Gradient AI specializes in AI-powered underwriting and claims management solutions for the insurance industry. Socure is used by institutions like Capital One, Chime and Wells Fargo, according to its website. The system runs predictive data science on information such as email addresses, phone numbers, IP addresses and proxies to investigate whether an applicant’s information is being used legitimately. The software allows business, organizations and individuals to increase speed and accuracy when analyzing financial documents.

Kensho Technologies

Companies can also take it a step further with AI-driven customer segmentation for more-targeted marketing campaigns and promotions. AI can help deliver personalization by analyzing customer data, preferences, and behavior to provide the right product recommendations, content suggestions, and offers. And a 2024 NVIDIA survey of 400 global financial services professionals found that “created operational efficiencies” was the AI benefit cited most often by those surveyed at 43%. GenAI can be used to produce narrative reports, providing context into the numbers by combining financial statements and data with an explanation of each. GenAI can fill out the needed forms with data provided by the finance team for the staff to review and confirm. AI can then use the data to help generate financial statements, such as income statements, balance sheets, and cash flow statements, transforming the data into reports that highlight key performance indicators (KPIs), trends, and observations.

  • Portfolios aren’t static; they evolve in response to changing risk levels, market volatility, and shifting investor goals.
  • A particularly valuable technology in regulatory compliance is natural language processing (NLP).
  • Finance is quickly becoming one of its most impactful frontiers — from catching fraud in real time to predicting market shifts before they happen, AI is more than just a buzzword.
  • While traditional financial forecasts must be manually adjusted when circumstances change, AI-driven forecasts can recalibrate based on new data, helping keep forecasts and plans relevant and accurate.
  • Giving finance staff increased understanding of AI will also be critical in ensuring the proper security, controls, and appropriate use of the technology.

Are AI finance tools safe to use?

Financial companies use them to manage risk better, invest smarter, and work more efficiently. Advanced algorithms help financial entities interpret and extract information from images, minimizing errors. This improves processes such as document verification and fraud detection. It automates the analysis of images like checks, IDs, and financial documents.

  • Speech recognition enables users to interact hands-free with banking systems, enhancing security and convenience.
  • If a tool requires weeks of training and advanced learning, it will only affect your team’s performance and productivity.
  • Scienaptic AI provides several financial-based services, including a credit underwriting platform that gives banks and credit institutions more transparency while cutting losses.
  • And decisions will be made in real time—not after market changes have passed the business by.

Trullion’s built-in audit function helps accounting teams with financial documents and transactions, reducing the chances of errors. It enhances collaboration between AP teams and other departments, reducing processing time and improving accuracy. Stampli is an AI-powered accounts payable (AP) automation platform that streamlines invoice management and approvals. The user-friendly platform further streamlines client collaboration and data collection. Designed for small businesses and accounting firms, it simplifies accounting tasks, reduces errors, and saves time, allowing teams to focus on growing their business.

What is artificial intelligence (AI) in finance?

The real risks aren’t the machines; it’s bad data, biased models, and blind trust in automation that can derail even the best tools. Here’s how AI tools are changing the way finance teams work- It takes over the repetitive, time-consuming work, freeing teams to focus on strategy, risk management, and growth. It compiles, validates, and logs every entry automatically, top 5 legal accounting software for modern law firms giving auditors clarity and finance teams back their time. AI tools are raising the bar for what finance teams can do. Its AI capabilities enhance financial processes by automating routine tasks, providing predictive analytics, and offering real-time visibility into financial performance.

How WebFX helps financial institutions harness AI

In the future, AI-powered platforms might expand to include alternative data sources—such as mobile phone usage patterns or agricultural yields—to build financial profiles for unbanked populations. AI is already used to expand access to financial services in underserved markets. Growth in distributed AI architectures and edge computing might allow fraud detection systems to process data closer to its source, reducing latency and improving response times.

