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AI in finance refers to the application of intelligent technologies, such as machine learning (ML), deep learning (DL), and natural language processing (NLP), to improve financial operations, decision-making, and service delivery.
These systems process large volumes of data to detect patterns, predict trends, and streamline workflows. AI empowers finance teams to work faster and smarter, enabling informed decision-making, greater accuracy, and responsiveness in a dynamic economic environment.
In this article, we discuss:
What are the key benefits of artificial intelligence in finance?
What are the challenges surrounding AI in finance?
How are machine learning and deep learning used in finance?
What are some common use cases for AI in finance software?
What does the future of AI in finance look like?
AI delivers tangible business outcomes across finance functions. Leading benefits include:
According to IDC, 26% of CFOs say faster decision-making is a top priority for AI investment, while 24% prioritize improved compliance and risk controls. Yet, many AI initiatives fail due to a lack of clear focus on use cases or internal skill alignment.
While the upside is significant, successful AI adoption requires overcoming several structural and technical challenges:
A Unit4 global study found that 83% of finance professionals expect to upskill in AI within two years, with adoption strongly correlated to higher confidence in leadership and business performance.
To summarize briefly:
Machine Learning: Focuses on algorithms to learn from data.
Deep Learning: A more advanced form of ML using neural networks to handle complex tasks.
Machine learning (ML), a subset of AI, is widely used in finance to analyze datasets, predict market trends, and optimize investment strategies. Financial institutions leverage ML to identify patterns and make data-driven decisions in real time. Machine Learning and Deep Learning are core to today’s financial innovation.
Deep learning (DL) is a specialized subset of Machine Learning that uses artificial neural networks with multiple layers (hence "deep") to model and solve complex financial problems, analyze large datasets, and make predictions or decisions. Its ability to process vast amounts of structured and unstructured data makes it a powerful tool for the financial industry.
AI models evaluate credit scores, cash flow trends, and payment history to support real-time risk profiling. This reduces default rates and enables more informed lending decisions.
ML systems continuously monitor transactions, learning from historical behavior to instantly flag abnormal activity and reduce fraud exposure.
DL models process millions of data points to forecast asset performance, giving hedge funds and institutions an analytical edge in trade execution.
Virtual assistants powered by NLP automate client interactions, delivering balance updates, payment tracking, or loan explanations without human intervention.
AI-tailored offers based on user preferences, behaviors, and risk appetites improve conversion rates and long-term loyalty.
According to Dresner Advisory Services, over 50% of enterprise performance management (EPM) users report that predictive forecasting and automation in finance have the highest impact, particularly in budgeting and scenario planning.
AI is deeply embedded in Unit4’s financial software, enabling human-centric, automation-first design across FP&A, ERP, and HCM platforms. Here are some examples of artificial intelligence use within software modules:
AI-driven storytelling in Unit4 FP&A transforms raw numbers into business narratives, identifies deviations, and recommends next actions.
Smart AI assistants cut invoice cycle times by 30% and boost multi-client processing efficiency by 90%.
Unit4’s Payroll Navigator reduces manual tasks by 30%, cuts errors by 50%, and speeds onboarding by 40%.
Pattern recognition accelerates matching and reduces time spent on exceptions.
A UK public healthcare provider using Unit4 FP&A reduced monthly reporting time by 90%, shortened cost center forecasting from 2 hours to 30 minutes, and consolidated budgets across hundreds of teams, supporting real-time decisions for a population of over 6 million.
AI is a foundational capability for future-ready finance teams. What’s next:
The future of finance lies in becoming the storytellers of business performance… Yes, roles will evolve, but finance professionals will be critical to the successful adoption of AI.
The competitive finance function of the future is intelligent, agile, and people-first. AI isn’t about replacing teams—it’s about empowering them to deliver faster, more strategic, and more personalized outcomes.
Unit4’s AI-powered financial systems help organizations reduce risk, improve efficiency, and drive smarter decisions at scale. Whether you need to modernize payroll, automate reporting, or enhance planning, AI will be at the heart of transformation.
Talk to our experts to assess readiness and define your roadmap.