In finance, sometimes the struggle is real: Every finance department knows the challenges of sifting through mountains of data, performing labor-intensive data entry, and trying to predict the future financial forecast. Luckily, artificial intelligence (AI) in finance is the ultimate problem-solver.
How is AI used in finance? It can automate mundane tasks, detect noncompliance, provide actionable insights, and predict future trends—all while you sip your coffee. If it sounds like AI for financial analysis can do a lot, you’re right. So let’s dive in.
The types of AI in finance
AI has evolved quickly over the past decade or so to meet the diverse needs of finance departments. Here’s a deeper dive into the different types of AI and the roles they play in financial analysis.
Machine learning
Machine learning (ML) uses algorithms to actively learn from data and make predictions or decisions. It can analyze visual data and work closely with deep learning for more complex pattern recognition. For finance execs, ML is a powerful tool that can help predict future cash flows, forecast market trends, identify financial risks, optimize investment strategies, and streamline operations.
ML algorithms continuously improve as they process more data, becoming increasingly accurate and reliable over time. These algorithms are the backbone of modern AI in financial analysis, providing the foundation for deep learning, generative AI, and conversational analytics.
Deep learning
Deep learning uses neural networks with many (“deep”) layers to analyze data. It builds on the capabilities of ML by handling more complex and nuanced analysis of larger datasets. For example, deep learning models can analyze voice and text data to detect sentiment in customer interactions, so they’re often used in customer service.
This type of AI for financial analysis does many of the same things as ML, but on a deeper level. Deep learning AI can help finance departments by improving cash flow forecasting, optimizing budget allocations, predicting financial risks, enhancing expense management, and automating complex financial reporting.
Conversational and generative AI
Conversational and generative AI (GenAI) create new content based on existing data. Like deep learning models, they’re trained to learn from patterns in large data sets, then replicate those patterns in their output. While there are some concerns around the privacy and accuracy of GenAI, the best AI solutions for finance are traceable and repeatable, so you can confidently take the training wheels off.
GenAI is especially useful for exploring data, hypotheses, and potential outcomes. From simulating financial scenarios, to summarizing key points in contracts, to analyzing spending patterns, it’s easy to see why this is a popular type of AI for financial analysts. There are even financial reporting AI bots that can generate financial reports and draft complex presentations.
Important applications of AI for financial analysis
Learning how to use AI to analyze financial data is a must for any finance department. Here are the top applications of AI in finance.
Task automation
Gone are the days of manual data entry and tedious invoice matching. AI automates these processes, improving accuracy and freeing up your team. For example, AI can scan, input, and automatically match purchase orders with invoices and payments. The latest AI finance tools go even further, using intelligent algorithms to handle complex workflows like expense approval and financial close processes—all without breaking a sweat (like a human might).
Risk and compliance
Risk management and compliance are critical in finance. Financial analysis AI can detect anomalies and outliers in financial data, review lengthy documents, contracts, and policies for noncompliance, and analyze transactions and communications for compliance issues. It can even review regulations for you so that you stay up to date. For finance execs, it’s like having a detective on your team who never takes a day off.
Reporting
Traditional dashboards can be rigid and hard to adjust. But with AI, financial reporting gets a whole lot easier. AI introduces iterative analytics, which allows for dynamic reporting that evolves with your needs. Using AI in financial reporting, you can dive deep into the data, uncovering insights that static dashboards might miss and generating reports that tell a story, instead of just presenting numbers.
Budgeting and planning
One of the most exciting areas of AI for financial analysis is predictive AI, which uses historical data to help inform future decisions. While it’s not a complete replacement for human decision-making, it can show causality and point you in the right direction. For example, AI can find correlations you might otherwise miss, like fluctuations in supplier pricing that impact profit margins or delayed payments that cause cash flow issues. That helps you turn uncertainty into opportunity.
How to use conversational AI to analyze financial data
Conversational AI is the ultimate solution for finance executives, and DataChat has mastered it. Our no-code, generative AI platform for instant, iterative analytics adapts to your needs and gets you answers faster. Here’s how to use this type of AI to analyze financial data.
Set up your data for analysis
First, load your data into the platform. You’ll still need to clean and wrangle it to set the foundation for your AI financial analysis, which involves identifying and correcting inaccuracies, handling missing data, and making sure everything is formatted correctly. However, many of these processes can be automated with DataChat. This initial step is essential because the quality of your insights depends on the quality of your data.
Formulate questions to ask your data
Next, identify the key questions you want your AI financial analyst to answer. Are you looking to understand cash flow patterns, predict future revenues, or identify potential noncompliance? With a clear understanding of your goals, you can formulate meaningful questions. For example, if you’re interested in cash flow patterns, ask questions about seasonal variations or quarterly trends in revenue and expenses. Starting with high-level questions helps you uncover deeper insights as you iterate.
Keep iterating
As you get answers to your high-level questions, ask more detailed questions to investigate further. For example, “What caused the spike in expenses last month?” After that, you might want to investigate whether similar patterns have occurred in the past, what actions were taken to address them, and whether they were effective. Following this “data trail” helps you uncover the root causes of issues and is one of the things that conversational, iterative analytics does best.
Interpret your data
While AI for financial analysis is powerful, human reasoning is irreplaceable. You’ll still need to use your expertise to interpret AI findings and make strategic decisions. For instance, AI might identify a potential opportunity based on historical data, but your knowledge of market conditions, regulatory changes, and company strategy will help you assess whether it’s a good fit for your organization. Combining AI-driven insights with human judgment is the perfect recipe for well-rounded and informed decisions.
Discover the best AI solution for finance
From automating manual tasks and generating reports to helping with budgeting and forecasting, there are plenty of applications for artificial intelligence in finance. But if you really want to be on the cutting edge, conversational analytics is one of the most exciting developments. Why? It’s simple: speed, accuracy, and plain English.
DataChat transforms your data into clear, actionable insights for everyone on your team, regardless of their tech skills. Unlike other platforms, it automatically documents every step, so you can verify how the proverbial sausage was made. And its iterative capabilities mean you can keep digging until you hit gold.
With DataChat, you’re not just keeping up with the times—you’re ahead of them. Book a demo today and get ready to unleash interesting insights and drive your finance department to new heights.