Finance Industry and more than $1 trillion. Yes, the number is right. AI is expected to save more than $1 Trillion for the banking industry by the year 2030. While the Financial Industry will experience a 22% cost reduction in operating expense, with most of the amount coming from the front office.

Artificial Intelligence in the Finance Industry is going to work at three different levels:

Front Office

Middle Office

Back Office

For the last couple of years, as well as the Real Estate Industry, the Finance Industry has started to consider leveraging AI solutions for resolving traditional financial problems.

Uses Cases of AI in Finance Market

Finance Industry Automation

AI can automate processes to manage tasks like understanding the new policies, rules, and regulations. Or developing personalized reports for individuals. Wealth managers can also use AI to generate more in-depth status reports for their clients, allowing them to provide personalized advice. They can conduct this task faster and present the information in a much easier way.

Additionally, AI allows bankers to make loan decisions in seconds, assessing the client’s spending pattern and risks. And also, evaluating other data, such as rent and utility history. By automating the decision-making process, bankers can reduce their risk of default loans and abandoned application form from frustrated borrowers.

Analysis and Reporting

A few years back if you wanted to check your bank account balance you had to switch on your computer, log-onto your bank’s website, and look for yourself. With mobile application and web portals powered by Artificial Intelligence, individuals can easily analyze their account to see how they are performing. Plus, get recommendations on future actions, and even get help in saving and budgeting automation.

AI can examine credit accounts, investment, cash accounts to judge a person’s overall financial health. AI can easily keep up with real-time changes and then create customized advises based on new incoming data.

Finance Industry Transaction Data Enrichment

Transaction Management is an important aspect of both consumer and financial institutions. TDE uses machine-learning capabilities to recognize unintelligible data that represents transactions and merchants. And then, convert them into readable text that shows merchants’ names and list their location.

The process of converting data into easy to read information can help both financial institutions and customer to acknowledge where they have spent their money. This can significantly reduce customer support calls and fraud research costs. And will reduce the number of people calling about mystery charges on their credit cards.

Predictive Analytics

“A recent study by Aite Group showed that 79% of 22 – 34-year-olds, 77% of 35 – 49-year-olds, and 62% of 50+-year-olds were interested in using a digital financial wellness coach.”

They simply want to get warned and updated about their financial data and get advice when they should or shouldn’t make investment step.

AI-powered financial spending tools tell users when they can spend their money based on their income, upcoming obligations, and bank balances. Tools can use machine learning to make a smarter decision based on the financial picture.

Expected Impact of AI in the Finance Industry

Personalized financial services

With AI in finance, it’s easy to create intelligent products that can learn from the customer’s financial data and determine what’s working for them and what’s not. And help them track their financial activities better.

Finance Industry Reduced Cost

AI in finance will help automate processes and significantly reduce the cost of serving customers. Along with reducing the cost of services, it will also make the finance system extremely convenient to avail.

Finance Industry Management

Artificial Intelligence now can help finance leaders to ask machines to analyze data and help them take data-driven management decisions for more accuracy and fast responses.

Preempted fraud

AI follows a proactive approach to make financial service’s environment breach-proof and safe. It helps in innovation by securing its products and services through a continuous understanding of human psychology.

Finance Industry Automation

AI works on research, understanding, and learning over long periods of time. And vast volumes of data. It introduces automation in areas that require high degrees of incisiveness thereby, safeguarding the trust of customers.

Finance Industry Insights

Generating insights involve extracting actionable and meaningful data from increasing quantities of raw data. One of the fastest growing use cases of Artificial Intelligence is to focus on customer communications. The communication can range from chat sessions to call center conversations, and even social media activity.

Business acceleration

Business acceleration means how companies will use Artificial Intelligence to assist knowledge-based activities to improve process efficiency and productivity, such as creating investment strategies for their investors.

Conclusion

Fin-tech companies are using AI to improve the customer experience. But finance leaders are predicting the real transformative power of Artificial Intelligence will be in areas linked to personalized Product development.

Financial institutions, banks, and credit community will be able to apply qualitative and quantitative data to manufacture financial products. For example, a fin-tech that uses AI and machine learning to underwrite loans using alternative data such as schools attended, work experience and consumers’ web behavior while applying for the loan online.