The financial sector has always been at the forefront of innovation, and 2025 is no exception. This time, however, the changes are driven by implementing AI technologies.
Have you ever imagined that a tool would independently analyze financial data, assess risks, or even detect fraud in advance? That’s exactly what AI is doing. Financial companies are adopting more and more AI-powered tools to work faster, more accurately, and without human-made errors. It can automate tasks that just a few years ago required entire teams of analysts.
One of the biggest advantages of such tools is the ability to make decisions based on data. Analyzing trends, predicting market changes, and determining the best investment strategies are all possible thanks to modern AI algorithms. Instead of relying solely on human predictions, financial institutions can use AI-driven financial analytics to work with objective and more accurate information.
But what does this mean for those working in finance? It means new opportunities. AI technologies provide data-driven financial insights, streamline financial planning, improve customer experience, and automate risk management.
DATAFOREST prepared an overview of the best AI finance tools in 2025. We will delve into their main features, use cases, pros, cons, and pricing options. Some tools provide free plans, allowing you to test them and see if they are a good fit for your business. Also, as a tech vendor, we can provide GenAI consultations for businesses in the financial sector looking for custom AI solutions. You can book a call, and our consultant will reach out to you.
Why businesses need AI tools for finance
The financial sector has always been based on accuracy, speed, and data. Any mistake in calculations and any delay in making a decision can cost the company millions of dollars. That is why AI is becoming a necessity for those who want to remain competitive in 2025.
According to a recent survey, AI has a huge economic impact on the financial sector. For example, financial institutions that use AI to automate processes have reduced operational expenses by up to 47%. At the same time, automating routine tasks showed a 22% boost in productivity.
Another reason why financial companies implement AI is to automate routine processes. Banks, insurance companies, and investment funds process thousands of applications, payments, and requests from clients every day. The human factor in such processes is inevitable, and therefore, the possibility of errors. AI can streamline the process of risk assessments and the detection of suspicious transactions, and it can provide customer support in real time 24/7.
At the same time, financial fraud is becoming increasingly complex, and traditional security methods can no longer identify it quickly enough. This is where artificial intelligence comes in. It does not simply check transactions according to standard parameters but analyzes customers’ behavioral factors. If something seems suspicious, for example, a sudden transfer of a large amount from an unusual location or atypical behavior in a banking application, AI reacts immediately. This helps prevent financial fraud before it causes damage.
Also, personalized financial services is another important factor. The modern customer expects financial services to be adapted to his needs. AI helps companies create personalized offers, from customized loan rates to AI-powered investment strategies. This not only improves the customer experience but also increases brand loyalty.
Benefits of AI tools for finance
One of the latest Gartner surveys on this topic demonstrates that 58% of finance institutions already use AI while 21% are planning its implementation.
1. Make decisions based on data, not assumptions
Accuracy in financial forecasting has always been a challenge. Traditional methods work, but they don’t take into account the millions of variables that influence the market. AI changes the approach with financial data processing: it analyzes huge amounts of data in real time, finds hidden patterns, and builds forecasts that help companies make informed decisions.
For example, machine learning algorithms can predict the likelihood of loan defaults, changes in customer behavior, or even stock market volatility.
2. Optimize costs and increase productivity
AI helps to significantly reduce operational expenses by automating routine tasks such as document verification, loan application processing, or payment management.
Previously, these processes took days or even weeks, but now AI reduces them to a few minutes. This not only increases the speed of work but also allows employees to focus on strategic tasks, instead of manual tasks.
3. Intelligent fraud detection and cybersecurity in finance
Financial frauds now involve increasingly complex schemes. AI can analyze customer behavioral patterns and detect suspicious transactions before they become a threat. For example, if the system notices that a client suddenly makes unusual transfers, it can block the operation and request additional verification. This significantly reduces risks for both companies and their customers.
4. Improved customer service and personalization
AI assistants, chatbots and automated recommendation systems are changing the approach to customer service. You no longer need to wait for hours for an operator to respond–smart algorithms help resolve most issues in a few minutes. In addition, financial companies can offer personalized products tailored to the specific needs of customers. For example, the system can automatically select the best lending or investment conditions by analyzing the user’s financial history.
5. Revenue growth and competitive advantage
In 2025, the companies that use AI have a significant advantage. They can adapt faster to market change, accurately predict risks, and interact with customers better.
