Rose Velazquez | Feb 06, 2024

If there’s one technology paying dividends for the financial sector, it’s artificial intelligence. AI has given the world of banking and finance new ways to meet the customer demands of smarter, safer and more convenient ways to access, spend, save and invest money.

AI in Finance

Artificial intelligence (AI) in finance transforms the way people interact with money. AI helps the financial industry streamline and optimize processes ranging from credit decisions to quantitative trading and financial risk management.

The market is growing too. The market value of AI in finance was estimated to be $9.45 billion in 2021 and is expected to grow 16.5 percent by 2030. 

And as the market expands, it’s important to know some of the key players. 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.

Companies Using AI in Finance

  • Kensho Technologies
  • AlphaSense
  • Enova
  • Scienaptic AI
  • Socure
  • Vectra AI
ai credit
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AI Companies in Financial Credit Decisions

Credit is king. One report found that 27 percent of all payments made in 2020 were done with credit cards. But easier payment isn’t the only reason credit is important to consumers. 

Having good credit makes it easier to access favorable financing options, land jobs and rent apartments. So many of life’s necessities hinge on credit history, which makes the approval process for loans and cards important.

Artificial intelligence solutions help banks and credit lenders make smarter underwriting decisions by using various factors that more accurately assess traditionally underserved borrowers in the credit decision making process. 

These companies help the financial industry rethink the underwriting process.

Read Next: The Future of AI: How Artificial Intelligence Will Change the World


Location: Chicago, Illinois

Enova uses AI and machine learning in its lending platform to provide advanced financial analytics and credit assessment. The company aims to serve non-prime consumers and small businesses and help solve real-life problems, like emergency costs and bank loans for small businesses, without putting either the lender or recipient in an unmanageable situation.


Location: New York, New York

Ocrolus offers document processing software that combines machine learning with human verification. The software allows business, organizations and individuals to increase speed and accuracy when analyzing financial documents. Ocrolus’ software analyzes bank statements, pay stubs, tax documents, mortgage forms, invoices and more to determine loan eligibility, with areas of focus including mortgage lending, business lending, consumer lending, credit scoring and KYC.


Location: Boston, Massachusetts

DataRobot provides machine learning software for data scientists, business analysts, software engineers, executives and IT professionals. DataRobot helps financial institutions and businesses quickly build accurate predictive models that inform decision making around issues like fraudulent credit card transactions, digital wealth management, direct marketing, blockchain, lending and more. Alternative lending firms use DataRobot’s software to make more accurate underwriting decisions by predicting which customers have a higher likelihood of default.


Location: New York, New York

Scienaptic AI provides several financial-based services, including a credit underwriting platform that gives banks and credit institutions more transparency while cutting losses. Its underwriting platform uses non-tradeline data, adaptive AI models and records that are refreshed every three months to create predictive intelligence for credit decisions.


Location: Burbank, California

Zest AI is an AI-powered underwriting platform that helps companies assess borrowers with little to no credit information or history. The platform uses thousands of data points and provides transparency that helps lenders better assess populations traditionally considered “at risk.” The company reported that auto lenders using machine-learning underwriting cut losses by 23 percent annually, more accurately predicted risk and reduced losses by more than 25 percent.


Location: Boston, Massachusetts

Underwrite.ai uses AI models to analyze thousands of financial attributes from credit bureau sources to assess credit risk for consumer and small business loan applicants. The platform acquires portfolio data and applies machine learning to find patterns and determine the outcome of applications.


Location: New York, New York 

Socure created ID+ Platform, an identity verification system that uses machine learning and AI to analyze an applicant’s online, offline and social data, which helps clients meet strict KYC conditions. 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. Socure is used by institutions like Capital One, Chime and Wells Fargo, according to its website.


ai finance
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AI Companies Managing Financial Risk

Time is money in the finance world, but risk can be deadly if not given the proper attention. Accurate forecasts are crucial to the speed and protection of many businesses.  

Financial markets are turning to machine learning to create more exacting, nimble models. These predictions help financial experts utilize existing data to pinpoint trends, identify risks, conserve manpower and ensure better information for future planning.

The following companies are just a few examples of how artificial intelligence in finance is helping banking institutions improve predictions and manage risk. 


Location: Ames, Iowa

Workiva offers a cloud platform designed to simplify workflows for managing and reporting on data across finance, risk and ESG teams. It’s equipped with generative AI to enhance productivity by aiding users in drafting documents, revising content and conducting research. The company has more than a dozen offices around the globe serving customers in industries like banking, insurance and higher education.


Location: Cambridge, Massachusetts

Kensho, an S&P Global company, created machine learning training and data analytics software that can assess thousands of datasets and documents. Its data training software uses a combination of machine learning, cloud computing and natural language processing, and it can provide easily understandable answers to complex financial questions, as well as extract insights from tables and documents quickly. Traders with access to Kensho’s AI-powered database in the days following Brexit used the information to quickly predict an extended drop in the British pound, Forbes reported.


Location: Walnut Creek, California

Derivative Path’s platform helps financial organizations control their derivative portfolios. The company’s cloud-based platform, Derivative Edge, features automated tasks and processes, customizable workflows and sales opportunity management. There are also specific features based on portfolio specifics — for example, organizations using the platform for loan management can expect lender reporting, lender approvals and configurable dashboards.


