Benefits Of AI In Banking
Artificial intelligence is evolving as a technology that companies across industries are relying on to improve their services. Though tech giants are hogging the limelight when it comes to applying AI, fintechs are no less, especially banks. There has been an increased interest in usage of AI in the banking sector in the past few months. Some of the rudimentary applications of AI in banking are chat-bots, personalization of services for individual customers, service automation and implementation of self-service robots.
It is crucial for banks to become innovative to sustain competition. According to Financial Brand, the top reasons for organisations in the banking industry to adopt AI are to increase workforce productivity, identify opportunities in data, increase standing as an innovative company followed by improving their ability to compete and personalize communication among other reasons.
To further understand the relevance of AI in banking, let’s see how some key applications that will revolutionize the industry in the years to come are being implemented:
- Fraud Detection: The increase in channels through which customers do banking has led to a rise in the number of frauds. The introduction of channels such as mobile banking, ATM’s, websites etc. has significantly increased the modes of fraud. Kinds of frauds include identity theft and fraudulent transactions which artificial intelligence can fight through solutions like biometric identification systems, voice and facial recognition. AI also enables understanding of customers’ transaction patterns. If a transaction does not match the pattern, it will be identified as fraudulent transaction.
- Recommendations: As mentioned earlier, AI is capable of processing and understanding the previous transactions, requirements and preferences of customers to provide them with recommendations on how to organise their spending and other finance related issues. RBC is one such bank that is making use of AI to solve real customer problems. The bank’s AI virtual assistant is known as NOMI and is designed to answer customers’ requests, identify funds in a customer’s cash flow that can be automatically moved to a savings account, alert customers of any abnormal activity in their accounts, and offer personalized financial management advice, including predicting future cash flow.
- Enhanced Customer Support: One of the major reasons behind banks adopting AI is to enhance customer support. Like any other industry, customers in the banking industry play a crucial role in the success of banks. Their needs have to be met promptly. The use of AI helps in understanding the customers hence providing them with recommendations, alerts and constant support through chatbots.
- Anti-Money Laundering (AML) Pattern Detection: Anti-money laundering refers to the set of procedures that are aimed towards stopping the practice of generating income through illegal actions. Currently, AML is done through regulation based account surveillance and KYC systems. These outdated practices are incompetent to keep up with the dynamic world of financial misconduct. Introduction of AI based AML systems has made it easy to detect patterns and trends that were not seen earlier. Machine learning based systems can be continuously trained to use the previous information to prepare itself for future money laundering threats. HSBC is one such bank that adopted AI for their AML system. This has led to a 20% drop in the number of investigations.
- Chatbots: It is important for banks to engage with their customers in the right manner and as promptly as possible. Using ML and AI chatbots can be integrated into the engagement process to provide customers with prompt and personalised interaction. There are a number of advantages of using chatbots. They are easy and inexpensive to develop and delivers performance equivalent to humans. They can be used across channels and do not require storage spaces when used on cloud systems. Chatbots are easy to use even from the customers’ end as there is no downloading required and provides personalisation. Advanced chatbots are also capable of tracking spending patterns, credit scores and give recommendations for better money management. Another added advantage of using chatbots is the 24/7 digital support. Though the banks may be closed or employees unavailable, customers can always get answers to the questions they have at any time of the day. Bank of America has adopted AI based chatbot and named it Erica. Erica sends its customers notifications, gives suggestions on how to save money, pays bills and helps in other simple transactions.
- Algorithmic Trading: This refers to the process of using pre-programmed computers for executing large trade in orders to generate profits at a speed and frequency that may not be possible by a human. Many hedge funds are deploying AI to make decisions on the go. Reports say that more than 70% of the trading in the present day is automated and is carried out by AI systems. These hedge funds adopt different strategies to make High Frequency Trades immediately after they spot a trading opportunity based on the inputs. DE Shaw is the first among the hedge funds to adopt algorithmic trading.
- Process Optimization- One of the most promising applications of AI is to automate high volume processes that are of low value, within the organisation. This helps in reducing the amount of money and time spent on things that do not need extensive attention. For instance, JPMorgan uses AI powered chatbots to process internal IT requests such as employees’ attempts to reset passwords etc. The chatbots were said to have processes around 1.7 million requests in 2017 which otherwise would have required 40 full time employees.
The above mentioned applications do not mark the end to the numerous opportunities AI has in the banking industry. The industry can be called as an early adopter of the trend replacing many activities that were previously done by humans, reaping better results. The rise of fin-techs is still in its starting stages. Some of the innovation leaders in the industry have prioritized strategic technological advancements by investing in AI. This will tremendously influence the way traditional banking is done paving way to increased competition among the banking companies.