10 Ways in Which Artificial Intelligence Is Revolutionizing the Financial Services Sector

Artificial intelligence (AI) has revolutionized the banking industry in recent years. AI is altering the rules of the game and revolutionizing the retail and wholesale banking industries. Similar to how "cloud natives" live in the world of cloud computing and "digital natives" were raised with technology, there exist "AI natives." 

Leading the way for the AI revolution in the banking sector are these AI experts, both personally and as organizations. With the advent of generative AI, this shift has accelerated. 

The 10 main ways that artificial intelligence (AI) is changing the retail banking industry are examined in this article, ranging from improved customer service to risk management and fraud prevention.

Artificial Intelligence is beginning to have a significant influence on the banking industry. These effects can be both positive and negative.

Intone Networks claims that artificial intelligence (AI) has improved the banking and fintech app development services sector by:

• Cutting back on operating expenses
• Increasing client assistance
• Enhancing risk-taking
• Regular procedures being automated
• Faster service delivery
• Increasing the precision and speed of data processing

According to Business Insider, artificial intelligence (AI) may save the banking sector almost $1 trillion by 2030 and $447 billion by 2025.

Even as artificial intelligence (AI) has many positive effects on the banking industry, it also has certain drawbacks. Forbes claims that AI exposes the sector to hazards including credit risk miscalculations, cyberattacks, and the much-feared loss of jobs and human capital, which will eventually be explained in this article. It is, however, undeniable that the beneficial impacts of AI outweigh the risks.

‌How Is AI Being Used in Finance?

The way we handle money in finance is evolving due to artificial intelligence. There are several ways that artificial intelligence (AI) may help the banking and financial sectors, from credit judgments to quantitative trading and fraud detection and prevention. Let's examine ten distinct applications of AI in banking and finance.

1. ‌Investment Management‌

The need for investors and asset managers to figure out how to incorporate AI into their investing operations is growing as the technology becomes more and more ingrained in the financial sector. Investment managers can create prediction models, examine technical and fundamental facts, and produce investment ideas more quickly and in real-time with AI. AI also turns investing into a passive process that needs less oversight, saving expenses and increasing revenue at the same time.

AI is also applicable to portfolio management:

• Risk assessment
• Supervision of compliance
• Mechanized analysis
• Task automation in the office

Man Group's hedge fund, which uses AI to manage over $12 billion in assets, has quintupled in size since 2014, according to Deloitte.

We have not yet reached the full potential of AI in investment management. Roughly nine percent of hedge funds use AI and machine learning for asset management and investments, according to the Alan Turing Institute. Nonetheless, a rise in this number is anticipated over time.

2. Risk Assessment

The volume of financial data that businesses process demands that the precision with which this data is processed also rise. However, the hands and minds of humans cannot accomplish this. This leaves room for fraud risk, which is now destroying the majority of financial services firms. According to a recent PwC analysis, on average six fraud instances were recorded per organization, and 47% of the companies under investigation were victims of fraud.

A business has to examine each and every transaction in massive data sets in order to identify even the smallest risk. AI can help with this. Financial organizations can now quickly sift through massive amounts of data and accurately identify abnormalities that support risk assessment and mitigation with the use of AI auditing tools.

Financial firms no longer need to do quarterly or annual audits since AI makes auditing tasks easier. Instead, they may have the AI perform a monthly analysis. By conducting ongoing audits, businesses may identify and address problems as soon as they arise.

3. Credit Evaluation

Financial institutions carry out a credit evaluation procedure to ascertain an individual's eligibility for credit. This procedure entails:

• Getting pertinent details about the candidate
• Using the information gathered to assess the applicant's creditworthiness
• Choosing whether to give the applicant credit
• Selecting the credit amount

Time and money are two limitations of this process. If a business requests credit too long, it might lose out on a potential customer. In the event that the evaluation procedure is done poorly, they also run the danger of losing their money.

However with AI credit assessment, these risks are neutralized. Numerous factors, such as credit card history, payment history, amount due, and duration of credit history, are taken into account when evaluating credit.

Even though AI makes it easier to swiftly sort through large amounts of data, it also has the power to greatly improve the assessment process. Even if a new client is creditworthy, the credit rating process based on past performance presents a hurdle.

Credit scores may be assessed using AI credit evaluation using forecasted and historical data. In this manner, the historical-based credit barrier can be surmounted by new clients, students, and startup founders. Financial firms aim to gain from AI credit evaluation by gaining more clients and lowering risks. Consumers, however, have more impartial and superior access to credit services.

4. Securities Trading

Computers can use AI trading solutions to:

• Think for yourself
• Examine previous market data
• Create plans based on such information.
• Make choices about trading.
• Control risk

AI-led hedge funds appear to have an advantage over others, according to certain research. In the last three years, these funds have produced an average return of 34%, as opposed to the worldwide hedge fund industry's 12%.

5. Risk Management

Financial institutions always face risks, including:

• Theft of identity
• Credit danger
• Fraud danger
• Risk underwriting

AI reduces these risks by identifying trends and reducing risk when they are broken through the use of advanced analytics and predictive analytics.

An excellent illustration would be financial identity theft. Before more harm could be done, the AI would identify abnormalities in the card's purchasing activity and block the card. AI is also capable of predicting the likelihood that a customer would fail and stopping the credit from being given, sparing the bank from a bad loan.

The three risk management domains that Infopulse determined would gain the most from AI are as follows:

Early warning systems: a means of managing credit risk

Stress testing: a tool for managing economic and market risk

Data quality: for managing the risk of fraud

6. Fraud Detection

Fraud has always been a threat to the banking and financial sectors. Crowe claims that fraud takes $5 trillion out of the world economy annually, and that amount is still rising. Machine learning is replacing traditional fraud protection techniques because it is more effective at what it does.

