Lately, the banking and finance sector has been seeing a revolution in its day-to-day operations. Leading banks such as JPMorgan Chase, Wells Fargo, Bank of America, and CitiBank have embraced AI to deliver rich customer experience.
JPMorgan Chase is using a machine learning algorithm that will extract crucial information from thousands of legal documents and create valuable pointers for the reviewers. It will help the company to reduce 360,000 man hours.
Wells Fargo is using AI-based Chatbots to meet their customers’ needs faster and to improve client experience.
Bank of America introduced their own “JARVIS.” Being one of the oldest banks to provide mobile banking services, the firm has launched a new and unique enhancement called “Erica.” It is a virtual assistant helping customers 24/7 to address their one of a kind banking requirements. Erica is also supporting the bank employees to address the more complex needs of their customers.
CitiBank being a part of a huge corporation – CitiGroup is constantly investing in different startups and tech companies. To prevent various fraudulent activities in online and personal banking, they invested in Feedzai, which is a leading data science enterprise. Feedzai is leveraging a unique machine learning algorithm to prevent fraud.
Keeping the massive corporations aside, AI has not yet wholly penetrated the financial sector. The corporations mentioned above have invested millions if not billions, in implementing AI in their business. Small and medium banks cannot afford that sort of investment. However, if they do manage to implement AI in their business below are the use-case which they must consider to skyrocket their business.
Top 10 Use-cases that are Revolutionizing Banking and Finance Sector
Followed by its massive success in sectors such as Retail and Manufacturing, AI is now up and ready to revolutionize banking and financial services. Below are a few use-cases which banks can ‘bank on’ right now.
1 In-app Banking Experience
Today, almost every bank has at least one mobile app for performing casual banking operations such as checking balance, making a transaction, and ordering new checkbooks, passbooks, and cards. But only a few banks are leveraging AI in their apps to deliver rich customer experience. AI-based chatbots can help banks provide personal assistance to their customers. It helps them to automate simple tasks such as opening a new account, transferring cash between accounts, paying a bill, and processing different applications.
2 Smart Sales Processes
Chatbots are better at answering fundamental questions of customers. They can act as a virtual salesperson. These chatbots will have a unique algorithm which will help you to negotiate with your customers seamlessly without human intervention.
Sales executives have limitations such as working hours and industry knowledge. Intelligent systems such as chatbots have no such limitations. It can answer any questions of customers regardless of the time as long as the information is available in the database.
3 Compliance Challenges
Every financial institution is facing a high level of scrutiny. A huge volume of data is being produced every minute by banks. It takes months to identify malpractices such as market manipulation, foreign regulatory compliance, money laundering, etc.
4 Risk Evaluation
AI solves one of the most significant problems of the IT world – Data management. Banks are generating and deleting terabytes of data every day.
5 Trading
Today, investment companies are relying on data scientists rather than a market expert to determine the future of stocks. Data scientists create complex machine learning algorithms which are capable of finding future patterns in the market by observing the patterns in old data. These algorithms can crunch terabytes of data in seconds and can be taught to identify triggers for anomalies happening in the market. Apart from this, individual traders can also leverage AI to make decisions (for them) such as when to purchase, hold, or sell a stock.
6 Predictive Analytics
As the name suggests predictive analytics, “predicts” a customer’s future financial condition. The AI algorithm predicts what will be a customer’s financial condition if he/she will continue to spend and invest money like the way he/she is doing. The algorithm can also act as a personal financial advisor to a customer by providing them advice as to how he/she can improve his/her financial condition.
7 Transaction Data Enrichment
Understanding transaction data can be difficult for a person who is spending and receiving money multiple times a day, such as a merchant. Transaction Data Enrichment or TDE works the way it sounds. It transforms the difficult-to-understand transaction information into easy-to-understand. It helps customers monitor things like credit scoring, budgeting, spending habits, analyzing and predicting the spending and earnings of the future.
8 Fraud Identification
Both the number of global transactions and amount in a single global transaction is increasing like a grapevine, and so is the threat of online fraud. According to McAfee, among the total $600 billion cyber theft, a massive part of it is of online fraud accounts. The traditional online fraud detecting algorithm took only a few data points into consideration, whereas AI-based algorithms consider much more data points to identify fraud. Such an algorithm helped payments giant MasterCard to reduce fraudulent activities by 50%.
9 Smart Loans
Banks provide loans to their customers based on a credit-scoring system. It takes into account their banking history, income, tax payments, and more. But, for customers who have all their financial information well-recorded get an edge. However, a majority of loan seekers who are underbanked do not have their financial information into bank records.
The new AI-based credit scoring system will collect wealth data from the smartphones of underbanked customers to identify their creditworthiness. These alternative data points will provide new means for such customers to access credit from the financial institutions.
10 Personalized Wealth Management
There are many wealth management applications available on play store and app store that help customers to manage their wealth. As these apps leverage a customer’s bank account details, banks are planning to steal their customers by introducing in-app personalized wealth management system. These AI-powered advisors continuously learn from our financial activities and provide the best advice to customers, similar to what a relationship manager would do.
Conclusion
A digital revolution is coming in the banking and finance sector with AI. The main aim to introduce AI in banking and finance is to deliver delightful customer experiences. It helps customers to focus on the things that matter the most rather than understanding various banking jargons and processes. Experts predict that the future of AI-based banking mobile app development services is brighter than most of us think.
