AI in Finance: A Change In Direction Refining Everything Money

Artificial intelligence (AI) has become increasingly prevalent in the finance industry due to its ability to analyze vast amounts of data and make predictions based on that data.

And with the aggregate potential cost savings for banks from AI applications estimated at $447 billion by 2023, banks are finding new ways to incorporate tech into their services.

Let’s dive into some of the popular AI applications in finance.

Applications of AI In Finance

AI is a powerful tool to analyze real-time activities in any given market or environment. It can work with more complex and sophisticated rules. It can explore new ways to provide extra benefits and comfort to individual users.

So, financial services providers across industries are leveraging AI to optimize their operations. Here are some popular ones:

Fraud Detection

AI models analyze large volumes of data from financial transactions to detect patterns and anomalies that could indicate fraudulent activity. They monitor clients’ behavior, location, and buying habits and trigger an alarm if something is out of order.

Investment Management

AI algorithms analyze market data, company financials, and other data to make investment decisions based on the data. Today, many AI-powered investment platforms help investors make better investment decisions.

Risk Management

AI can help banks and other financial institutions assess risk in loan applications, investment portfolios, and other areas of their business. AI-powered risk management systems can detect potential risks and recommend ways to mitigate them.

Customer Service

AI chatbots are increasingly used in the finance industry to provide customer support and answer customer inquiries. They are capable of providing comprehensive solutions and saving human resources. Besides, they can also check balances, schedule payments, look up account activity, etc.

Trading

AI-powered trading algorithms can analyze market data in real-time and make trades automatically based on that data. They leverage both stock data and trending news to make predictions and decisions. This is also known as algorithmic, quantitative, or high-frequency trading.

Personalized Recommendations

AI algorithms can analyze customer data like income, recurring expenses, and spending habits. Based on it, they can make personalized recommendations for financial products and services based on the customer’s needs and preferences.

As AI technology continues to advance, we can expect to see even more innovative applications of AI in the finance industry. One of them is increased transactional and account security.

But in whichever way AI is used, it has significant advantages.

Benefits of AI in Finance

The strategic application of AI’s many technologies, including machine learning, natural language processing, and computer vision, can drive meaningful results for financial institutions. The direct cost savings with the implementation of AI can be significant.

Here are some advantages of employing AI in Finance:

Minimum Risk Credit Decisions

AI can analyze the financial profiles of people more quickly and correctly. It considers a range of characteristics, with strict rules and regulations, to determine financial credibility. In case an individual has a poor financial profile, he or she can be denied financial credit. So, credit decisions can be made with minimal risk.

Round-the-clock Financial Consulting

With AI algorithms, individuals can get the information they want as rapidly as possible, whenever, wherever. They can get financial consulting based on analysis of their portfolio, the most recent trends, or the majority of sorts of essential financial information.

Protection Against Cyberattacks

Customers want to know that their payment and personal information will be kept as safe and protected as possible. AI can assist in monitoring financial systems and ensuring that any threats are avoided. It can replicate cyberattacks to locate compromised information and loopholes in the existing system. It can alert authorities well in time to take necessary action. Human mistake is thought to be responsible for up to 95% of cloud breaches.

Lowering False Positives and Human Errors

People do make mistakes, and operator error is an unavoidable occurrence. In the financial services business, 94% of IT professionals stated they are unsure that their employees, advisers, and partners can properly handle consumer data. Fortunately, artificial intelligence can assist in reducing false positives and human mistakes.

Improved Forecasting & Loan Risk Estimation

Artificial intelligence can evaluate a customer’s spending history and behaviors to forecast loan borrowing behavior. The algorithms can determine if or not a person will be able to return the loan, also in how much time.

It can help assess existing borrowers and identify new borrowers. This is especially significant in locations throughout the world where individuals have smartphones and other forms of connectivity and communication.

With so many advantages on the plate, the use of AI in Finance shall continue to grow.

Opportunities for AI in Finance

AI usage in finance is expected to grow as it helps financial firms gain a competitive edge in two primary ways:

Efficiency Boost

AI helps companies to reduce costs and enhance productivity, which leads to higher profitability.

Higher Customer Satisfaction

Thanks to AI, new highly-customized product offerings are becoming available to a growing number of consumers.

Limitations of AI in Finance

Some of the drawbacks of AI in the financial sector are:

High Costs

The advanced and premium technologies of AI are quite expensive and are not affordable for smaller organizations and those with limited finances.

Risk to Human Employment

Employment of AI raises the doubt of job loss to the workforce of the organizations, considering the rapid expansion of AI in day-to-day applications.

Complex Algorithms

AI employs complex ML and NLP algorithms for decision-making, which are extensively hard for people to understand and process the same. Hence many companies doubt investing in this technology.

Lack of Regulatory Scrutiny

AI requires scrutiny to avoid any kind of data leak or misuse of data which may lead to cyber attacks thereby putting the personal information of customers at high risk.

Future of AI in the Financial Sector

Financial services have recognized the potential of AI. Digital assistants and apps will continue to perfect themselves with improvements in cognitive computing like deep learning.

Managing personal finances will then be easier, especially as robots continue to do the heavy lifting of the day-to-day. Consumers and employees alike can focus on what matters, like longer-term decision-making and strategy.

With everything happening rapidly, the experts estimate AI to save the banking industry roughly $1 trillion by 2030.

If you wish to integrate AI into your financial system or want to know more about us, contact us today.