These days, fraud detection algorithms are always learning from past transactions to identify fraud patterns in future transactions. They also make data analysis easier, which allows fraud analysts to concentrate on what really important and work more efficiently.

Thanks to AI fraud detection and prevention, Highmark Inc. has saved over $850 million in fraud prevention over the past five years. Imagine now how much AI would save the world economy.

7. Personalized Banking ‌

In today's corporate environment, establishing enduring connections and fostering client loyalty depend heavily on customer pleasure. In a poll conducted by Accenture, more than 80% of 47,000 banking and insurance customers said they would be prepared to swap specialized services for the sharing of their personal data.

Banks and other financial institutions should use AI's capabilities to gain a competitive edge in order to meet these needs. Chatbots and AI predictive personalization are examples of tools that assist in:

• Streamlining communications with customers
• Individualized smartphone banking
• Advising customers on how to save and spend
• Defending against deception
• Delivering customized marketing communications

8. Debt Management

For many firms, managing and collecting debt is still a difficult issue. According to CNBC, the typical American has $90,450 in debt, and that number is rising every year.

But debt collection doesn't have to be a difficult, ineffective, and antiquated procedure anymore, thanks to AI. Businesses may now automate, simplify, and improve this process while preserving positive customer relations by utilizing behavioral science, data analytics, and machine learning.

According to Receeve, AI will change the way that data is collected by:

• Making use of data and analytics to increase payback rates
• Using behavioral science to create debt recovery plans tailored to each unique client
• Process automation for payments
• AI-powered A/B testing

9. Customer Service

Any firm that wants to succeed must maintain positive relationships with its customers. Vendors should use AI customer care technologies to guarantee the highest level of client satisfaction.

Surprisingly, the second most popular application of AI is in customer support. Additionally, the industry was projected to earn $4.5 billion in AI investments in 2020, the largest of any other subject. According to the 2019 Chatbot Report, 90% of customer interactions in banking customer care are anticipated to be automated using chatbots by 2022 as a result of the use of AI and data science.

Among the instruments that AI is being utilized in customer service are the following:

• Chatbots
• Bots for email
• Call-bots
• Voice and Face Identification

10. Compliance Oversight

In the financial industry, compliance is crucial since it guarantees that companies adhere to both internal and external regulations. This guards against the dangers associated with breaking these regulations and guarantees market efficiency, fairness, and openness for financial institutions.

Compliance officers used to be entrusted with sifting through different communication channels to look for anything immoral or illegal. This task was expensive, time-consuming, and prone to numerous mistakes, which increased the likelihood of consequences.

But AI has made it easier to oversee compliance. Compliance teams can efficiently and accurately go through several data sets in the least amount of time thanks to AI.

The beauty of AI is that thanks to machine learning, compliance may now be based on anything novel or unusual in addition to following a predetermined set of criteria. AI recognizes new rarities and enhances the whole compliance procedure in the event of a new oddity. As a result, compliance inside an organization becomes a self-sustaining mechanism.

89% of the participating firms in a recent NICE Actimize poll acknowledged that they were moving toward utilizing AI for compliance-related reasons. 

It's time to accept AI as the new compliance officer, despite concerns of data breaches, prejudice, and discrimination, which prompted the creation of the AI Act by the European Union.

Which Industries Are Benefiting the Most When it Comes to AI in Finance?

Certain segments of the financial industry are benefiting more from AI in finance than others, and these include:

Banks

Without question, banks have profited the most from artificial intelligence in the financial industry. Banking institutions have used AI to:

• Lower operating expenses by utilizing robotic process automation
• Boost the management of consumer relationships.
• Detect fraud more effectively and adhere to regulations
• Enhance the methods used to evaluate credit
• Automate the process of investing.
• Enhanced debt administration

Banks classified as retail, commercial, or investment comprise the majority of the financial industry. They stand to gain the most from artificial intelligence in the financial sector.

Funds and Investments

Hedge funds and investment organizations are among the other major benefactors of artificial intelligence in finance. The following are some ways that AI has helped these businesses:

• Systems for automated trading
• Instantaneous high-frequency trading backed by data
• Better data examination
• Enhanced risk mitigation
• Increased capacity to produce alpha

Insurance

Finally, but just as importantly, the following are some ways that AI has helped insurance companies:

• Individual pricing for customers based on data
• Automating the processing of claims
• Automated payments
• Improved identification of fraud

Pros and Cons of AI in Finance

AI has both advantages and disadvantages, particularly for the financial industry.

A few benefits of AI in finance are as follows:

• More rapid and precise data analysis Improved risk assessment and management
• Enhanced fraud prevention and detection
• Get rid of human mistakes
• Enhanced data quality Better judgment

Several drawbacks of AI in finance include:

• High expenses for installation and upkeep
• Incapacity to render decisions
• Stifles individual inventiveness

Future of AI in Finance

With the assistance of data scientists, artificial intelligence (AI) in banking is still in its infancy and is spreading rapidly. Financial AI will undoubtedly see more incremental and architectural advancements in the years to come, despite the disruptive advances that have resulted from it.

There has never been a time in history when humans have not innovated. It is reasonable to assume that, given its ongoing advancements, artificial intelligence (AI) will continue to discover new applications and establish itself even more firmly in the financial industry.

Hire a professional mobile app development company that includes AI in their FinTech development services to leverage the competitive advantage in the business.