Financial industry 2024 – six trends for the use of AI

Financial industry 2024 - six trends for the use of AI

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By 2026, more than 100 million people will come into contact with AI. The use of AI is also increasing in the financial industry. Transparent and secure use is particularly important in this area.

Generative AI is currently taking the world by storm and is not stopping at the financial industry. The key to successful deployment lies in the transparent, trustworthy and secure use of AI: financial companies that rely on these aspects can improve the adoption of this technology, the achievement of their business goals and the acceptance of users by up to 50 percent.

This development opens up numerous potentials for financial companies, says Frank Striegel, Head of BFS Central Europe, Cognizant. 77% of bankers believe that creating added value through artificial intelligence will be the decisive factor that will make the difference between successful and less successful banks in the future. To remain competitive in this dynamic environment, it is critical that companies pay close attention to the following key AI trends in the financial sector in the coming year:

1. Customer and employee experience

Generative AI will significantly improve the interaction between customers and financial service providers in the next 12 to 24 months. AI-enabled digital channels are particularly important for companies that want to attract younger customers: 47 percent of Generation Z would turn their back on a brand after a single bad customer experience.

AI-powered virtual assistants and chatbots enable companies to gain deeper, more nuanced and personalized insight into the customer journey. Intelligent chatbots are able to analyze text and voice-based interactions. In this way, they can, for example, help customers transfer money between accounts or guide them to specific areas and features of the website to help them achieve their desired destination. Problems can be identified more quickly and solved better.

The engagement of employees can also be increased using AI and thus increase employee loyalty. A practical example: Companies struggle with fluctuation rates of up to 45 percent in customer service. The main reason is that the stress factor is too high. AI enables employees to give better and more effective recommendations to customers, which also increases their own satisfaction and motivation.

2. Personalized banking

Customers are increasingly looking for products that are better tailored to their priorities and lifestyle. According to studies, 65 percent of consumers expect companies to understand their individual needs and expectations, and 53 percent want all offers to be personalized for them. Generative AI enables companies to offer more personalized financial products. The significantly improved contextualization of customer and company data helps to gain usable insights for personalization more quickly.

Generative AI and narrow AI technologies automate time-consuming research and exploration processes. This helps reduce the time it takes to review loan applications and gives customers faster access to money than ever before. In addition, frictional losses are reduced when checking loan documents and identifying customers. This allows employees to focus on value-adding tasks while improving the customer experience. All of this optimizes the customer experience and leads to cost savings.

3. Detect fraud and comply with regulations

It is estimated that financial companies lose up to $4,1 trillion annually to fraud. Given the magnitude of this threat, companies are constantly looking for ways to detect fraudulent activity as early as possible. At the same time, financial service providers are confronted with a multitude of regulations, both within a country and across national borders. The operational costs of implementing and complying with these regulations have increased continuously in recent years

As a result, financial firms are adopting generative AI to augment their existing fraud and compliance tools and techniques in accordance with regulations. This is made possible by the technology's strength in areas such as anomaly detection, for example in identifying suspicious activities or discrepancies between new policies and their actual implementation and their "explainability", including the generation of the necessary documentation for audit procedures. Companies will also use the system to provide their employees with appropriate training, such as creating materials for compliance training.

4. Social listening

Financial companies are looking for new ways to analyze and interact with content from social media, blogs and other relevant online sources. Generative AI accelerates and simplifies this process, allowing companies to better understand the drivers and impacts of online conversations.

The technology also helps companies identify emerging trends and market needs within their customer base. This is possible because the generative nature of the technology examines the relationships between a much larger number of variables than has previously been the case when assessing customer needs. These insights help make better business decisions and better address customer needs.

5. Companies need tools that deliver both internal and external benefits

To maximize the value of generative AI, many financial organizations are seeking solutions that provide both internal and cross-functional benefits, for example through use cases that simultaneously improve internal and external processes. It is therefore expected that credit institutions, for example, will increasingly focus on industry-specific use cases, increase the productivity of developers and intensify the support of support teams so that problems can be solved more quickly.

The external benefits that generative AI can bring to the financial industry include personalized communications for debt collection, improved customer service, credit risk analysis, customer acquisition, and personalized credit recommendations. Internal benefits include improved fraud detection, loan document processing, internal support for lenders and servicers, and contact center optimization.

6. Software engineering

Another area is software development. Experience shows that software developers in the banking environment can become up to 30% more productive with the support of generative AI. While the productivity advantages when defining requirements are still relatively small, they are clearly measurable, especially in documentation, testing and also in the coding itself.

In summary, generative AI will transform the financial industry in many ways in 2024. Companies that strategically deploy this technology will be able to capitalize on the numerous opportunities presented by personalized banking, improved customer interaction, fraud detection and compliance, social listening, and internal and external benefits. The future of finance will undoubtedly be shaped by generative AI, and only those who adapt to these trends will thrive in this competitive industry.

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About Cognizant

Cognizant (Nasdaq: CTSH) builds modern businesses. We help our clients modernize technology, redesign processes, and transform experiences—so they stay on top in our rapidly changing world. Together we improve everyday life.


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