Approximately 49 percent of financial planners and advisers in the United Kingdom are planning to retire within the next five years, while a mere one percent of firms intend to retain between 75 percent and 100 percent of the assets they currently manage, according to a study by Investec Wealth & Investment (UK). Concurrently, research from St James’s Place Financial Adviser Academy reveals that only four percent of UK workers have contemplated a career in financial advice, indicating a growing talent gap. This situation underscores the urgent need for scalable solutions, prompting some companies to leverage technology to fill this void. One such company is Stalwart Holdings, established in 2020 by Fabio Dias, an assistant professor at the University of Surrey. The company has carved out a niche in the financial sector, building on a 2019 peer-reviewed publication by Dias on machine learning applications in stock market prediction. The onboarding process for investment clients starts with a detailed questionnaire aimed at capturing both qualitative and quantitative aspects of their financial and tax situations. The questionnaire delves into qualitative aspects such as client intentions, preferences, and financial goals, as well as quantitative details like income, investment size, and maximum tolerated loss. The collected data is then analyzed using time series econometrics models that consider historical data and various economic variables linked to market risks. This analysis helps in generating optimal investment allocations that balance potential returns with acceptable risk levels. The results of the client evaluation are processed through a natural language processing model to create a human-readable financial advice report, which is reviewed and sent to the prospective client by Dias. If the client opts to proceed, they undergo verification through facial recognition technology and automated sanction list tests as part of the company's anti-money laundering protocols. Dias has assembled a team of researchers, developers, and compliance experts to build the robust infrastructure that supports Stalwart Holdings' operations. Dr. Anup Basnet, an assistant professor at Western University in Ontario, Canada, highlights the utility of this service for investors with limited financial knowledge and less diversified portfolios. He notes that the automated process facilitates quick dissemination of investment information, reduces behavioral biases, and enhances the reward-to-risk ratio. A Statista report estimates that by 2023, robo-advisors managed over $1.37 trillion in assets, indicating a growing trend and interest. However, Stalwart Holdings' reliance on AI and facial recognition technology raises concerns about data privacy and the potential for errors in automated processes. Dr. Basnet points out that not all investors are comfortable trusting algorithms with their investments. While these technologies can streamline operations and enhance security, they also carry risks if not managed properly, such as potential false positives in anti-money laundering checks and limitations in automated report generation. Dr. Basnet also notes that such services may not be beneficial for well-diversified investors, as transitioning to an algorithm-advised portfolio may yield only minor changes in volatility. He concludes by highlighting that robot advisors, like human advisors, are susceptible to sharp market movements due to systemic risks, and their algorithms may reflect the biases and limitations of their developers.