5 Use Cases of AI in the Financial Industry

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The financial services industry faces increased challenges of random instability, uncertainty, and unpredictability. Global economic shocks can arrive through many sources like the COVID-19 pandemic and many recent upheavals. That’s why many leaders have turned to increasingly efficient AI applications to remove uncertainties caused by human error, and speed up trades and the dissemination of information 24/7.

Keeping up with criminal attacks on financial industries becomes more difficult because of new ways of creative ways of money laundering, more complex regulatory mandates that limit what businesses can do, and the technological capabilities of your competitors. That’s why many experts recommend AI applications for evening the playing field. The benefits of artificial intelligence usage in finance include:

  • Personalizing financial products and services
  • Creating business opportunities based on speed
  • Automating operations
  • Managing risk and fraud
  • Fostering better compliance and transparency
  • Reducing costs
  • Enabling faster communications and processing

There’s no end in sight for all the benefits of generative AI applications.

AI Application in Finance

financial services application

The potential of AI to transform financial services and improve efficiency, security, and customer experience. The possible use of AI financial service applications has reached a watershed moment in time that can transform the industry and set new highs for efficiency, security and the crucial customer experience. Artificial intelligence use cases have become widespread within the financial industry within a fairly short time, and the sky’s the limit for new applications from creative, focused companies like financial software development services. Five of the top uses include the following uses.

1. Fraud Detection and Prevention

Advanced software algorithms can change the scope of fraud. Enhancing AI efforts for social engineering creates vast opportunities for fraudulent scams. It’s important to protect your company with your own fraud detection software. Ideally, proper software works proactively to detect and prevent actions that might expose your company to criminal fraud.

2. Algorithmic Trading

You can’t keep up manually with trades that often earn small profits many times a day or even a fraction of a second. AI use cases in finance favor algorithm trading that takes place in fractions of a second. The opportunities come from the speed, adaptability, and accuracy of AI-generated trades. Many brokers and investors already use AI for its predictive analytics and real-time access to data.

3. Chatbots for Customer Service

If you visit many websites, you already know that chatbots have taken a major hold over customer service in all industries. Financial services can use chatbots to answer queries, manage accounts, and provide customer support in the fast-moving financial industry where people want immediate answers. Chatbots generate cost savings and improve the customer experience. Using these chatbots boosts customer service, saves money spent on human customer service reps, and creates a clear trail of everything to address the situation.

4. Credit Scoring and Risk Assessment

AI can analyze more data tailored to specific demographic groups to assess a person’s creditworthiness for business or personal loans. The same tools also work for assessing risk management, which insurance companies and other financial concerns make to underwrite policies and expedite important decisions.

5. Personalized Financial Advice

AI-driven robotic advisors have the unique ability to analyze vast amounts of data to create personalized financial reports and provide investment advice on the current market and the investor’s goals.

Uses for generative AI for personalized financial services include:

  • Developing financial forecasts and budgets using predictive analytics, modeling, and hypothetical market scenarios.
  • Providing financial insights to businesses researching trends and how to capitalize on them.
  • Using AI to produce financial insights and commentary
  • Cutting the time needed to produce business reports on-demand, recurring reports, and information for special projects
  • Automating intelligence gathering by creating predictive templates for any market upheaval
  • Leveraging generative AI’s vast language model for more access to a wide cross-section of public opinion for generating slanted market insights, competitive intelligence, and personalized analyses
  • Analyzing data for CRM and ERP applications to provide personalize marketing strategies
  • Managing customer business contracts to trigger alerts when terms expire] and provide data on any customer service issues
  • Detecting errors, fraud signs, and financial anomalies

Summary of Using AI Intelligently for Business

Many firms from all industries now invest in AI software to meet their goals, which tend to be virtually unlimited. Creative use of AI solutions for the financial service industry generates tangible, measurable, and verifiable results. Like any new technology, there must be integration with human-based staff, the company’s culture, and extant technology.

Failing to use AI resources in your financial business means that you could fall behind your competitors, risk large losses to fraud, and fail to capitalize on time-sensitive market opportunities. Your customers expect you to execute their business securely and efficiently with the latest financial tools available. The only way to do that in the backbiting financial services industry is to stay ahead of the game with your own AI software.

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Becca Williams is a writer, editor, and small business owner. She writes a column for and many more major media outlets.