Financial services can benefit from AI that personalizes financial planning, detects fraud and automates processes – not just the back office but also customer facing operations.
A recent analysis by Accenture indicates that between 2018 and 2022, banks that invest in AI and human-machine collaboration at the same rate as top-performing businesses could boost their revenue by an average of 34 percent and, most importantly, their employment levels by 14 percent. You can learn how this prediction can become a reality in your company by exploring our solutions.
Morgan Stanley, for example, has already started augmenting the work of its 16,000 financial advisors through the introduction of AI agents (their human brokers get an ‘algorithmic makeover’). Using AI in the financial sector could not only enhance forecasting, but also streamline repetitive processes. For example, documents could be scanned and analyzed by computers. Thanks to image recognition and machine vision, AI can not only scan masses of documents but also take action based on the laws and regulations which apply. Teaching AI the regulations of different organizations or countries can also provide the human decision-maker with immediate support regarding policy or, in some cases, allow the computer to make decisions independently.
Thanks to developments in natural language processing, chatbots and virtual personal assistants could enable companies in the financial sector to interact with customers on a much wider scale and solve problems before any human staff get involved. While today it is still a contact center agent who answers customer calls and messages, handling both minor and major issues, in the near future virtual agents could take care of simple queries and issues – improving customer experience and allowing the human workforce to manage relationship portfolios and deal with major issues involving complexity.
Voice recognition and facial recognition could be used instead of passwords to ensure security. The new tech could also enable a swifter profiling of customers – to offer personalized communications generated by a system that adjusts the messaging to automatically created profiles of individual customers (AI could use the data collected on each person to analyze behavioral patterns and come up with psychological portraits). This could also enhance risks assessment in potential payment fraud cases, another major area of AI investment.
