinguish machines from ‘thinking’ machines.

It’s been astonishing to see the amount of media attention around Artificial Intelligence (AI) in recent months. From the dystopia of HBO’s Westworld to the hype of Salesforce's Einstein, we’ve been inundated with larger than life claims about AI and its abilities. 

The flexibility and cost effectiveness of Apache Hadoop was quickly recognized by many organizations as an effective delivery vehicle to empower business users with operational self-service query and analytic capabilities.  Many organizations established, or are presently establishing, data lakes for operational intelligence query and analytics capabilities for the field personnel who need them most, best understand the data, and are the most capable of actioning insights gleaned. 

Clients choose NexJ because they are looking for a highly integrated solution as a strategic investment in their business. Their primary goals typically include improving the customer experience and driving cross-sell and upsell. To accomplish these goals, commercial and corporate banks are looking for an integrated banker experience that uses an enterprise view of the customer to drive cross-system workflows and enable bankers to collaborate across channels, regions, and lines of business. 

Many organizations established, or are presently establishing data lakes as a cost effective means of provisioning operational intelligence query and analytics capabilities directly to the field personnel who need them the most, understand the data the best, and are the most capable of actioning insights gleaned.  Sounds like an ideal arrangement.