Utilization of Robo-Advisory Tools in Decision Support Systems

1.1 Decision Support Systems (DSS):

Decision Support Systems (DSS) are essential tools for helping people and organizations navigate the complex world of decision-making. DSS essentially uses cutting-edge computing technology to gather, compile, and examine data from many sources. This guarantees that decision-makers have access to a vast and pertinent information source. The capacity of DSS to handle both structured problems where specified procedures are available and unstructured problems which frequently have no predetermined solutions marks their adaptability (Rahamathunnisa & Chellappa, 2018). Decision-makers with less analytical experience can still engage with the system in real-time because of DSS's user-friendly interfaces. Through the examination of multiple scenarios made possible by this interaction, a deeper knowledge of the possible outcomes of various decisions is fostered (Ulfert et al., 2022). Applying DSS to business, healthcare, human resources, supply chain management, or environmental conservation all benefits from these tools' invaluable nature, which helps with resource allocation, strategic planning, and overall better decision outcomes.

A database management system (DBMS) for effective data organization, a model base containing mathematical models for analysis, an interface for user interaction, a knowledge base with domain-specific expertise, and the end-user, or decision-maker, who uses the system to make decisions, are the typical components of a decision support system (Grander et al., 2021). When making decisions in dynamic contexts where conditions are always changing, DSS is especially helpful. In today's fast-paced and complicated corporate context, they provide a strategic advantage by enabling users to predict and simulate probable outcomes. The applications of DSS are extensive and significant, ranging from supply chain optimization and environmental conservation initiatives to financial analysis and healthcare planning (Teniwut & Hasyim, 2020). Decision Support Systems considerably improve the efficacy and efficiency of decision-making processes in a variety of businesses and sectors by giving decision-makers timely, pertinent, and actionable insights.

1.2 Robo Advisory Tools Development:

The financial services business has undergone a significant transformation with the emergence of robo advising tools, which has altered the field of investment management and financial planning. Early in the twenty-first century, the idea of robo advising was developed in response to the demand for more affordable and easily accessible investment options. Around the middle of the 2000s, the first wave of robo advisers appeared (Yun et al., 2021). These platforms were algorithmic in nature and automated the process of investing, providing diverse portfolios based on the risk tolerance and financial objectives of their clients. The goal of these early versions was to offer a more efficient and technologically advanced substitute for conventional financial counselors.

The capabilities of the second phase of robo advising saw an expansion as technology progressed. Artificial intelligence (AI) and machine learning algorithms have become essential components, allowing robo advisers to give more individualized investment plans, analyze enormous volumes of financial data, and adjust to market changes. Robo advising platforms proliferated in the middle to late 2010s, drawing in a wider spectrum of investors with features including socially conscious investment, tax efficiency, and goal-based planning (El Abdallaoui et al., 2018).

Over time, robo advising systems have evolved to become more complex, including chatbot and natural language processing features to improve user interaction and communication. Robo advisers have benefited from the incorporation of behavioral finance principles, which has enabled them to better comprehend and address the psychological and emotional components of investment decision-making. Furthermore, a few platforms have branched out into debt management, retirement planning, and full financial consulting in addition to investment management.