Artificial intelligence (AI) is disrupting diverse industries, but banking is projected to benefit the most out of incorporating AI systems in the next couple of years. Analysts estimate that AI will save the banking industry more than $1 trillion by 2030.
I have been talking with bank executives for the last couple of years and it is exciting to hear that the banking industry has started to seriously consider artificial intelligence-based solutions for many traditional banking problems. The use cases where executives are seeing value do vary based on size, location and the type of financial institution. However, some core attributes remain the same.
For example, large banks have a huge customer success burden, so they naturally look toward automation of customer service with chatbots. Financial institutions like hedge funds are chasing alpha with AI on top of new layers of data sources, and insurance companies are improving risk models with AI. On the other hand, many of the financial institutions in developing countries are still stuck on setting up data infrastructure in a way that allows them to leverage AI.
Here are a few problems and AI solutions that many financial institutions are actively pursuing to create value. Of course, this is not a comprehensive list of all the AI initiatives the finance industry is experimenting with, but I would say these are some of the most popular trends.
Chatbots And Personalized Customer Service
With increasing automation, there is a fear of reduced loyalty due to less personal contact. However, increased AI usage does not necessarily mean less personalized experience, in fact, banks are using AI to increase client satisfaction, improve efficiency and maintain customer loyalty in many ways.
Bank of America has already developed a chatbot, Erica, an AI-enabled tool that provides financial guidance for the bank’s clients through voice and text messages. The service is accessible 24/7, and it can perform day-to-day transactions. This allows clients to have access to services at any time without costing more money hiring customer service personnel. Chatbots help ensure that, over time, less-typical queries have ready-made responses versus the current status quo where advisors often have to consult experts for immediate advice.
Transactional and other data sources can be tracked to help understand a customer’s behavior and preferences to improve their experience. For instance, American multinational bank Wells Fargo created a new artificial intelligence enterprise solution team this year to better leverage data and customize their services.
Banks understand the importance of accelerating and increasing connectivity with customers. Both JPMorgan Chase and Wells Fargo recently launched their mobile banking apps — Finn by Chase and Greenhouse by Wells Fargo. These apps were introduced with the aim of making customer interactions easier and attracting new clients, especially millennials. This sort of AI-based tech shows how banks are looking for new and creative ways to personalize the user experience and better understand customer behavior.
With AI’s potential to disrupt finance and fintech, the competition among leading institutions will rise in the following years. Large banks seem to have grasped the importance of innovation and the application of AI in their businesses, and they are starting to reap the benefits while the small and medium-sized institutions struggle to catch up.
One of the obstacles facing smaller companies in adopting AI is the shortage of talent. Bigger companies that have better reputations for innovation and higher profit-per-employee ratios are more likely to recruit top talent due to attractive paychecks for AI and machine learning experts. The good news, however, is that we are seeing AI startups that believe in equal access to AI technologies investing in educating and training more AI engineers with a goal of helping smaller and medium players.
Compliance, Fraud Detection And Anti-Money-Laundering
Avoiding fraud and money laundering is a challenge for many financial organizations. Artificial intelligence has the potential to help banks become more efficient in the process of detecting fraud and money laundering. To quickly identify potential fraud, AI engineers have developed tools and systems that automatically conduct and compress data that normally requires many hours of labor in just a matter of minutes, writes Alex Hickey of CIO Dive.
Read the source article in Forbes.