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Natural Language Generation: Sailing Through Your Data Lakes

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Natural Language Generation: Sailing Through Your Data Lakes

Alex Serman • March 23, 2023

While most might not admit it, many wealth managers are drowning in their data lakes. Whether structured or unstructured data, performance or regulatory information, corporate or client documents, it is easy for firms with a large number of accounts to feel like they can’t get their head above water to make the best decisions for their clients. Many firms have basic checklists and standardization process for their data which focus primarily on accuracy and reliability. However, with the help of AI and Natural Language Generation (NLG), there is a way to make the data work for you and empower your strategy and decision-making.

If you are a wealth manager managing 500 or more accounts, that may only allow you 30 minutes a month of mindshare to analyze the data per portfolio. That is, unless your firm is investing in expanding your tech stack with tools that can analyze and process the data you need. We can help you mine your data and ultimately better serve your clients specific to their needs and risk tolerance.

What is Natural Language Generation?

Before establishing NLG, we must first identify Natural Language Processing (NLP), which is an AI technology that converts textual data into predictions and classifications in the form of numbers. Natural Language Generation (NLG) is a part of NLP that turns structured data into written or spoken language. When these technologies are combined, they have the capabilities to analyze the collected data, interact with this data, and extract the underlying meaning and insights to describe it in the form of written narratives.

As per recent research, the global natural language generation market was valued at over USD 336 million in 2018, and it is expected to rise at an annual rate of 19.8% from the year 2019 to 2025. Out of the total market share, the financial services, insurance, and banking sectors accounted for nearly 22% of the market in 2018. The report also states that by 2025, the banking and financial services segments are expected to dominate in terms of the overall NLG market share.

How Can Wealth Managers Leverage NLG and Machine Learning?

Investment Analysis: Actionable Narratives for Strategic Data-Driven Decision Making

    As we have mentioned, many wealth managers lack the bandwidth and resources to individually track portfolios and accounts to a high level of detail. However, with NLG and Machine Learning, they have the ability to track the impact of current or evolving trends in the market, unveil potential investment opportunities, spot risk outliers, and predict market downturns. This in-depth and personalized analysis adds a higher level of value to the portfolio analysis and is invaluable to the strategy and decision-making process.

    Increase Personalization and Deepen Client Relationships

      Studies show that organizations outperforming their competition attribute 40% of the additional revenue to their personalization efforts.

      The ability to speak into individual portfolios with a higher level of detail and data-driven strategies builds trust and loyalty between the advisor and their clients. Using NLG to provide insights into a client’s account to provide accurate and personal advice can strengthen an advisor’s ability to show value.

      Reduces Operational Costs and Drive Business Growth

        NLG and AI will never replace the “human in the loop”, but it can significantly decrease the time needed and spent on data analysis and the investment strategy process.

        With every area of financial services having to analyze and report some sort of data, NLG can be put to work to automate repetitive, time-consuming workflows and increase the quality, speed, and consistency of analytics and reporting. The narratives generated by NLG can be used by the CIOs, data analysts, portfolio managers, and compliance teams to gain an advantage over their competitors. This way, the data analysts and executives can devote their time on other value-added tasks that drive business growth.

        Whether your firm has mastered the data extraction, reconciliation, and normalization phases of data aggregation or not, it still leaves you with a massive vault of information that is in need of context, analysis, and review.

        Learn more about First Rate’s Data Aggregation as a Service and how our NLG and AI-driven solutions can help your firm sail through the complexities of your data lakes.