Global banks are increasingly turning toward Artificial Intelligence technologies to stay competitive in the digital era.
Digital solution providers state that one robot can work 24/7 and replace up to eight employees, without asking for days off or a raise. This is the major reason why big global banks are increasingly turning toward Artificial Intelligence (AI) technologies to stay competitive in the digital era.
AI has huge benefits, for both banks and their customers. The implications of AI disruption in the financial sector is that the analysis of users’ habits, activities, behavioral characteristics, and financial data products can be customized to meet and anticipate each user’s unique and evolving needs. This makes it viable for each user to have his/her own digital personal financial assistant.
The banking and financial sectors are slowly moving from the first digital age to the second. AI, cloud computing, mobile-first and digital dashboards are already the norm, and new technologies are being adopted.
These are the most relevant application areas of Artificial Intelligence technology in banking and finance:
1. Personalized Financial Services
Automated financial advisors and planners assist users in taking financial decisions. They monitor events, stock and bond price trends against the user’s financial goals and personal portfolio, and offer recommendations regarding stocks and bonds to buy or sell.
2. Smart Wallets
Digital wallets are billed in most tech circles as the future of real-world payment technologies. With major players like Google, Apple, PayPal and others jumping on the bandwagon and developing their own mobile-first payment technologies, it appears to be a safe bet.
The insurance sector is utilizing AI systems that automate the underwriting process and provide more granular information to take better decisions.
4. Voice Assisted Banking
This technology empowers customers to use banking services with voice commands rather than a touch screen. The natural language technology can process queries to answer questions, find information, and connect users with various banking services.
5. Data-driven AI applications for lending decisions
Applications embedded in end user devices, personal robots, and financial institution servers are capable of analyzing massive volumes of information, providing customized financial advice, calculations and forecasts. These applications can also develop financial plans and strategies, and track their progress. This includes research regarding various customized investment opportunities, loans, rates, fees, etc.
6. Customer support
As speech processing and natural language processing technologies mature, we are drawing closer to the day, when computers could handle most customer service queries. This would mark an end to waiting in line and hence result in happier customers.
7. New Management Decision-making
Data-driven management decisions at low cost could lead to a new style of management, where future banking and insurance leaders would ask right questions to machines, rather than to human experts, which would analyze data and come up with recommended decisions that leaders and their subordinates would use and motivate their workforce to execute.
8. Reducing Fraud and Fighting Crime
Most industries operating on the World Wide Web are susceptible to fraudulent users and the banking industry is no exception. This has led to an arms race between online security providers and fraudsters involved in everything from email scams to credit card frauds. As security providers improve, criminals change their ways. AI tools, which learn and monitor behavioral patterns of users to identify anomalies and warning signs of fraud attempts and occurrences, along with collection of evidence necessary for conviction, are also becoming more commonplace in fighting crime.
According to a Gartner study, by 2020, consumers will manage 85% of the total business associations with banks through chatbots. Banks can offer advice on a large scale and with better impact by using AI chatbots that can learn about customer’s user habits. These engines can refer to the data from the past about user transactions, offerings, credit card usage, investment strategies, fund management pattern, etc. , and make the recommendation to the user based on the same aligned with best banking practices.
Banks can benefit from artificial intelligence models which can be done by taking input from several financial market sources and offer trading platforms based on the automated artificial intelligence systems.
Source: Financial Express