AI in Finance: How Artificial Intelligence is Changing the Industry

Artificial intelligence (AI) is influencing nearly every industry, including finance. According to the German Federal Minister of Labor, Hubertus Heil, by 2035, there will not be a single job in Germany that does not involve the use of AI. In this article, we will take a look at how AI is already being used in finance today and what changes we can expect in the future.

What is AI and how does it work?

Artificial intelligence refers to technologies that can mimic human capabilities. These include language, analysis, learning, or hearing. AI systems use large datasets and algorithms to recognise patterns and relationships. Machine learning also enables them to adapt to new data, so AI technologies are constantly learning. This functionality can be used, for example, to analyse financial transactions or detect fraud patterns.

Changes in Finance Jobs

As in other industries, the use of AI is changing job roles in finance: routine tasks such as data analysis and customer service are being automated, leading to changes in job requirements. Entire job profiles, such as that of an accountant, may shift.

These developments have direct implications for the job market in Germany: according to a study by the McKinsey Global Institute, about 30% of current working hours could be automated by technology by 2030. AI can learn and take over repetitive processes, giving employees time for other, more complex tasks. New professions such as data scientists, AI specialists, and algorithm developers are gaining importance.

What Role Does AI Play in Finance Today?

AI is already being used in finance today—banks are among the pioneers in implementation. One example from practice is Deutsche Bank, which uses AI in security with its account sensor, which can detect unusual account transactions through an algorithm. In addition, there are other areas of application; here are a few examples:

• Customer Service: Interactive chatbots are used to provide 24/7 customer support. These chatbots can, for example, answer frequently asked questions.
• Fraud Detection: AI technologies can detect anomalies and thus identify unusual activities. This ensures that potential fraud attempts can be detected early and within seconds.
• Security: If you are looking for a bank, you can often sign up online. For all necessary security measures, biometric authentication is often used, so AI can determine whether the applicant is indeed you.
• Process Automation: AI can automate repetitive and time-consuming tasks like data processing, making them more efficient.
• Investment Strategies: Algorithms analyse market data and make automated decisions based on trends and developments. This allows financial institutions to respond more quickly and accurately to market changes and adjust their investment strategies.
• Data-Driven Credit Evaluation: Data points are analysed by AI to assess credit risks more accurately. This leads to better credit decisions and lower default rates.

Shorter response times, higher security, and more efficient processes are already established in finance. But AI will not stop there—on the contrary.

Outlook: How Will AI Continue to Develop in Finance?

Based on current trends and technological developments, it is likely that the finance industry will continue to change and adapt through AI. Here are some examples:

• Natural Language Processing (NLP): AI technologies will better understand and process natural language, improving and making voice assistants more user-friendly. There are already beginnings with video assistants in customer service that can look and speak like real people.
• Personalisation: Banks and other financial service providers will increasingly focus on personalised offerings for their customers, such as tailored financial plans based on detailed analyses of customer behavior or financial goals.
• Forecasting: Data analysis enabled by AI will become more complex, and the data volumes larger. This will ensure that market forecasts and risk assessments become more accurate or even consider geopolitical events.
• New Business Models: Shifts in job profiles and technological advancements could lead to new business models in finance. For example, predictive analytics could be used for customised insurance products.

It makes sense to engage with AI. Companies that adopt innovative approaches early and incorporate AI into their job profiles will be well-positioned to succeed in this dynamic environment.

Advantages and Challenges of AI in Finance

The integration of AI in the finance industry offers numerous advantages: processes become more efficient, customer satisfaction is improved through 24/7 support, security measures strengthen fraud protection, and forecasts become more accurate. AI enables cost reductions and significant efficiency gains through automation and extensive data analysis. It helps in accurately assessing credit risks and developing personalised financial products better suited to customer needs.

However, the use of AI also brings challenges: data protection and the ethical use of AI are paramount. After all, the finance industry deals with very sensitive data daily. Financial institutions must ensure that their AI systems are transparent and understandable. Additionally, it is crucial that decisions made by AI are fair and unbiased. The balance between technological advancement and human expertise is essential for this.

Artificial intelligence is already established in many industries, including finance. And this will not stop in the future: processes will be made more efficient, customer satisfaction will be increased, and security measures will be improved. Technologies are constantly evolving—your company should do the same. Invest in training your employees to build the necessary skills to handle AI and remain competitive.

At LHH, we understand the challenges of your industry. Get in touch with our experts and let us work together on your goals.