The banking industry is paving the way in AI adoption. Utilizing AI to its fullest potential to maximize its use on all forefronts; automated threat intelligence, fraud analysis, prevention methods, and more.
AI in banking is already common practice but only continues to grow as more companies are adopting it into their organization and investing more money to improve its capabilities.
It’s common belief that the use of AI in banking is a means to replace humans with automation. This isn’t the case. In relation to customer service and engagement, AI is able to work with humans to carry out back-end technical tasks to make workloads more efficient. Having AI perform the back-end technical tasks allows frontline staff to increase their ability to focus on high-value client needs and provide optimal customer service.
AI/ML applications are able to deal with routine internal workflows such as:
- Administrative Workflow
- Ticket & Email Routing
- Fraud Detection
- Error Detection
One of the most common uses of AI in banking is used for predictive customer profiling: By bringing internal and external data, banks are able to create predictive profiles of customers in real-time. With the use of predictive profiling, banks are able to learn more about the client and offer advice based on their profile. The use of predictive customer profiling is only improving the consumer experience, making sure information is relevant, timely and catered to their needs.