AI in Finance: Applications & Benefits For Fintech Industry

Artificial intelligence is transforming every industry it touches, and the financial sector is no exception. AI in finance is game changer for financial institutions, helping them make faster decisions, reduce operational costs, and enhance customer satisfaction.

It's changing how banks interact with customers, providing personalized advice, and detecting fraud with 100% accuracy.

Consider this: a fraud detection review that typically takes analysts 90 minutes of manual work can now be completed by Generative AI in under 30 minutes.

This is just a one-use case of AI in fraud detection. Want to know other benefits and applications of how AI is used in the financial sector? Read this blog to learn more.

What Does AI in Finance Include? 

AI in finance helps banks and financial institutions to analyze large amounts of data and improve their decision-making processes in the areas of risk assessment, fraud detection, customer service, investment strategies, and other compliance related tasks.

Integration of chatbots on websites and mobile apps ensures that customers get personalized attention. Unlike human staff, banking chatbots are available all day and never get tired or sleepy.

These AI chatbots are not just confined to providing speedy customer service; they can upsell financial products/services on behalf of banking agents.

Overall, AI is helping financial institutions to improve the accuracy of transactions, provide speedy customer service, and extract valuable insights from data collected through customer interactions.

One of the main benefits is automation of routine tasks and banks can handle their transactions quickly. Customers can use chatbots 24/7.

59% of US banks used AI to reduce their costs. In comparison, LATAM banks (48%) achieved a competitive edge in the industry.

That's how AI in banking and finance is transforming banks and the financial services sector.

Market Size and Growth of AI in Finance Industry

From performing number crunching to analyzing vast amounts of data and making informed decisions based on that, Artificial Intelligence is a game changer for banks and financial institutions.

1) A report from Markets and Markets states that the AI in Finance market was estimated at $ 38.36 billion in 2024, and its usage is expected to reach $190.33 billion by 2030.

2) North America is the leading player in the Finance market, which leverages artificial intelligence to the full extent.

3) The market size of AI in the fintech segment is expected to rise at a CAGR (16.5%) from 2022 to 2030.

4) The reason behind this increasing growth is that many financial institutions are utilizing artificial intelligence technology to automate their banking operations, detect fraud, and protect customer security, thereby ensuring the safety of their funds.

Benefits of AI in Finance

AI is present everywhere, and it's not new in this world. Consider the times when web chatbots, such as Apple's Siri, and financial institutions leveraged the power of LLMs.

37% of respondents stated that AI improved operational efficiency, which was a decrease compared to the previous year. But this was one of the primary benefits of integrating Artificial intelligence.

1) Enhances Customer Experience

Have you ever noticed how, on your favorite streaming platform, there's always that perfect movie for you, knowing exactly how you feel now?

AI works similarly to fintech, performing analysis on vast volumes of data and recommending financial products or policies based on customer needs.

Surprisingly, up to 80% of consumers actively look for and, thereafter, do business with companies that interact with them based on personal experience.

Moreover, initially, financial service businesses need to focus on providing speedy support to customers. With the integration of AI, the way finance companies operate, serve their customers, and manage money has changed.

Today, customers can access financial services quickly with the help of conversational AI, such as chatbots or virtual assistants. They can find a better credit card that suits their requirements and cancel unneeded accounts with a few clicks.

These AI agents have become a productivity tool for bank agents, as they can offer personalized advice that's tailored to a customer's unique financial situation.

Tools such as Mindstream and SuperHuman first analyze customers' data and then provide personalized suggestions to them, whether it's about offering loan options or creating investment strategies.

Beyond providing immediate resolution to their queries, AI in fintech is also offering convenience to customers. As everything has shifted to a virtual mode, this reduces the need for in-person interactions, as basic banking activities are now automated.

This isn't helpful only for bringing in new customers but also for retaining existing ones.

2) Improves Fraud Detection

Financial institutions that use AI-driven analytics and fraud detection systems have seen significant benefits from AI and experienced a reduction in losses.

Its intelligent algorithms analyze vast amounts of data and then identify suspicious transactions that the human eye might miss.

As digital businesses grow, they come with increased cyber risks and phishing scams. These automated systems do a great job at monitoring billions of records, pattern recognition, and spotting anomalies.

Similarly, in banks, these AI-powered fraud detection systems track banking and financial activities, identify app usage, and block suspicious attempts based on the data they have been trained on.

As machine learning and artificial intelligence can distinguish between fraudulent and legitimate transactions, it can reduce the risk of such fraud. A study by Capgemini found that 75% of financial institutions utilized AI, resulting in a 25% reduction in costs.

For instance, Logic Federal Credit Union makes banking convenient for its customers. As a leading financial institution in America, it offers a wide range of banking services and loans for individuals and businesses.

Although they had a team of 12 investigators, it was a time-consuming task for them to detect fraudulent documents from time to time.

To verify the documents, they needed to keep a few samples, compare the files, or even contact banks or financial institutions to verify them.

