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NexJ Systems Inc., announces the launch of a new intelligent investment recommendation assistant that creates highly individualized investment options optimized to mitigate risk and volatility. It continuously monitors and detects portfolio imbalances and automates compliance by identifying the need to rebalance and applying investor mandate and firm compliance rules to all recommendations.

The intelligent investment recommendation assistant consolidates investor information from any source, internal or external, then utilizes client preferences and the firm’s portfolio management strategy to create a hyper-personalized mandate for each client portfolio. Working directly in partnership with Boosted.ai, a strong team with experience building Machine Learning algorithms at Bloomberg, the product employs Deep Learning methodologies to perform analysis of 10+ years of historic data to arrive at smart recommendations. It also automatically captures documented rationale for why a recommendation is made.

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Previously recognized by Celent that said “NexJ is one of the industry leaders for its implementation and application of AI across its platform”¹, this product extends the real-world deployment of AI and further deepens NexJ’s wealth management vertical specific capabilities.

“The intelligent investment recommendation assistant is not only delivering significant efficiency gains in the process of creating an investor mandate but, more importantly, is introducing hedge fund quality investment algorithms to client portfolios, hyper-personalized to individual and firm investment criteria,” said Matthew Bogart, Vice President of Marketing at NexJ Systems Inc. “Through the continuous monitoring for portfolio imbalances, the system driven alerts mitigate the potential of being out of compliance.”

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NexJ is confident that the intelligent investment recommendation assistant adds significant value to a firm’s investment in portfolio management, financial planning and trading systems. Immediate value is delivered through the reduction of manual processes required to consolidate information from these systems. It enhances a firm’s investment recommendations based on augmented intelligence and predictive models, taking existing systems and turning data into actionable and repeatable investment ideas.

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