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6 examples of AI’s spreading influence on the financial services sector

Posted by Celene Robert

May 9, 2022

Artificial intelligence is empowering financial services firms to better serve their clients. An Economist Intelligence Unit study found that 86% of financial services executives plan to increase their AI-related investments through 2025.

Why financial services firms are turning to AI

Financial services firms are leveraging AI to realize several benefits. About 54% of financial service organizations with 5,000+ employees are now using AI to improve their business processes, according to Forbes. The following five points elaborate on how AI is transforming the financial services industry:

1. Providing predictive analytics

By leveraging AI solutions, companies can predict the behavior of millions of customers in seconds. AI and machine learning can provide financial services firms with predictive models and insights by processing large databases that enable them to optimize processes and minimize fraud. 

2. Reducing operational costs

Financial services firms are exploring new ways to integrate AI into their services, such as insurance, banking and asset management. Process automation accomplished by implementing AI-based solutions can eliminate human errors and save up to 70% of the operating costs associated with data entry and other repetitive tasks. 

3. Increasing opportunities for revenue growth

AI implementation is critical for financial services companies to remain competitive. A survey called the State of AI in Financial Services showed a significant financial impact of AI, with 34% of companies agreeing that AI would boost their annual revenue by at least 20%. 

4. Enhancing customer engagement and satisfaction

Fintech companies that invest in AI can improve customer satisfaction by using chatbots for frictionless, 24/7 customer interactions. AI-based virtual assistants can further help these companies to better understand their customers’ needs, in turn increasing customer engagement.

5. Improving cybersecurity

AI is playing a significant role in improving the fraud detection and prevention process in online banking. Financial institutions are using AI to improve the security of transactions and verify customers’ identities to meet regulatory requirements. 

Applications of AI in the financial services sector 

Because it offers a plethora of business benefits, AI algorithms are being implemented by most financial services companies⁠. Below are some of the most popular examples in which AI solutions are applied.

Algorithmic trading 

Data-driven investments — aka algorithmic, quantitative or high-frequency trading — have grown rapidly across the world’s stock markets. Intelligent trading systems use AI to make precise predictions based on historical and real-time data. AI-powered trading systems can analyze huge, complex data sets, enabling quick decision-making and transaction, thus increasing opportunities for profit. 

Example: Infinite Alpha uses AI to facilitate a cryptocurrency trading platform specifically designed for professional investors. It secures traders' data and transactions via advanced authentication and encryption. The trading platform provides users with an instinctive dashboard interface to easily access their account details, balances and transaction histories.

Fraud detection and prevention

AI enables financial services firms to analyze and detect irregularities in customers’ behaviors, locations and spending habits in real time. It can recognize suspicious or anomalous activity and trigger a security mechanism to reveal and prevent fraud.

Examples:  BNY Mellon, one of the largest payments service providers, has designed an AI-based fraud detection framework to defend its third-party data. The bank deployed AI and ML-based models trained on over 100 million data samples to identify patterns of fraudulent transactions that improved fraud detection accuracy by 20%. Another example is American Express, which uses AI-based algorithms to monitor every transaction on its platform in real time to detect fraud and render decisions in milliseconds.

Process automation

Financial services firms are using AI-powered solutions to trim operational costs and increase productivity and operational efficiency. AI can help such organizations to automate repetitive time-consuming tasks and eliminate human biases and errors. AI-enabled applications can also help firms to verify data, generate reports and review lengthy documents.

For instance, AI-enabled intelligent character recognition software can automate distinct mundane tasks such as entering customer data from contracts, forms and other sources and extracting information from documents like loan applications and agreements. 

Examples: Royal Bank of Canada has designed a private AI-based cloud to run simulations, train AI models and analyze large databases to deliver smarter and more secure services. The cloud is helping the bank in faster delivery of AI-enabled applications for their clients and customers to improve their banking experience.

Meanwhile, JP Morgan Chase also leverages AI-based process automation to perform otherwise time-consuming tasks such as data extraction, know your customer updates and capturing documents.

Personalized banking

Financial services firms leverage AI-enabled solutions to offer personalized products and services to customers, such as banking, lending and payments. They also use AI-based chatbots powered by natural language processing to offer 24/7 financial guidance to customers. 

Some also use voice-controlled virtual assistants to provide better customer service. AI-based applications employ algorithms that can track customers' regular expenses, income and purchasing habits to provide personalized financial advice based on the user’s financial goals.

Examples: Bank of America uses an AI-based mobile banking app to provide clients with reminders to pay bills, enable customers to plan expenses, and let them interact with the bank in an easier and more streamlined way.

Fintech Square uses conversational AI to empower its virtual assistant, which the company says can understand and answer 75% of customers’ queries.

Insurance claim processing

AI-enabled applications are transforming the insurance industry by improving the accuracy and efficiency of claims. The insurance claim management process frequently now employs a fully data-driven approach wherein AI analyzes all required documents to process and automate insurance claims. Using AI to automate claims processing also helps insurers to identify fraudulent claims and offer digital services to improve customer experience.

Examples: Cape Analytics uses AI to convert geospatial data into actionable insights to enable insurers and other property stakeholders to access valuable property characteristics at the time of underwriting. It also provides data about vegetation density and roof material that homeowners can use to protect their property, along with a calculated risk that insurers can use to write better policies.

NerdWallet is a finance company that uses AI to recommend the best financial products to meet the needs of their customers, such as credit cards, mortgages and insurance. 

Credit risk evaluation

An AI-based platform provides lending companies with a quick and accurate assessment of a potential borrower by considering several factors, such as their credit score and history. In other words, lenders can make better-informed, data-backed decisions to identify credit-worthy applicants and expedite the overall process of credit risk evaluation. 

Example: Fintech document automation software firm Ocrolus helps lenders to automate credit decisions. The company enables financial services organizations to make the right lending decisions by providing accurate data and analyses.

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