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Investment Assistant

Overview Case Study Pricing


UI - Investment Assistant


Personalizes investment recommendations, dynamic product summaries, macro research, asset allocation recommendations, overall investment rationales. Examples of tasks include:

  1. Generating personalized investment summaries.

  2. Updating asset allocation recommendations.

  3. Providing macroeconomic research insights.

  4. Summarizing investment rationales.

  5. Tracking performance of recommended investments.

Case Study

Traditional Workflow:

Relationship managers start by assessing the client's financial goals, risk tolerance, and investment horizon through in-person consultations and questionnaires. Then, they manually research investment products, analyze market trends, and review economic indicators to formulate recommendations. This process often involves extensive paperwork, data gathering, and reliance on industry expertise. Finally, the banker presents their investment advice based on their professional judgment, historical data, and market insights, aiming to align the recommendations with the client's objectives and risk preferences.

Workflow with Unique FinanceGPT:

Unique FinanceGPT for investment assistance offers personalized, data-driven recommendations based on investor profiles and market trends. It provides dynamic summaries of investment products, conducts macroeconomic research, and suggests asset allocation strategies. Additionally, it offers transparent rationales behind each recommendation, empowering investors to make informed decisions efficiently. By leveraging advanced algorithms and real-time data analysis, the assistant optimizes investment strategies and enhances financial outcomes.


While a typical investment advice takes 3 hours to compile for an investment professional, Unique FinanceGPT can shorten this entire process by 2.5 hours - for every single customer.


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