It doesn't take a genius to figure out that Artificial Intelligence (AI) has changed all kinds of industries and workplaces in a number of significant ways. Attitudes towards the use of AI have also shifted, along with the ways in which it has been approached. One of the biggest shifts has been the emphasis on top-down reasoning rather than bottom-up big data. 

This is more true for the fields of Artificial Intelligence, Machine Learning, and Deep Learning than others, which is why our developers have put together a list of more commonly used terms to help you tell your Algorithms from your Active Learning, and Selection Bias from Sentiment Analysis.

Trying to tell corporate and investment bankers about the importance of understanding their customers is a lot like listing the benefits of butter to a pastry chef. They get it. They know it really, really well. And yet, considering we are in the business of Customer Relationship Management, I sometimes can't help but question what this means.

Wealth management is about trust. It is about giving an advisor control of your financial health and security and depending upon that advisor to make or recommend decisions that help you meet your financial goals. When we, as CRM vendors, focus on features that give our products an edge, we always focus on how specific features can help advisors build more trust. This is what makes relationship hierarchies so important.

 “VerticalCRM will be the preferred CRM Choice in the next three years”¹

Picture this: You, an advisor at a financial services firm, are interacting with customers. You have at your disposal an enormous amount of information related to their likes and dislikes, along with a comprehensive overview of their finances. 

I am often reminded of a specific parable whenever someone drops the words 'cloud', 'private cloud', 'hybrid cloud' or 'SaaS'. It's the one about the blind men and an elephant, who describe the animal based on which part of its anatomy they feel, then come to blows because they assume the others are being dishonest. 

A lot of people have the misconception that getting banks to change is like pulling teeth. It's a misplaced analogy, first because banks really are more open to embracing emerging technologies than most people think, and second because the last time pulling teeth was painful was probably around 1846, when the first successful surgical procedure was performed with anesthesia.

In my last blog [Invested Users: Best Practices of Maximizing User Adoption, Part 2], I discussed NexJ's second set of three best practices for user adoption, and why planning, partnering, and encouraging leadership are crucial steps in the process of engaging your users with your CRM.

In my last blog, I discussed NexJ's first three best practices of user adoption, and why developing, analyzing, and aligning are crucial steps in the process of engaging your users with your CRM. Today, I'd like to discuss the next three of the 9 best practices for user adoption, which are planning, partnering, and encouraging.

In a previous blog, I discussed how to measure your user adoption rates, and the effectiveness of comparing quantitative and qualitative results. Because users can log into your CRM system, without actually using it, it's possible to have extremely high quantitative results without having high user adoption.

Some of you may be familiar with Next Best Action in the context of Sales & Marketing, where the consideration is which offer is most appropriate for which customer at a point in time. Extending Next Best Action to customer service seems a natural progression, considering the service representative is already engaged with the customer, and presuming the interaction went well, means extending the dialog with an appropriate offer. 

To deliver optimal value to our customers, NexJ leverages our vast experience in deploying our software at the most recognized financial services firms in the world, our strict focus on addressing the specific business needs of the sub-vertical markets within financial services and our fervent passion for innovation.

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.

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.