Which five albums would you like to be stranded on a desert island with?
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Which five albums would you like to be stranded on a desert island with?
For those in Wealth Management, what has emerged is the acknowledgment that customer engagement is more critical than ever before.
Advisors who understand their clients better, and then use this understanding to meet specific needs more effectively, are going to emerge from this unprecedented crisis in better shape than the rest.
It is based upon the fact that customer expectations have changed across businesses and sectors, with customers now expecting the same kind of engagement from financial institutions that they do with other products or services.
Innovation and a global approach
Salesforce, for example, always manages to make us smile. Last year, the question posed by its co-CEO after his company acquired MuleSoft for $6.5 billion was: “…this is integration software, what does that have to do with CRM?”
Data migration involves a change in storage and database or application, which is what makes it a potentially complicated process. This is why we, at NexJ Systems, adopt industry best practices while managing migrations from legacy systems, using our extensive tooling and significant experience with client data encompassing a varying degree of size and scope.
Take Machine Learning and Deep Learning, both of which make an appearance whenever a discussion of AI begins. What defines Machine Learning? How does it work? Isn't Deep Learning just another form of Machine Learning? We thought it made sense to try and simplify answers to those knotty questions. So, here goes.
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.
Financial services organizations are accepting the advantages of cloud deployment because they are seeing that unified ecosystems, more agility, and better management of investments are all great for business. The cloud can be daunting though, for organizations that aren't clear about their priorities or don't have access to the expertise required to maintain or secure data effectively.
Working with data is always tricky because there's so much that can go wrong so quickly. Any CRM solution that claims to do its job well has to deal not just with data duplication or conflicts, but with third-party applications, back-office systems that don't talk to each other, external systems and a seemingly unlimited number of integration points.
Here's an interesting piece of information that got lost in the hype surrounding Salesforce's biggest deal ever. Apparently, the acquisition of MuleSoft in March for $6.5 billion was met with skepticism by senior management, until they were gently informed by a financial services firm of the importance of connecting data that is stored in disparate systems.
“Vertical CRM will be the preferred CRM Choice in the next three years”1
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
What’s it all mean?
Continuous Integration lets lots of people work on one project at the same time, while merging their work together in a central place regularly. This maintains the most recent version, so everyone is checking in or out only the latest code.
Our CRM capabilities and features are targeted towards a specific set of users, job requirements, or departments within an organization.
It makes perfect sense here too, because a Continuous Delivery Pipeline is nothing but a set of steps that code changes must go through to make their way to production. This Pipeline has four elements — Continuous Exploration (CE), Continuous Integration (CI), Continuous Deployment, and Release on Demand.
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.
The Financial Services industry is a fast-paced environment. With constantly changing and increasing compliance regulations, client expectations, and access to information, financial services organizations need access to the newest and best tools.
The increasing popularity of internet banking and mobile access are paired with increasing regulation and scrutiny. This means both more possibility for issues and more consequences when issues arise. NexJ enables firms to manage and protect information with a robust, centralized security model.
This is a question that increasingly occupies a lot of minds across industries. For financial service providers, it depends on not just how their customer data is stored and protected, but how it is processed and used on a day to day basis.
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.
Enterprise computing is undergoing a revolution, but it’s not the first. It has undergone a number of phases, or waves, throughout its history, each looking to introduce efficiencies in how we work. The first two waves of computing were centered on the back-office.
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.
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.
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!
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.
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.
Interested in AI, Intelligent Customer Management, or Chatbots, but having a hard time unpacking what they all mean? Adam Edmonds, VP of Products at NexJ Systems, explains everything you need to know in this series of short videos.
High user adoption rates reflect that your company's software investments are being appropriately leveraged, and ideally show that users are engaging with the system. To determine the effectiveness of the software at your company, you need to know your user adoption rates.
The Apache Open Source contributions to Hadoop are numerous and cover a broad portion of a reference architecture. It has been some time since we considered foundational low cost storage and in-place query capabilities. And as we saw in the "Data Lakes" blog posting, many organizations utilized this foundational offering.
I admit it; though I’ve been marketing software companies for many years, when it comes to earning recognition from the industry, I still feel a great sense of achievement. So when Aite Group, a global research and advisory firm, recognized NexJ for being top in features and technology in their report Next-Era Wealth Management CRM: Technologies to Acquire and Engage, I was elated.
Vendors have a similar language when it comes to describing the benefits of their solutions but that doesn’t mean you’ll get the same results with every solution. Whether you’re looking for CRM, customer engagement, business process management, or a customer insights platform, it’s worth your while to ask each vendor how their solutions deliver on their promises.
In my previous blog, we discussed how Intelligent Customer Management applies to Wealth Management and Private Banking. This blog will do the same but for Commercial and Corporate Banking. If you read my previous blog, you’ll find the description of the mechanics familiar, even though the examples are tailored to Business Banking.
In my previous blog, I introduced the concept of Intelligent Customer Management that we discussed at NexJ Client Day. Many of our Wealth Management and Private Banking customers were eager to discuss how it could explicitly apply to them.
Whether you’re shopping for customer relationship management, customer engagement, business process management, or a customer insights platform, you’re bound to come across similar vendor promises. “We’ll help you better understand customers. Improve the customer experience. Increase productivity.”
Today I’m boarding a plane heading to fabulous Las Vegas, Nevada.
It’s not my first time in the “City of Sin”, in fact I’ve lost track of how many times I’ve been, but this trip is different. Tomorrow morning the Gartner Application Strategies & Solutions Summit 2017 #GartnerAPPS begins. These shows are always incredibly insightful.
It was a pleasure to attend the inaugural Wealth 2.0 conference in Canary Wharf, London, UK last week. The two-day event brought together industry leaders from some of the top wealth management firms including Barclays, BNP Paribas, Schroeders, Northern Trust, Rabobank and many more as well as robos like Wealthsimple, Nutmeg and PensionBee. Of course, innovators like NexJ such as SwissQuant and Addativ were there too.