The future of artificial intelligence in finance: the end of the job description! Bank advisor?

artificial Intelligence is one of the most important technological trends in the world Future. No wonder it also plays a major role in the financial industry.

AI in the financial sector – the future is now

The German financial industry sees artificial intelligence as promising Innovation with great potential. Since OpenAI and Microsoft have amazed both the professional world and average users with ChatGPT in the fall of 2022, it seems clearthat the triumph of AI cannot be stopped. One Study by the market research company Gartner even revealed that 75% of teams working in the financial sector will use AI-based applications in the coming years.

So-called neural networks are increasingly being used to process loan requests. Algorithms based on the principle of deep learning analyze large data sets to make better investment decisions. AI systems are also used to automate resource-intensive and repetitive processes and optimize customer service. One of the most significant changes here is increasing efficiency and optimizing processes. This Article looks into the future and dares to predict how artificial intelligence will influence finance.

Job profiles in the financial industry of tomorrow: Will IT specialists overtake business people?

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The rapid development of AITechnology will transform the financial industry as well as most other sectors of the economy. This will be accompanied by a change in job profiles in finance. There is much to suggest that algorithms will take over classic activities in the future Industry like Accounting or will take over the loan processing.

In the past, for example, commercial skills such as risk management, financial market analysis and maintaining customer relationships were among the core elements of the financial industry. The triumph of AI suggests that the Significance of bank clerks, customer service employees and accountants will decrease in the future. Financial institutions will therefore increasingly hire IT specialists. So you can already have one today Loan despite SCHUFA received or a lucrative one Investment without having to speak to a bank employee Contact to kick? What sounded like science fiction a few years ago is now almost part of science fiction Everyday life in the financial sector.

What exactly do the changes look like?

One thing is certain: Artificial intelligence (AI) has the potential to transform finance in many ways. However, artificial intelligence will not fundamentally revolutionize the financial system, but will continue and accelerate a trend that has long begun. Technological developments lead us to expect that the artificial intelligence of tomorrow will open up additional areas of application and new business areas.

It should be noted, however, that this trend is not new: renowned financial institutions have been recruiting highly qualified mathematicians, physicists and computer scientists since the late 20th century. These workers automate work processes, optimize risk management and develop powerful algorithms for trading on financial markets. But how will AI specifically change finance? From today's perspective, the following areas are among the most important areas of application of AI in the financial industry:

• the automation of receipt processing, VAT refunds, expense categorization and invoice processing
• the optimization of internal processes in finance
• the analysis of large amounts of data

AI to automate receipt processing, VAT refunds, expense categorization and invoice processing

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Artificial intelligence is suitable for... expenditure automatically categorize and process receipts. OCR technology (Optical Character Recognition) is mainly used. OCR is not AI in the true sense, but rather a process that captures text from scanned documents and images and converts it into machine-readable code. OCR technology allows computers to recognize both printed and handwritten letters and numbers and convert them into digital data. The further processing of the extracted data material is currently primarily carried out by human workers. It can be assumed that the processing and analysis of data will be one of the core tasks of artificial intelligence in finance in the future.

Advanced applications are already able to automatically recognize and extract relevant information such as the invoice number, the name of the supplier, the due date, the line items, the invoice currency and the VAT rate from documents. On this basis, algorithms will take over the labor-intensive and time-consuming process of VAT refunds in the future. This process requires collecting invoices and receipts from a variety of data sources. AI can automate these processes by extracting data from various sources and combining them into a central database. This Tasks Although they are not part of the core business of financial institutions, they are important for accounting and controlling.

In contrast to OCR technology, AI is used in work steps that traditionally require human intelligence. This includes solving problems that... decision making and the ability to learn from experience and apply what has been learned to similar situations.

AI to optimize internal processes

Other common use cases for AI systems in the financial industry include the automation of processes other than accounting activities.

Artificial intelligence can automate approval processes – for example in credit. As well as customers as well as financial institutions benefit from accelerated and efficient approval procedures. Artificial intelligence also has the potential to automate the internal invoice approval process. Applications are already available today that record and digitize invoices and then compare the data obtained with suppliers, customers and specific orders. The tools code every process and trigger further necessary work steps fully automatically. In contrast to traditional digitalized work processes, AI-based analysis tools are able to do so without human intervention Employees distinguish between different requirements and perform the appropriate operations.

AI can also help detect attempted fraud at an early stage and prevent damage to financial institutions. In the future, machine learning algorithms will likely be able to identify previous fraud patterns and draw conclusions about new ones Methods criminal actors. The rule-based testing systems used today often cannot detect these modified procedures because they are not trained on the current patterns of deception.

AI for analyzing large amounts of data

Scientists in almost all disciplines assume that artificial intelligence will revolutionize data analysis. Today's software can handle various statistical indicators fast calculate, but establishing or excluding connections is still the responsibility of the person People. This poses the risk that important causalities between different factors remain unrecognized. The biases of human researchers and analysts can also prevent a neutral view of the results. Among other things, AI can detect changes in customer behavior at an early stage and identify emerging market trends. Financial institutions can use these insights to optimize their product range and present their customers with tailored offers that fit their individual life and financial situation.

The financial industry can also use AI systems to identify trends and... Pattern recognized in the financial markets. There are already various indicators that support private and institutional investors in their investment decisions. However, these generate their output based on a fixed set of mathematical rules, so the error rate is high. AI systems have the potential to reduce the number of wrong decisions by significantly increasing the complexity of the calculations. This should be accompanied by a synthesis of the methods of technical, fundamental and macroeconomic analysis.

Artificial intelligence is also suitable for carrying out financial market-relevant sentiment analyzes away from the trading floor: This includes, for example, the automatic collection and analysis of press reports, comments on social media and analyst reports.

Conclusion: The increasing importance of artificial intelligence in finance

AI systems can automate and optimize repetitive workflows such as invoice entry, VAT refunds and other internal company processes. It is also expected that artificial intelligence will increase the security of credit institutions against attempted fraud and improve the management of risks in financial investments.

Overall, AI has the potential to make finance more efficient, customer-focused and profitable. As AI technologies continue to evolve, we are likely to see even more innovative applications that can fundamentally change the way we use and deliver financial services.

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