Artificial intelligence streamlines work processes in the finance sector, taking care of time-consuming tasks fully automatically. It optimises data processing, assists with analysing customer needs and detects fraud. It’s a win-win for any forward-thinking company.
2025-06-11 – Christian Mennrich-Ketelsen
The financial market requires constant modernisation of processes in order to remain competitive. Companies in the financial sector should regularly optimise their processes to achieve efficient and fast results. Artificial intelligence can help with this. AI controls data flows within financial companies, optimises document management and incoming invoice processing, and modernises financial processes such as data entry and verification by automating manual activities.
Efficient data processes and automation enable companies in the financial sector to respond directly to changes in the financial market. This strengthens the market position of financial companies that already work with AI today. They also gain an advantage over their competitors because they can use their expertise more effectively and no longer have to deal with manual data maintenance and analysis.
Banks and insurers see artificial intelligence as an opportunity to make processes simpler, cheaper and more understandable. It reduces the workload for employees by shortening decision-making processes and automating data analysis and classification. The use of AI links physical and digital processes. It helps to assess risks and take precautions to prevent fraud. This protects financial service providers and customers.
Forecasts show that the use of AI will become an integral part of the financial services industry in the future. More than three-quarters of executives in the financial sector are convinced that the use of AI makes sense. They see it as a new opportunity to create innovative services that are precisely tailored to the needs of customers. This strengthens customer loyalty and builds trust among new customers.
Artificial intelligence learns independently and works proactively. With the help of machine learning and deep learning models, it simplifies data collection and document control. In addition, it supports the creation of problem-solving strategies and improves financial processes.
Machine learning is a subcategory of AI that improves itself independently without explicit programming. It uses collected data to create strategies for solving problems and optimising models. To achieve good results, AI needs documents with high data quality for learning.
Deep learning models categorise different data sets from their raw form to achieve precise results. They work without human intervention, evaluate results independently and continuously improve their approach. In this way, the deep learning concept helps to automate and refine digital services.
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Lean processes give you more time to focus on strategic measures. Real-time AI analyses check transaction regulations and minimise the risk of bad investments. Depending on market conditions, AI can trade based on defined rules using algorithms. Other time-saving areas of application include contract management and AI in accounting.
Artificial intelligence in finance creates greater clarity by analysing data in real time, generating important insights and enabling you to respond quickly to market needs. It organises data sets and simplifies work processes through optimised risk management. Predictive analytics improves communication with your customers by providing you with an optimal basis for consulting.
AI is not infallible, so it is important to check content on a random basis. AI uses sources that are made available to it for learning purposes. These must be accurate in terms of content and comply with company guidelines. If this is not the case, there is a risk of improper processing of customer data and breach of confidentiality agreements. Data breaches also damage your reputation and can result in fines or other financial losses. You should therefore pay attention to IT security and data protection when selecting your provider.
• Real-time data analysis
• Forecasting market needs
• Optimised risk management
• Improved communication with customers
• Dissemination of incorrect results
• Risk of source manipulation
• Conflicts with data protection regulations
With solutions such as Azure OpenAI and the new Microsoft 365 Copilot, Microsoft offers a comprehensive AI infrastructure and applications that are directly integrated into Microsoft 365 – including SharePoint Premium, the Power Platform and other central apps. Data stored in these applications is subject to the strict compliance rules of the Microsoft Cloud and can be optimally protected using policies.
Shareflex is used for complex business applications, such as document and contract management. All data and documents stored in Shareflex solutions are kept in a central repository, which can also be used for AI-supported information retrieval. This significantly improves a company’s efficiency and productivity.
AI is already being used increasingly in the financial sector to simplify workflows. In the future, it will play an increasingly important role, taking over repetitive tasks and analysing large amounts of data. Financial companies that optimise their processes with AI at an early stage will have the opportunity to gain a competitive advantage. This is because eliminating manual tasks gives consultants more time to focus on customer service and strategy development.
Hamburg, 11 June 2025
Author: Christian Mennrich-Ketelsen
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