The best tools in the current year
GPT Excel
GPT Excel is an AI tool that automates, simplifies, and enhances work in spreadsheet applications like Microsoft Excel, Google Sheets, and Airtable. It lets users quickly generate formulas, SQL queries, and VBA scripts. As a result, it simplifies complex tasks, boosting productivity, automating repetitive processes, and providing deeper data insights.
Pros:
- formula generation for Excel, Google Sheets, and Airtable;
- AI chat and data insights;
- table template generation;
- SQL query generation.
Cons:
- adds-on don’t always work;
- some users experienced billing issues.
Pricing: free plan available; Pro plan at $6.99/month.
Client Ratings: 4.6/5 on G2 reviews.
Alteryx
Alteryx is an AI solution to simplify, automate and accelerate data analytics. It’s ideal for financial companies looking for data automation and fast, reliable insights. With its drag-and-drop interface and AI-guided data automation, it enables anyone to analyze, discover, and share insights needed for informed decision-making.
Pros:
- provides answers to data analytics questions in minutes, automatically;
- no tech skills needed;
- drag-and-drop interface;
- reduces manual work and errors;
- boosts data analytics productivity.
Cons:
- no pricing details on the website.
Pricing: 30-day free trial but no further pricing details;
Client Ratings: 4.6/5 on Gartner.
Finbox
Finbox is an AI-driven tool to track accurate, up-to-date information on publicly traded companies around the world. They claim to have financial data for nearly every exchange in the world since they cover over 100,000 stocks on 130+ exchanges around the world. Financial specialists and investors can use this tool to navigate every step of the investing process and find promising companies for investments.
Pros:
- cover over 100,000 stocks on 130+ exchanges around the world;
- stock screener that supports 1,000+ metrics;
- allows users to track the stocks and customize views with the metrics they need.
Cons:
- risk analytics can be improved;
Pricing: free trial available for each plan; Starter plan at $19/month.
Client Ratings: 4.0/5 on G2 reviews.
Equifax
Equifax offers various products and services in the financial sector. For business, they can help make better credit decisions and expand access to credit with advanced data and analytics while delivering a better customer experience and smarter revenue. Their offering includes credit risk assessment, verification, identity protection and fraud prevention, workforce management and data-driven marketing.
Pros:
- provides expert analysis of key economic indicators to adapt to shifting market dynamics.
Cons:
- some users experienced issues with customer support.
Pricing: no details on pricing.
Client Ratings: 3.4/5 on Trustpilot.
Betterment
Betterment provides financial solutions for individuals, businesses, and advisors. They make it easy and affordable for small and mid-market businesses to provide a scalable retirement plan for their employees. They have 17 billion retirement assets under management. Their platform provides everything from expert-built, curated portfolios to customizable investment options, giving employees the flexibility to save on their terms.
Pros:
- allows businesses to design a plan that fits their needs, from auto-escalation and auto-enrollment to eligibility requirements, vesting schedule, and profit sharing;
- offers optional financial wellness benefits;
- provides tax savings calculator to estimate plan costs;
- claims to provide a possibility to earn up to $15,000 in tax credits over the first three years of the plan;
- 350+ payroll integrations.
Cons:
- pricey financial advisor consultations.
Pricing: $100 monthly base fee, billed each calendar year annually ($1,200) +$5 monthly record-keeping fee per participant +0.25% annual advisory fee.
Client Ratings: 4.8/5 by Forbes.
Wealthfront
Wealthfront is a robo-advisor to help investors earn more on their short-term savings with a high APY delivered through Wealthfront’s partner banks. It offers access to expert-built portfolios and strategies for investments without sneaky requirements or account fees. With AI and automation tools, it allows users to limit risks, minimize taxes, and maximize returns.
Pros:
- allows users to invest with expert-built portfolios and strategies;
- no account fees;
- free 24/7 instant withdrawals;
- no minimum or maximum balance to earn 4.00%* APY;
Cons:
- investment minimum is $500.
Pricing: annual advisory fee is 0.25%.
Client Ratings: 5.0 by NerdWallet.
Numer AI
Numer AI is a unique hedge fund that uses the collective intelligence of data scientists to make investment decisions. The platform works as a decentralized prediction market: users can upload their machine learning models that analyze financial data and make predictions. The best models influence the fund’s investment decisions, and their authors receive rewards in the cryptocurrency NMR.
Pros:
- allows users to predict the stock market with machine learning and AI;
- combines artificial intelligence, data anonymity, and collective knowledge to create more accurate financial strategies.
