07 Jun The Game-Changing Role of Generative AI in Finance Departments
The full article is available in German language for REthinking Finance subscribers.
Table of Contents
Artificial Intelligence (AI) has become a focal point of technological advancement, particularly in the realm of generative AI. Since the launch of the ChatGPT chatbot in November 2022, a new cycle of AI development has begun, influencing various sectors, including the stock market. Major technology companies dominate the leading American stock indices, and according to a report by the Swiss bank UBS, AI is identified as the trend of this decade.
AI's Growing Presence in Finance
Chief Financial Officers (CFOs) and other finance leaders cannot ignore the implications of AI in finance.
The integration of AI offers unprecedented opportunities for efficiency, accuracy, and decision-making. Technologies such as machine learning, natural language processing (NLP), and robotics are used to automate complex and repetitive tasks, enhance decision-making through predictive analytics, and optimize customer experiences. Applications range from risk assessment and fraud detection to automated customer support and personalized financial advice.
Current Use of AI in Finance in German Companies
Despite AI’s strategic importance, its application in German companies remains limited. According to regular surveys by the Digital Association Bitkom, only 15% of companies reported using AI in any form.
This figure has increased by just 6% from the previous year. Generative AI plays a minimal role, with only 3% of companies actually using it. The Federal Statistical Office found similar results, with only 12% of companies with at least ten employees using AI. Larger companies (35%) are more likely to adopt AI than medium (16%) or small (10%) companies, with the most common use cases being in accounting, controlling, or financial management.
Generative AI in Finance Departments
Generative AI can transform finance departments by creating new, high-quality content like texts, images, videos, audio, or programming code based on prompts.
Unlike traditional AI, generative AI continually improves. In finance, AI can automate standard tasks, generate financial reports, and create summaries from extensive data quickly.
Use Cases for Predictive AI in Finance
Predictive AI in finance can help CFOs forecast potential revenue developments based on various internal and external factors. This is crucial for companies in cyclical industries that are heavily influenced by global economic trends.
AI is already used to analyze macroeconomic developments without prior hypothesis formation, identify complex relationships, and draw independent conclusions.
AI in finance can also play a significant role in fraud detection. In large companies with complex structures and vast amounts of data, AI helps uncover irregularities in financial transactions, thus contributing to effective risk management.
Successful Integration of Generative AI in Finance
For successful implementation of AI in finance, CFOs should introduce AI first in their department to understand its potential and limitations.
This can involve in-house development, purchasing technological solutions, or collaborating with AI technology companies. Pilot projects with a fixed investment sum can help identify use cases with high return on investment. The CFO should act as an enabler for innovation, providing financial resources to integrate generative AI across the company.
Challenges and Considerations of AI in Finance
The rapid development of AI brings both excitement and concerns. Some fear that the emphasis on AI might lead to a technology bubble. The rapid progress of generative AI, compared to the slower adoption of past technologies like smartphones, poses uncertainties for CFOs regarding the speed of development and the potential long-term impacts on business models.
AI development also primarily affects jobs requiring higher cognitive skills. While entire jobs may not be replaced, specific tasks within those jobs could be automated. The quality control of AI outputs by humans remains essential. Companies face the challenge of finding qualified employees for successful AI integration, necessitating technical training and emotional engagement of employees.
Data Quality and Protection in AI in Finance
AI in finance relies on data, and ensuring data quality and compliance with data protection regulations is crucial. For internal data bases, it is important to anonymize personal data according to the General Data Protection Regulation (GDPR).
Generative AI holds the potential to significantly enhance productivity and reduce costs in finance departments. By starting with pilot projects and gradually integrating AI across the company, CFOs can leverage AI to streamline operations and focus on more strategic tasks, positioning their companies at the forefront of technological advancement.
Rethinking Finance Magazine
REThinking: Finance, 3-2024 - Page 4-10
The article “The Game-Changing Role of Generative AI in Finance Departments” has been published in German in REthinking Finance online magazine, issue 3/2024.
This edition of REthinking Finance explores how financial executives can actively tackle current and future challenges in their departments through technological and organizational transformations. Topics include Digital Finance, Finance Excellence, People & Culture, and Business Organisation.
