Abstract
As the COVID-19 pandemic continues to evolve even beyond a second wave, there is an urgent need for business organisations to rethink and reconfigure their strategies for long-term sustainability beyond the pandemic. Many organisations are already making changes in the way they run their businesses and the way they make decisions to emerge stronger. It can be observed that the pandemic has seriously affected the way business organisations are being operated. However, this research suggests during the discussion that what is required is a transformational change rather than a directed one for any business organisation. In the current scenario, AI is being seen as a key enabler for business organisations to be on the path to recovery. What the ‘modus operandi' beyond the pandemic will be is a relevant issue for businesses indicating further need of research in this area. Using financial analytics and AI in combination will bring in a transformational change that might be viewed as the ‘game changer' for businesses beyond the pandemic.
TopPrevious Experiences – The Case For Ai And Financial Analytics
Even prior to the COVID-19 pandemic’s disastrous effect on the world economies, business leaders had started to increasingly embrace advanced analytics and artificial intelligence (AI), for good logic and reason. However, the pace at which it was being implemented was quite slow and even though financial analytics and AI adoption were progressing, it took a lot of time and a relaxed approach on the part of businesses.
The situation today has no time to relax. COVID-19 crisis has upended businesses as usual for communities and societies, which must now prioritize changes in their organizations to meet these new challenges. Specifically, governments and healthcare frontline workers, are leading massive efforts to support victims and their families and contain a virus that already has infected millions of people globally and claimed hundreds of thousands of lives. At the same time, business leaders must protect their employees and customers while managing the economic repercussions in the wake of mass economic lockdowns, increasing consumer fear, and continual uncertainty. The decisions they make today may alter their firm’s trajectory for years to come and become a ‘game changer’ alternative to bankruptcy and closure. There is a need to seamlessly combine AI with human judgment and experience for long run sustainability (Ågerfalk, 2020). Min-Yuh Day and Tun-Keng Chang(2018) developed a portfolio optimization module which took the information from a variety of sources, such as stocks prices, investor profile and the other alternative data, and used them as input to calculate optimal weights of assets in the portfolio. Coombs, & Chopra (2019) discussed the benefits of AI for improving financial data analytics and decision-making, current and potential applications of AI within financial services, operational challenges and potential solutions for AI adoption, and concluded with the requirements for successful enterprise. (,, 2020) studied the application of artificial intelligence and its powered technologies in the Indian banking and financial industry. Akter and Uddin (2020) researched transforming business using digital transformations with the application of AI, Blockchain, Cloud and Data analytics.
Some companies that are on the forefront of these trends and have already begun the AI journey will thrive in the post-crisis world. Again, history provides a guide: during the four previous global economic downturns, 14 percent of companies were actually able to increase both sales growth and profit margins, according to Boston Consulting Group research. (See Exhibit 1.) The majority of companies, however, are at the very early stages of the journey—or have yet to begin.
Key Terms in this Chapter
Causality: Given a relationship between two or more variables, it looks the relationship between cause and effect or what variables cause what.
Algorithmic Transformation: These are small processes that transform a given value into another according to algorithm that is created by analysts.
Machine Learning: The use of computer systems that can learn and adapt without following instructions via algorithms and statistical models to analyze the patterns that occur in the data.
Artificial Intelligence: The ability of a computer to perform tasks that are usually done by human beings because they require human intelligence and skills to conduct these tasks.
Predictive Analytics: It uses a variety of statistical methods from data mining, predictive modelling, and machine learning. It analyzes the current and historical data to make predictions about the future.
Pandemic: A disease that is prevalent over a whole country or throughout the world.
Financial Analytics: A financial analysis that refers to an assessment of the viability, stability, and profitability of a business or a project undertaken by a business using data mining tools to analyze the data with a goal to make financial decisions.