Cons:
- requires tech skills;
- no pricing details.
Pricing: some models are free but no pricing details on the website.
Client Ratings: no info.
Sift
Sift is an AI-powered fraud detection and prevention platform for the financial sector. Businesses use this platform to secure the customer journey and reduce risks. Sift also offers payment protection, account defense, dispute management, and content integrity. Using machine learning and big data in finance, it analyzes transactions, user behavior, and risk factors to predict potential fraud before it happens. Financial services, e-commerce, fintech, and payment services companies use it to automate security processes, reduce financial losses, and improve customer experience.
Pros:
- fraud prevention in real time;
- user behavior analysis;
- seamless integration with existing financial platforms and CRM systems;
- intuitive interface for risk analytics and monitoring suspicious activities.
Cons:
- false positives may occur;
- dependence on the quality of input data.
Pricing: free demo but no info on pricing or free trial.
Client Ratings: 4.7/5 on G2 reviews.
Upstart
Upstart is a fintech platform that uses AI to assess the credit rate of borrowers. It helps banks make more accurate decisions on loans by considering not only traditional credit scores but also additional factors such as education, professional experience, and income level. Through intelligent analysis, Upstart provides customers with faster access to loans, and lenders with the opportunity to reduce the risk of defaults.
Pros:
- AI credit rate analysis that considers 1,500 factors to assess borrowers;
- automated decision-making;
- 70% of loans are approved without human intervention;
- fast application review in less than 24 hours;
- integrations with banks.
Cons:
- high rates.
Pricing: platform is free for personal use but for lenders fees apply.
Client Ratings: 4.9/5.
Zest AI
Zest is an AI-powered platform for banks and credit unions to help them make smarter, more inclusive, and more efficient decisions. It can be seamlessly integrated into the lending process. Zest also offers AI-automated underwriting to make credit decisions faster, fraud detection feature, and personalized reporting.
Pros:
- automates 80% of decisions;
- leads to 20% reduction in risk;
- can be integrated into the lending process.
Cons:
- no pricing info.
Pricing: no info.
Client Ratings: 4.8/5.
AI tools comparison table
Final Thoughts: Is it a good time to bring AI in?
The answer is yes. 2025 seems to be a game-changer for the financial industry.
AI can automate routine tasks, predict market trends, and prevent financial fraud. But does this mean that financial analytics or risk management will soon be completely controlled by AI algorithms? No. Despite all the benefits, even the best AI solutions require human judgment, because the market is not just about numbers, but also strategic thinking, intuition, and experience.
The main question is no longer whether to implement AI, but how to do it right. Choosing the right tool depends on the business model and specific tasks. Some need solutions to automate reporting, while others are looking for tools for deep market analysis or expanded credit scoring. Companies that are already implementing AI are gaining a competitive advantage and strengthening their market position.
In short: AI in finance is not the future, it’s already a reality. And while full automation is yet to happen, businesses that adapt to new technologies today will be in a winning position tomorrow. If you haven’t yet integrated AI into your finance strategy, it might be time to think about it. By partnering with tech vendors like DATAFOREST, you can define use cases for your teams and start integrating AI without disrupting workflows. Our team provides Gen AI consulting services to make sure you choose the right tool for your business. If you’re interested in a consultation, please, fill out the form, and we’ll contact you soon.
FAQ
How do AI tools help in risk analysis for financial institutions?
AI tools analyze large amounts of data in real time, uncover hidden patterns, and predict potential risks to make informed decisions.
How can AI tools improve the accuracy of customer credit assessment rates?
AI takes into account not only credit history, but also other factors like education, experience, and income level to define a more accurate credit rate.
How do AI tools impact automated reporting and financial analysis processes?
Artificial intelligence accelerates data processing, automatically generates reports, and allows financial professionals to focus on strategic tasks.
How are AI tools used to monitor and forecast currency fluctuations?
They analyze market trends, economic state, and investor behavior to predict exchange rate changes with high accuracy.
How do AI tools help in improving the accuracy of loan interest forecasts?
These tools analyze market dynamics, customer behavior, and macroeconomic indicators to build accurate financial models.
How do AI tools help optimize lending processes and improve decision-making quality?
AI automates the analysis of questionnaires, speeds up decision-making, and reduces errors when considering applications.
What is the role of AI tools in improving the security of financial transactions?
AI detects suspicious activity in real time, analyzes behavioral patterns, and blocks suspicious transactions to prevent fraud.
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