Convenience and personalization for customers have become the forefront of 21st-century services. A client-centric approach is crucial for remaining competitive, with the onboarding process being one of the most important parts of interaction. When it comes to financial companies that clients need to completely trust, not only the first impression but also further service is essential.
Given this, it is unsurprising that financial institutions are increasingly looking for solutions to improve customer engagement. Among them is digitalization, namely Artificial Intelligence (AI) integration, which is already widely implemented in many entities. According to the Accenture study, the economic impact of AI on enterprises is considerable: By 2038, companies can benefit from an additional $10.3 trillion.
These impressive statistics raise a question: Can AI also be that effective in customer onboarding and further experience, or is it not that developed yet?
AI-powered onboarding enhances customers’ satisfaction
To begin with, AI, including machine learning, greatly helps banks and other financial institutions in reducing onboarding time for their clients. Automated document and adverse media check, scoring for risk category — these can significantly save time on the onboarding and Anti-Money Laundering (AML) processes. While manual checks could take days and weeks, AI’s results could be instant or take just a few minutes. In addition, such automatization reduces the need for human supervision and allows to cut costs on personnel engaged in onboarding processes.
With the help of AI and ML, the onboarding process can operate 24/7 compared to typical business hours procedure. Clients can open accounts or new products whenever they want, which increases retention and customer satisfaction. All additional documents could be requested during the onboarding process, as opposed to the current standard practice of waiting for the application to pass several levels of compliance and then returning days later with additional requests.
If any issues arise during the onboarding process, the application can automatically be sent for manual review. Even in this scenario, AI can provide suggestions or recommendations for the specific case, awaiting approval from the compliance officer only.
In terms of improving customer experience, AI helps banks by offering tailored services and advice. By analyzing individual data, AI can provide personalized financial recommendations, improving user experience with a personal touch. AI’s predictive abilities can even predict customer needs and suggest additional bank or fintech services. The technology elevates customer satisfaction and drives organizational growth.
Companies that prioritize customer experience a priori are more competitive than their rivals. Here, AI can act as a great tool for achieving the goal for a number of reasons.
AI and ML, in particular, also greatly aid primary analysis. AI can assist in document recognition, extracting and collecting data from many documents received daily by financial organizations. Considering that these datasets can be huge in big companies, AI can help provide a higher-quality service based on the analyzed data.
Beyond personalization, AI is also valuable for internal processes. For example, automatization with AI reduces costs linked to operational processes — the need for employee involvement in routine tasks is minimized with AI. The technology can handle many processes on its own, only requiring human approval in particular cases. This makes AI-driven companies much more competitive compared to traditional ones.
Also, AI fraud detection helps reduce security risks, making businesses more effective in preventing fraud. The early detection enables companies to respond quickly and mitigate potential damage before it escalates. This not only makes a company more trustworthy but also minimizes the company’s losses and expenses.
