Half of finance work could be AI by 2030

Dear Editor,

The G.M.A. Integrated News unveiling of A.I. sportscasters Maia and Marco last 24 September captivated many people during the start of the National Collegiate Athletic Association or NCAA Season 99. This groundbreaking introduction sparked intense discussions on social media about Artificial Intelligence’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 Artificial Intelligence advances at an unprecedented rate, it is not only in journalism where AI can automate work. According to McKinsey, 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 on 31 May 2023, 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. The KAI-GPT provides a human-like, financially literate response. Westpac, Australia’s first bank and oldest company serving more than 12 million customers, is in the process of implementing KAI.

Meanwhile, in risk assessment, the tool DataRobot AI can simulate potential fraud scenarios and detect credit risks, fraud risks, and market volatility. Using predictive and generative DataRobot AI improves the technical ecosystem in Financial Services.

Sanlam, Africa’s largest non-banking financial institution, uses DataRobot AI, resulting in more streamlined and transparent solutions, driving critical business value levers such as sales and client retention.

In the finance area of credit scoring, the Personetics and AIO Logic can detect risk, determine rates, and structure customer loans. Personetics serves over 140 banks and financial institutions across 30 global markets, reaching 135 million banking customers. United Overseas Bank, a Singapore-based Banking and Financial Services organization with 24346 employees and revenues of $9790000.00 billion, uses Personetics. AIO Logic is well known as an AI for Automated Payment Management, Automated Balance Management, Automated Accounting, Complex Structures, Automated Invoicing, Automated Reporting and Analytics. These two credit scoring AI 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.

The AI is now also in market sentiment analysis, and Bloomberg G.P.T. shows how to automatically analyze news, articles, social media and other classified textual data. Launched on 30 March 2023, Bloomberg GPT is a significant language model with 50 billion parameters trained explicitly on a wide range of financial 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 AI technologies’ ethical and responsible use.

Still, job displacement in finance may occur, and the need to upskill the workforce is now paramount.

Arnel Lopez Cadeliña
arnelcadelina@gmail.com

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