Impact of Artificial Intelligence on Portfolio Management

Impact of Artificial Intelligence on Portfolio Management

Artificial Intelligence (AI) has played a pivotal role in pushing digitisation in several realms of financial management, more specifically, portfolio management. From big data to GPUs, AI has skyrocketed its advancements in the fintech domain.

Artificial intelligence-based technologies have finally been optimised in the finance space with the introduction of Robo-advisors and algorithmic trading.

Quite a few fintech organisations have focused on uplifting the usage of AI for various purposes like automatic savings and risk management. This has transformed how investors manage their portfolios. Let us see how the upcoming technologies have paved their way into the investing decisions of experienced as well as novice investors. But for that, let us start with understanding what exactly AI is.

What is AI? AI or Artificial Intelligence is any software that a computer uses to imitate the characteristics of human intellect. Currently, some of the AIs that you come across in everyday life include Amazon’s Alexa, Apple’s Siri, AlphaGo and many more. Alexa and Siri use NLP algorithms to decipher a language, whereas AlphaGo has beaten the champion Go player. So yes, it would not be a

challenge for you to understand the capabilities of artificial intelligence in today’s world!

Download TejiMandi App for Advisory Services A few of the most used AI techniques are: Genetic algorithms: This is a heuristic algorithm that is search-based and derives its inspiration from Charles Darwin’s theory of evolution. This algorithm is mainly used to deal with optimisation and search-based issues.

Cluster analysis: This is an unsupervised method of machine learning. With this AI technique, you can identify and group similar data points in terms of properties and features.

Support vector machines: This is a supervised machine learning method that categorises data for regression and classification analysis. However, it is used more for the purpose of classification.

Decision trees: Like SVMs, decision trees are also a supervised way of machine learning. Yet, this is non-parametric and used for regression and classification.

With this basic understanding of AI, let us now decode AI in portfolio management. But first, a quick look at what is portfolio management?

What is portfolio management?

By portfolio management, we refer to the process of making decisions viz-a-viz the contents of an investor’s investment portfolio. Portfolio management stresses on policies required for managing the investments for an investor. This is based on their financial goals, asset allocation strategies, objectives, and risk appetite. Portfolio management is a financial service rendered by Professional Financial Advisors and investment planners. They are experts with experience in managing investment portfolios, with the ultimate aim of generating high returns and minimising the scope for losses.

Portfolio management helps minimise your risks by a proper set of investmentrelated plans and strategies that aim at diversification. Suppose you are willing to invest in bonds, stocks, or other assets. In that case, portfolio management will ease your burden by identifying the strengths and weaknesses of your investment choice so that you do not face any unexpected risks.