The combination of high interest rates, high inflation and greater economic uncertainty means that banking leaders in the financial services sector have had to focus on their main concerns. Many aim to improve operational profitability, reduce risk when it comes to regulatory compliance and keep their customers satisfied with excellent service.

Technological advances will have a major impact on the future of banking and the banking landscape as a whole. Banks that embrace artificial intelligence (AI) and other advanced software development solutions will be able to adapt to changes in the financial sector more easily than those that dismiss them as optional.

Here are three key banking technology trends covered at this year’s Sibos conference that are on the rise in the financial services sector.

Trend 1: AI will continue to change banking technology in the coming years

It may seem like artificial intelligence has become the topic of the day, but it’s not a trend that’s going away anytime soon. AI has the power to transform the banking industry when it comes to risk management, operational efficiency, customer experience and much more. Digital transformation with a good AI strategy will equip financial services organizations that adopt it to be more agile as the financial landscape changes.

Applications of AI in the financial services industry

Regulatory risk and compliance: Artificial intelligence can discern patterns and behaviors to identify risks early. By analyzing historical data and predicting future scenarios, banks can assess market risk, credit risk, and operational risk and make their risk mitigation efforts more effective .

Customer service: In the banking sector, customer satisfaction and loyalty are of vital importance. When you combine custom software product development , such as chatbots, with employees working to solve critical problems customers face, you can improve outcomes and engage people with personalized experiences. Additionally, AI-enabled customer service offerings provide more data analysis on customer behavior, improving service offerings and marketing efforts.

Operational efficiency: AI can automate mundane and routine tasks to help save time and create operational efficiencies. It has the ability to analyze data and information faster and more accurately than humans, improving visibility within an organization so leaders can make better decisions, faster.

Trend 2: Data is the most important thing to get the most out of AI technology

One of the main trends we saw at the conference focused on that data. Many traditional banks and financial institutions still use spreadsheets created and maintained by humans, increasing the potential for human error and risk.

Connect your data

Siled data leads to a narrow perspective and an incomplete view. Wherever possible, connect data from disparate systems to create a unified view and realize its full potential. This not only improves AI automation, but also ensures that everyone who needs to access it within your organization has the most accurate information. For the big banks, this has been a challenge. Software development solutions that make use of the data fabric can help. A data fabric helps you work with data in a virtual architecture so that you don’t have to migrate it from one platform to another to use it. With a data fabric, it’s as if all your data is connected, regardless of where it lives.

Maintain the integrity of your data

If your data is not of good quality, that is, as complete and accurate as possible, the technology that depends on it will not work. Bad data can also lead to poor business decisions, regulatory fines, and customer dissatisfaction. Improve the accuracy of your data by involving IT teams in the process of defining, normalizing and managing it. Look for places where there is friction in your data entry processes and work to improve those workflows to improve the integrity of your data.

Be mindful of AI and data privacy issues.

Managers are right to be concerned about privacy when it comes to data and AI. The information that is fed into the linguistic models of many AI products is used to train the model for future results. If fed sensitive information or sensitive customer data, that information can become publicly exposed, creating additional risk for businesses regarding proprietary rights and regulatory concerns.

The solution to this in the financial sector is private Artificial Intelligence . With private AI, the language model is internal to your company and is only trained on your own data. This gives you the benefits of AI while maintaining a high level of security for your organization and your customers. It also means that AI results specifically reflect your customer base, allowing you to better understand the needs and habits of those you serve.

Trend 3: Tokenization and digital assets are becoming more popular. Automation can help

Most large asset management banks and financial organizations are exploring digital assets, tokenization and blockchain technology. Digitizing these assets will bring more real-world assets closer to a wider range of potential customers and allow money to more easily move around the world securely.

A growing number of investors are interested in investing in these new assets for wealth management, but traditional business models do not always make this possible. Modern fintech companies and banks are leading the way in addressing the pain points and solving these data challenges.

How are modern banks doing it? AI automation. Many of the tasks associated with digital assets can be made easier using automation, such as asset value assessment, financial forecasting, and much more. AI can also be used for risk assessment, risk management and regulatory compliance of these financial products.

Future-proof your organization with AI-powered tools

Financial services companies are facing massive changes in the sector. Banking leaders must be aware of how custom enterprise software development can help them adapt to save on operational costs, improve banking processes and digital experiences for customers, and reduce risk. A strong AI strategy combined with data and process automation is the way to succeed in 2024.