Half of finance work could be AI by 2030
The GMA Integrated News unveiling of artificial intelligence (AI) sportscasters Maia and Marco last Sept. 24 captivated many people during the start of the National Collegiate Athletic Association Season 99. This groundbreaking introduction sparked intense discussions on social media about AI’s potential implications on journalism’s future. People expressed a mix of excitement and apprehension, highlighting the need for further exploration and understanding of AI’s role in shaping the field of journalism.
As AI advances at an unprecedented rate, it is not only in journalism where AI can automate work. According to McKinsey and Co., by 2030, approximately half of the finance work could be automated. This automation will bring opportunities and challenges, as AI can streamline processes and improve efficiency.
The finance areas that have already started to be automated are the banking and financial institutions, risk assessments, credit scoring, customer service, and market sentiment analysis. In banking and financial institutions, an AI called KAI-GPT can auto-detect risks, generate insights, and make financially literate recommendations. Launched last May 31, KAI-GPT is “the world’s first banking-specific large language model designed to address the industry’s unique accuracy, transparency, trustworthiness, and customization needs.” KAI-GPT provides a human-like, financially literate response.
In risk assessment, the tool DataRobot AI can simulate potential fraud scenarios and detect credit risks, fraud risks, and market volatility. In the finance area of credit scoring, the Personetics Technologies and AIO Logic can detect risk, determine rates, and structure customer loans. AIO Logic is well-known as an A.I.A.I. for automated payment management, automated balance management, automated accounting, complex structures, automated invoicing, automated reporting and analytics that can also assess customers’ creditworthiness and set credit limits.
In customer service, robo-advisors, chatbots, and virtual assistants provide a conversational system fit for financial planning assistance. Robo-advisors offer financial advice and limited human interaction, which appeal to Generation Z, who have virtual interactions with advisors and are increasing interest in novel assets like cryptocurrency. AI is now also in market sentiment analysis, and BloombergGPT shows how to automatically analyze news, articles, social media, and other classified textual data; it can perform market sentiment analysis and even help manage investment portfolios.
These advancements in AI technology have the potential to significantly streamline and automate many tasks in the finance industry, reducing the need for human intervention. The applications of generative AI in finance will be widely seen in regulatory compliance and reporting, financial forecasting, portfolio optimization, anti-money laundering, and algorithmic trading.
However, it is essential to note that while AI can enhance efficiency and accuracy, it is not a substitute for human expertise and judgment. Human oversight and decision-making will still be crucial in navigating complex financial landscapes and ensuring ethical and responsible use of AI technologies.
Still, job displacement in finance may occur, and the need to upskill the workforce is now paramount.
Arnel Lopez Cadeliña, Ateneo de Manila University