With the automated fraud detection mechanism, investigators saved hours and prevented a loss of $3 million.

3) Cost Reduction

Banks and financial institutions that utilize artificial intelligence experienced a 32% increase in profits in 2024. From fraud detection to customer service, financial companies that utilize AI can reduce operational costs and improve customer satisfaction.

Through the automation of tasks, financial institutions don't have to spend thousands on hiring manual labour. This saves them money and makes them more operationally efficient.

Whether it’s about processing loans, reconciling transactions, or managing back-office tasks, banks still rely on manual processes that are time-consuming, slow, and prone to human errors.

Think about when loan approval takes days to process, but with the help of AI and ML, customers can get the loan approved in a few seconds. This means speedy service for customers and lower costs for banks. How?

1. Integrate AI-driven solutions for manual tasks, such as document processing, loan approval, and toner support, that take hours and waste your labour costs. Deploy an AI-driven solution to solve a bunch of customer queries online.
2. As everything is online these days, AI tools can reduce paperwork and speed up back-office operations.

4) Improves Operational Efficiency

In the financial sector, AI serves as a timesaver by automating basic manual tasks. It can provide unique insights by analyzing vast amounts of financial data.

On the operations side, Artificial intelligence can automate backend routine tasks, such as loan processing, and speed up insurance claims, all while reducing errors. That saves time and money for insurance companies and financial analysts.

Here's how AI is making financial professionals more efficient in several ways:

1. Automation of data entry work frees human staff to focus on complex projects that require problem-solving and logical thinking skills.
2. Manual verification efforts are reduced when KYC-related processes are automated.
3. On the front side, AI-powered chatbots can assist customers in banking-related tasks and account transactions.

Agustin Rubini, Director Analyst at the Financial Services and Banking team at Gartner, says that AI doesn't replace jobs, but it replaces tasks. It automates nearly 80% of the routine tasks.

Applications of Artificial Intelligence in Finance Industry

1) Robo-Advisors and Automated Wealth Management

Personal guidance in Finance is a trend nowadays, but it comes at a high cost as well.

With robo-advisors, banks and financial institutions can provide personalized advice to their clients. Consider robo advisors as personal virtual assistants who can do the following things for financial firms, such as -

1. Portfolio management
2. Personalized investment recommendations
3. Performance tracking of investments
4. Retirement planning tools

These AI and ML technologies have become remarkably advanced in recent years. Because they are trained on vast amounts of data, they can suggest personalized solutions for each individual, considering their risk tolerance, financial goals, and past financial history.

In the US, robo-advisors are managing assets for clients, and the graph below shows a steady increase in the use of these automated technologies year by year.

Source

Best part? These advisors are cost-effective and easier to maintain, as they never sleep and never make emotional decisions.

The primary goal of robo-advisors is to help clients grow their wealth by allocating funds across various asset classes. The goal is to maximize the return on investment for the money invested on behalf of the client.

Bad part? It's risky for financial firms, as robo-advisors have access to a customer's economic data. If any breach occurs, it costs them millions in loss and damages their business reputation.

Real-life Example

The National Bank of Canada implemented robo-advisory services for its portfolio management solution. For customers, this results in customized portfolios, and for banks, it leads to cost savings.

2) Automated Credit Scoring and Approval

Traditional credit scoring platforms often have certain limitations, as they rely on the borrower's credit history and adhere to fixed rules.

However, it creates a challenge for businesses and individuals with little to no financial background and no credit history who still want to obtain a loan.

This prevents people living in rural areas from accessing credit, as they often lack a strong financial history.

Reason? They generally rely on informal sources of financing, such as chit funds and self-help groups, so it's challenging for credit risk executives to assess the creditworthiness of those individuals.

Additionally, the traditional credit scoring process is time-consuming and prone to manual errors.

But AI in finance simplify the credit scoring process by analyzing data from multiple sources, such as -

1. Analyze data from other sources such as social media, utility bills, and transaction histories.
2. Spot the risk patterns and tell the probabilities when the borrower is likely to default.
3. The model attempts to improve and learn as new data becomes available.

By implementing AI-based credit scoring systems, financial service companies such as HSBC Bank reduced their decision-making time to analyze financial statements and borrowers' credit histories from 2 hours to just 15 minutes.

As it speeds up the loan approval process, this increases customer satisfaction. Of course, human elements are always required in loops, but Artificial intelligence reduces the likelihood of defaults by not sanctioning the funds to the wrong borrower.

3) Personalized Chatbots and Banking Assistants

Today, customers expect bankers to provide personalized and round-the-clock services. In financial customer service, conversational AI is gaining huge prominence these days by automating 90% of customer interactions.

This means banks are now becoming AI-first by automating basic servicing requests and freeing up their human staff to focus on other areas.

AI-based banking assistants are changing the way customers interact with banks.

As Artificial intelligence is aware of a customer's financial history and account balance, it can suggest personalized financial advice and investment strategies to help manage their funds with ease.

