Once the stuff of science fiction novels, generative AI is now an accessible technology that is redefining how we do business. The fast-moving world of finance has embraced this powerful technology, and we’re seeing its impact in almost every aspect of the industry. From risk assessments to fraud protection, AI tools are redefining our approaches to old problems. Here, we’ll explore some of the most common uses of AI and machine learning in the world of finance.
- Fraud Detection Tools
If there’s one thing generative AI is good at, it’s pattern recognition and probability, making it a potentially useful option for the partial automation of fraud detection. AI can analyze vast volumes of data and recognize behavior that’s out of the ordinary. AI models can assess data in real time and detect changes or correlations that human analysts might miss. Any unusual behavior can be flagged for further analysis by a human, helping reduce the risk of false positives and also acting as a check and balance against any potential bias or other issues with the model.
- In-depth Credit Score Analysis
AI has the potential to improve the effectiveness of credit scoring, allowing businesses to make better decisions when it comes to assessing a customer’s creditworthiness. According to one recent study, AI-driven models can increase revenue by 5-15%, reduce credit loss by 20-40%, and offer efficiency improvements of up to 40%.
Rather than relying on static variables from a credit history, AI can analyze a broader range of data points ranging from total income and transaction history to work experience and wider behavioral data points, offering deeper insights into a potential customer’s creditworthiness. AI’s ability to look at current behavior patterns means it has the potential to identify signs of financial distress in a way other systems, which rely more on lagging indicators, might not be able to.
- Enhanced Productivity
Time-consuming tasks that require attention to detail and are often repeated lend themselves to AI’s performance. By handing over repetitive tasks to an algorithm, businesses enable employees to focus on more complex tasks requiring human judgment. In the long term, this can increase productivity, cut costs, and improve customer service.
Scripting, automation, and primitive bots have been available for many years. What makes the current generation of AI tools particularly interesting is their ability to provide more personalized responses and take context from the data being fed to them. This produces higher-quality answers, even for complex queries.
- Automation
Behind the fancy apps and websites users interact with today, many Fintech companies rely heavily on manual processing and verification. Manual processes are vulnerable to human error and can be slow and resource-intensive. Automating tasks, where possible, can be a game-changer for any business, making it easier to scale up their activities. One example of this is using chatbots as the frontline for customer support. These bots can handle frequent, simple queries, freeing up human agents to address more complex issues.
Generative AI can also assist with other financial tasks, from audit compliance to reporting. Embracing these tools doesn’t just save time, it opens opportunities for innovation. Fintech companies that learn how to use AI tools to their advantage can position themselves as industry leaders in both finance and technology.
- Accurate Financial Forecasting
Generative AI models are at their most useful when fed with large volumes of high-quality data. Companies in the financial sector can leverage AI models to generate forecasts, perform risk assessments, and simulate various scenarios. Today’s AI models can process data quickly and can be paired with easy-to-use tools to create charts, graphs, and reports. Many modern analytics tools have natural language interfaces, making them accessible to more users, so anyone can get access to the data they need to make wiser decisions.
AI is The Next Financial Revolution & It’s Already Happening
The Internet revolutionized the world of finance by opening borders and making trading a 24-hour endeavor. Traditional financial businesses were forced to adapt to a world where it was possible to perform financial tasks at home from a computer. AI is set to change the world of business in a similar way.
We’re already seeing the impact of AI as entry-level positions are being replaced by automation, and an entire new era of engineers is emerging. The job of “prompt engineer“, a person who devises AI prompts to generate optimal outputs, has appeared overnight, and “powered by AI” has become a common marketing slogan.
Taking advantage of generative AI in a cautious, ethical way is something every financial business needs to do. Those who get it right will become the new market leaders, and those who choose to ignore it risk being left behind in an increasingly competitive market.