Published | May 8, 2019


Here’s How Artificial Intelligence Helps Our CRM Get Smarter, Faster And More Powerful

Artificial Intelligence Helps Our CRM

Let's start with a cliché. It was a simpler time for financial services organizations when the amount of information available about customers was limited.

Today, firms have access to information at an unprecedented level and must contend with a highly regulated industry as well as the commodification of products and services. For a CRM solution like NexJ, this represents a challenge as well as a great deal of opportunity, because more information about a customer is a powerful tool when used effectively.

AI and financial services

Financial services organizations have had access to large volumes of customer data for a while now. This data can be used effectively to deliver augmented intelligence and analytics at the point of service, but only if the CRM solution being deployed is powerful enough. There are a number of potential problems that arise at this point though, starting with the fact that a lot of data is siloed across systems. Another issue is the constant addition of external, fast-moving data sources.

AI and NexJ CRM

NexJ’s core philosophy was born with AI in mind, which is how our Intelligent Customer Management platform came into being. Our CRM started out with a data-first philosophy to ensure we would have access to all customer data. This is why NexJ CRM generates a Comprehensive Customer View to make sense of all data in real time.

Another aspect of our philosophy that drives how our CRM functions is automation. Our product automates tasks that advisors and bankers do on a daily basis. We started by developing an integration framework to integrate data from any source, then built a backwards chaining rules engine to leverage the data and help with automation. Our backward-chaining rules engine is fully integrated with the Business Logic tier. Backward chaining, also referred to as backward reasoning, is an inference method that works backward from the goal and is used in a number of AI applications. It is, along with forward chaining, one of the most commonly used methods of reasoning with inference rules and logical implications. The Platform is fully capable of triggering third-party rules engines based on any business event that occurs in the NexJ application.

Finally, we built a workflow engine to leverage the rules engine and complete the automation. This now enables our users to:

  • Automate lead scoring and routing during marketing
  • Automate onboarding to bridge marketing and sales
  • Automate customer loyalty programs to increase customer satisfaction

NexJ CRM uses AI to improve customer experience and revenue outcomes, drive suggested next actions and proactive engagement. It also uses rules in marketing, sales, and customer service, as well as to manage processes such as generating customer insights or automating research distribution to clients. Our latest deployment of AI takes the form of a special module we call NexJ Nudge.

Using NexJ Nudge to drive customer success

NexJ Nudge generates, scores and ranks actions based on best practices. It provides users with choices, helps them perform actions, and also tracks and puts out alerts related to important compliance issues. What it does, in the process, is empower advisors to deepen relationships with their customers, dramatically increasing advisor efficiency while keeping regulatory frameworks in mind.

Consumers want to be treated as individuals with distinct preferences, which is why the implementation of NexJ Nudge begins with the creation of an exhaustive client profile by leveraging data from the Comprehensive Customer View. It can then facilitate everything from KYC reviews to financial reassurance depending on fluctuations in market conditions.

As NexJ CRM evolves, it will enhance interaction points, deploy NLP processing and sentiment analysis to augment intelligence in the form of auto-generated interests for insights, personalized and targeted recommendations and actions, and outcome tracking. Our comprehensive customer view will generate and rank actions using centralized rules, prompt advisors, automate actions, and measure outcomes over time. These outcomes will then use Machine Learning to further tune the rules in a feedback loop.

NexJ believes advancements in Artificial Intelligence, Machine Learning, and Deep Learning will only be leveraged further by CRM solutions. As data becomes more organized, and acquisition processes more streamlined, AI will enable stronger connections with customers and empower sales, marketing, and customer service departments.

We are passionate about how AI and Machine Learning can transform our solutions and allow us to empower our customers in all kinds of ways. To find out more about how we do this, get in touch with us today.

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Adam Edmonds

Author: Adam Edmonds

Vice President, Products

With almost 2 decades of experience developing customer management solutions in financial services and insurance, Adam Edmonds is responsible for establishing overall product vision and designing easy to use solutions that solve real market problems.

Adam is excited to share the lessons he has learned and his insights on where the industry is heading with readers of his blog. He encourages readers to join the discussion or reach out to him with their own insights, best practices, and solutions to industry challenges.

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