Artificial intelligence (AI) is no longer a sci-fi-esque buzzword; it’s a transformative force that is reshaping how financial operations are conducted as we speak.
For controllers and CFOs, understanding and leveraging AI is not only pivotal to staying ahead in today’s fast-paced financial landscape but also to helping your business navigate uncharted waters and prepare for the future of finance.
On that note, join us as we explore some of the key use cases for AI in the finance sector and cover some real-world examples of AI in action:
AI in Automated Data Analysis
One of the most significant contributions of AI in finance is seen in the realm of data analysis. Traditional data processing methods are often time-consuming and prone to human error; AI, however, can analyze vast amounts of data quickly and accurately, providing insights that were previously unattainable.
Real-World Example: JPMorgan Chase
JPMorgan Chase’s AI-based contract intelligence (COIN) program has been around for roughly seven years, automating the interpretation of commercial loan agreements, a task that previously consumed 360,000 hours of work each year. By deploying COIN, the bank saves an enormous amount of time and reduces the likelihood of human error.
AI in Predictive Modeling
Predictive modeling is another area where AI excels. By analyzing historical data and identifying patterns, AI can predict future financial trends, allowing companies to make proactive, informed decisions.
Real-World Example: American Express
American Express uses AI to analyze historical transaction data to predict consumer behavior and identify potential cases of fraud, enabling the company to take preventive measures to reduce the risk of fraud and enhance customer trust.
Since the rollout of its AI system, American Express has lowered its fraud losses by 30%, representing a substantial cost-saving measure for the organization that also enhances the consumer experience.
AI in Risk Management
Looming cybersecurity threats and compliance headaches can keep you up at night, but you’ll be happy to breathe a sigh of relief, knowing that AI may hold the key to peace of mind for CFOs and controllers the world over.
AI is transforming how risks are identified, assessed, and mitigated. The most advanced algorithms can even evolve their threat response protocols in real-time, allowing them to adapt and address sophisticated cyber threats.
AI also plays a role in detecting financial risks, such as credit and market risks, in turn allowing it to help insulate your organization from major profit losses.
Real-World Example: UBS
UBS employs AI to enhance its risk management framework, using machine learning algorithms to detect patterns that indicate risks that allow the bank to take timely action to mitigate potential issues. UBS’s proactive approach to risk management has significantly reduced its exposure to financial risks.
AI in Customer Service and Personalization
AI is also revolutionizing customer service in finance. Chatbots and virtual assistants powered by AI can handle customer queries, provide personalized financial advice, and even assist with transactions.
Real-World Example: Bank of America
Bank of America’s virtual assistant, Erica, is built upon AI and provides personalized banking services to customers. Erica can analyze customers’ financial histories, offer tailored financial advice, and assist with everyday banking tasks. Moreover, it accelerates the delivery of support, enhancing overall customer support.
In mid-2023, Bank of America announced that Erica had completed 1.5 billion customer interactions, and in support of the continued adoption of AI-powered self-help, Bank of America has recently upgraded Erica to make interactions feel more human.
AI in Financial Forecasting
Financial forecasting is essential for long-term strategic planning, and AI can enhance the accuracy of your forecasting efforts by allowing you to analyze more data, obtain relevant insights, and access dynamic market trends.
While current AI forecasting tools aren’t infallible, they are impressively accurate. You can combine these insights with your financial acumen to make informed business decisions and mitigate risk.
Real-World Example: IBM
IBM’s Watson uses AI to assist businesses in financial forecasting. By analyzing market data, Watson can provide accurate financial forecasts, enabling businesses to make more informed strategic decisions.
Watson is far from the only AI-powered financial forecasting solution, but it is one of the world’s most advanced platforms. It has exceptional analytics capabilities and is a testament to the sheer volume of data that an AI algorithm can process.
The Many Uses of AI
AI is not just changing finance; it’s revolutionizing it. From automated data analysis to predictive modeling, risk management, and customer service, the applications of AI in finance are vast and diverse, and as a financial leader, embracing AI is no longer optional for you; it’s essential for driving efficiency, accuracy, and decision-making.
That said, the applications for AI are many, and you’ll have to decide which use cases to prioritize first. Winning the AI race isn’t about being first; it’s about strategically investing in technologies that yield a strong ROI and condensed time to value.
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