Workiva connects data within systems, streamlines reporting processes, and provides real-time collaboration and audit-ready outputs, all built for finance teams. It helps finance teams reduce manual effort, eliminate errors, and get real-time insights into cash flow and financial management. The right AI tools empower your finance and accounting teams with real-time insights, accurate forecasting capabilities, and access to data analytics to help make smarter financial decisions. This technology fosters innovation in financial services by integrating visual data into decision-making processes, enhancing risk management and operational insights. Kensho is an AI analytics and data visualization platform that provides real-time insights into financial markets and economic trends.

Efficiency

Giving finance staff increased understanding of AI will also be critical in ensuring the proper security, controls, and appropriate use of the technology. Second, train staff so they have the skills to effectively interact with AI tools, building analytical capabilities that capitalize on the technology. What can companies do now to prepare for increasing AI use over time?

Companies Using AI in Finance

These systems can provide actionable insights for both individual investors and institutional asset managers. AI is transforming insurance operations by automating underwriting and claims workflows by using tools like natural language processing and image recognition to analyze documents, photos and unstructured data. Natural language processing (NLP) enables these conversational AI systems to understand and respond to customer needs effectively.

Image recognition also enhances customer experience by enabling faster and more secure document handling, ensuring compliance with regulatory standards. Machine learning algorithms streamline document workflows, reducing manual errors and processing times for greater efficiency. This technology swiftly extracts and analyzes data from forms, contracts, and financial statements. This capability is crucial in expanding market reach, boosting global partnerships, and driving innovation within the financial industry. AI-powered translation capabilities are transforming finance by breaking language barriers and facilitating seamless communication across global markets.

This ensures smooth data flow and eliminates the need for manual data entry. Yes, Osfin.ai offers seamless finance definition integration with over 170 data sources, including ERPs, accounting software, banks, and payment processors. Osfin.ai is an AI-powered fin ops automation platform designed to streamline reconciliation and payouts. AI offers a way out, not by replacing finance professionals, but by supporting them.

They analyze user goals, risk tolerance, and market trends to build and manage portfolios in real-time. The gains of AI in finance promise heightened efficiency for today’s financial institutions and are helping to fuel digital finance transformation across the sector. The company’s platform uses natural language processing, machine learning and meta-data analysis to verify and categorize a customer’s alternate investment documentation.

Zest AI is an AI-powered underwriting platform that helps companies assess borrowers with little to no credit information or history. Let’s take a look at the areas where artificial intelligence in finance is gaining momentum and highlight the companies that are leading the way. The market value of AI in finance was estimated to be worth over $38 billion in 2024 and is expected to grow over 30 percent by 2030.

SoFi makes online banking services available to consumers and small businesses. Here are a few examples of companies using AI to learn from customers and create a better banking experience. MarketAxess develops automated and algorithmic trading solutions, enabling greater transparency, efficiency and competition across the fixed income marketplace. Additionally, Entera can discover market trends, match properties with an investor’s home and complete transactions. Canoe ensures that alternate investments data, like documents on venture capital, art and antiques, hedge funds and commodities, can be collected and extracted efficiently.

Document processing

But CFOs who begin now—selectively, strategically, and with governance in place—will redefine what it means to run a finance function in the AI-first era. AI is already rapidly reshaping how finance works. For example, a telecom provider could spot customer churn trends early enough to adjust pricing or retention programs before the quarter ends. Equip leaders with AI-driven dashboards that highlight emerging risks and opportunities. With prescriptive models updating automatically, finance variable and fixed cost in accounting can refresh scenarios as soon as conditions change. A global manufacturer, for instance, could view financial performance as it happens, enabling cost and investment decisions in days, not weeks.

These static interactions were limited, as they were unable to gauge human sentiments in real-time. These examples highlight customer-facing AI tools, such as mobile banking apps or 24/7 available AI agents, the section’s first example. This next category is about how AI supports enhanced customer experiences (CX) and interactions in finance.

What are the primary risks or challenges of using AI tools in finance?

Analyzing past data and forecasting trends helps allocate resources wisely and avoid unnecessary spending. AI’s powerful automation is transforming efficiency and costs in finance. By integrating AI solutions, financial companies streamline operations and build trust with regulators and clients. These AI tools also act as watchdogs, identifying irregularities and guaranteeing accurate reporting.