With artificial intelligence evolving at a huge pace, a large variety of sectors are becoming heavily reliant on it in the running of their customer service departments. The banking sector is one of these. Here are three ways it is doing so:
- Cyber security
With cyber security one of the biggest threats facing financial institutions, banks are using AI to enhance their fraud detection systems. AI's power to dissect large amounts of data quickly and accurately makes it the perfect tool for identifying suspicious activities and lessening risks.
For example, JPMorgan Chase has implemented AI to enhance its fraud detection capabilities. By adopting AI, the banking giant’s systems are now able to analyse transaction data as it happens and flag abnormalities that may be revealed to be fraudulent, instantly. The company, which recently rose to the top of the US Financial services rankings in our Customer Effort Index, is now actively advertising for thousands of AI-related roles and has more than 300 AI use cases already in production.
- Chatbots
Virtual assistant chatbots have become prevalent across most major banks, with Bank of America, JP Morgan Chase, and Ally Bank all employing these tools across their customer service operations. Generative AI has evolved customer service chatbots in a way that allows the banks to provide data-based information in an instant, which inevitably leads to more accurate and precise answers in a lot less time, naturally improving customer satisfaction at the same time.
Furthermore, this allows human members of staff to focus on more important queries and tasks. We're seeing brands go even further with the adoption of proactive AI communication to help their customers before issues even arise.
- Personalising experiences
As we approach 2025, banking customers now consider personalisation a requirement rather than a bonus, and AI is allowing financial companies to easily implement this across their channels. By using the tech across their customer service processes, it is delivering clients with support that is more tailored to their needs in a tone of voice that reflects the subject of the interactions. For example, automated product recommendations based on data collection from a particular client is helping to create a unique personalised experience.