Best part? It can increase bank conversions by upselling and cross-selling financial products, turning first-time users into loyal customers.

These AI-powered chatbots enhance customer satisfaction because of 3 things:

1. Provides speedy responses to queries
2. Round-the-clock assistance
3. No more waiting time

Bank of America launched its AI-powered financial assistant, Erica, to help 37 million customers. This conversational AI has facilitated over 1.5 million interactions with customers, and Erica has significantly improved client engagement rates.

Erica is helping the Bank of America's customers in the following ways:

1. Access the account information
2. Send money to different accounts
3. Remind customers about any upcoming bills
4. Suggest the nearby ATM

4) Algorithmic Trading Systems

Unlike human agents, AI can analyze mountains of data and identify market movements in milliseconds. The integration of Algorithmic trading in Finance is changing the way investments are managed, as well as predicting stock prices.

It helps banks and investment firms make informed trading decisions by analyzing market trends and economic indicators in real time. A study from JP Morgan states that in the US market, more than 60% of trades are conducted through AI algorithms.

Benefits?

Such algorithmic trading systems enable fast calculations at lightning speed. They can help human traders make data-driven decisions based on factors such as historical price values, trading volumes, and other relevant data.

It can protect traders from significant losses by predicting what-if scenarios and sudden market changes, and making trading strategies accordingly.

5) Automated Document Processing

Banks and Insurance companies rely on paperwork and employ human agents to review documents and conduct the verification process manually.

Whether it's a finance document, such as an invoice, compliance record, or loan application, which can be several hundred pages long, traditional systems require hours of manual validation.

That's why it's a slow, time-consuming and expensive process which sometimes becomes unsustainable for banks. Traditional systems require hours to review the loan documentation; with the use of AI in finance, the same task in a few seconds.

Source

Such AI-powered systems have improved document processing time, reduced manual errors, and enhanced financial outcomes. Result? Faster loan approval process = More satisfied clients.

Studies indicate that banks utilizing intelligent automated processing systems have seen a 75% reduction in reporting errors and increased transparency in their financial records.

For instance, DSB Bank has adopted an intelligent document processing system to speed up its credit card application process. Initially, it used to take 5 days, but it has now been reduced to 1 day. This means more efficient workflows and improved customer satisfaction.

How Can BigOhTech Help You Develop Solutions Using Artificial Intelligence in Finance?

AI in banking and finance is a disruptive force that's reshaping how the financial sector operates, driving smarter decisions, automation, and enhanced customer experiences. Banks that have adopted custom AI solutions have experienced higher profits (approximately $1.439 billion US dollars).

While fraud detection systems prevent banks from significant losses, those who develop AI-powered bots are free to focus on complex tasks.

Creating custom banking applications is no longer an optional upgrade; instead, it's a vital tool for reducing costs, enhancing the customer experience, and generating additional revenue.

As an AI/ML development company, we have a team of expert engineers who can build custom solutions (such as robotic process automation and ChatGPT solutions) for your business that keep customer information safe and comply with global financial regulations, including GDPR, PCI-DSS, and ePrivacy.

Whether you need help:

1. Personalize customer experience through virtual AI assistants
2. Automate the credit scoring process
3. Get rid of manual document processing
4. Creating algorithmic trading systems

Connect with our fintech app developers now and get a user-friendly banking app or mobile wallet for your business.

We've developed a web panel for our clients, enabling them to assist SMEs in managing their finances.

The client needed help in creating a financial system that can manage and issue credit cards to users within their organization. Our app developers have created a secure and scalable platform that is both PCI and AoDA compliant.

Result? One dashboard to monitor transactions. Track expenses and spending in one place.

FAQs

Q1) What is the future of AI in finance?

A1) AI isn't a replacement for humans, as it adds value to banking and financial companies. AI copilots will be available in the future, making human staff more productive. Hyper personalization will be prevalent in the finance sector, where AI is utilized for sending personalized product recommendations and generating content.

Q2) How is AI used in financial risk management?

A2) AI in risk management can be used for detecting fraud. For instance, if the AI algorithms predict that there is a voluminous amount of customer spending using credit cards, then the AI may not detect this as a legitimate transaction. It can be used to predict demand for inventory by analyzing historical data, market trends, and other economic factors. For instance, AI can predict the demand for specific products during this season, allowing companies to plan their inventory accordingly.

Q3) How does AI assist financial analysts?

A3) AI is helping financial analysts streamline their workflow, as they spend 60-70% of their time collecting and extracting data from various sources and then compiling it in a structured manner. This task is both big and time-consuming these days. However, LLMs can be a game changer for financial analysis, as they don’t just perform number crunching; instead, they work with unstructured data and generate insights about financial performance or company performance.

Q4) How is generative AI used in accounting and financial modelling?

A4) Generative AI is used for accounting and financial tasks. It can do the following functions, which are given below -

1. Simplify bookkeeping processes
2. Creating virtual bots for audits and complex accounting tasks
3. Analysis of financial data to provide valuable insights