Location: Fully Remote 

Simudyne’s platform allows financial institutions to run stress test analyses and test the waters for market contagion on large scales. The company offers simulation solutions for risk management as well as environmental, social and governance settings. Simudyne’s secure simulation software uses agent-based modeling to provide a library of code for frequently used and specialized functions.


Location: Menlo Park, California

Ayasdi creates cloud-based machine intelligence solutions for fintech businesses and organizations to understand and manage risk, anticipate the needs of customers and even aid in anti-money laundering processes. Its Sensa AML and fraud detection software runs continuous integration and deployment and analyzes its own as well as third-party data to identify and weed out false positives and detect new fraud activity.


Location: McLean, Virginia

Range is a membership-based fintech company that markets its money management services specifically to millennials. Part old school and part new, it offers everything you’d expect from a traditional wealth management service: investment, retirement, education and estate planning delivered via consults with certified financial planners. These services are bundled with DIY wealth management tools powered by machine learning.


ai trading
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Companies Using AI in Quantitative Trading

Quantitative trading is the process of using large data sets to identify patterns that can be used to make strategic trades. Artificial intelligence is especially useful in this type of trading. AI-powered computers can analyze large, complex data sets faster and more efficiently than humans. The resulting algorithmic trading processes automate trades and save valuable time.

The following companies are just a few examples of how AI-infused technology is helping financial institutions make better trades.

More on AI Trading: How AI Trading Technology Works for Stock Investors


Location: New York, New York

Trumid is a fintech and fixed income trading platform. The company applies advanced analytics and AI technologies to develop products and data-driven tools that can optimize the experience of credit trading. Trumid also uses its proprietary Fair Value Model Price, FVMP, to deliver real-time pricing intelligence on over 20,000 USD-denominated corporate bonds. This AI-powered prediction engine is designed to quickly analyze and adapt to changing market conditions and help deliver data-driven trading decisions.


Location: Chicago, Illinois

Powered by their AI and machine learning algorithms, Tegus is an investment research platform. The company helps clients research investment opportunities more efficiently by providing AI-generated summaries of expert interviews to help them make informed investment decisions. 


Location: New York, New York

Canoe ensures that alternate investments data, like documents on venture capital, art and antiques, hedge funds and commodities, can be collected and extracted efficiently. The company’s platform uses natural language processing, machine learning and meta-data analysis to verify and categorize a customer’s alternate investment documentation.


Location: New York, New York

Entera is an AI-powered investment platform for real estate investors. The platform lets investors buy, sell and operate single-family homes through its SaaS and expert services. Investors can access homes from on and off-market sources. Additionally, Entera can discover market trends, match properties with an investor’s home and complete transactions.


Location: New York, New York 

An AI-powered search engine for the finance industry, AlphaSense serves clients like banks, investment firms and Fortune 500 companies. The platform utilizes natural language processing to analyze keyword searches within filings, transcripts, research and news to discover changes and trends in financial markets.

AlphaSense is valuable to a variety of financial professionals, organizations and companies — and is especially helpful for brokers. The search engine provides brokers and traders with access to SEC and global filings, earning call transcripts, press releases and information on both private and public companies.


Location: Seattle, Washington

Kavout uses machine learning and quantitative analysis to process huge sets of unstructured data and identify real-time patterns in financial markets. One of Kavout’s solutions is the K Score, an AI-powered stock ranker. The K Score analyzes massive amounts of data, such as SEC filings and price patterns, then condenses the information into a numerical rank for stocks. The higher the K Score, the more likely the stock will outperform the market.   


Location: San Mateo, California 

Alpaca uses proprietary deep learning technology and high-speed data storage to support its yield farming platform. (Yield farming is when cryptocurrency investors pool their funds to carry out smart contracts that gain interest.) Alpaca is compatible with dozens of cryptocurrencies and allows users to lend assets to other investors in exchange for lending fees and protocol rewards.


ai in banking
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Companies Using AI in Personalized Banking 

Traditional banking doesn’t always cut it with today’s consumers. A 2021 survey from J.P. Morgan Chase found that 89 percent of respondents use mobile apps for banking. Additionally, 41 percent said they wanted more personalized banking experiences and information. 

AI assistants, such as chatbots, use AI to generate personalized financial advice and natural language processing to provide instant, self-help customer service. 

Here are a few examples of companies using AI to learn from customers and create a better banking experience.


Location: San Francisco, California

SoFi makes online banking services available to consumers and small businesses. Its offerings include checking and savings accounts, small business loans, student loan refinancing and credit score insights. The company applies AI in multiple ways. For example, SoFi members looking for help can take advantage of 24/7 support from the company’s intelligent virtual assistant.


Location: New York, New York

Kasisto is the creator of KAI, a conversational AI platform used to improve customer experiences in the finance industry. KAI helps banks reduce call center volume by providing customers with self-service options and solutions. Additionally, the AI-powered chatbots also give users calculated recommendations and help with other daily financial decisions.


Location: Orlando, Florida

Abe AI is a virtual financial assistant that integrates with Google Home, SMS, Facebook, Amazon’s Alexa, web and mobile to provide customers with more convenient banking. The assistant provides services ranging from simple knowledge and support requests to personal financial management to spending overviews and budgeting. In 2016 Abe released its smart financial chatbot for Slack. The app helps users with budgeting, savings goals and expense tracking.


Location: San Francisco, California

Trim is a money-saving assistant that connects to user accounts and analyzes spending. The smart app can cancel money-wasting subscriptions, find better options for services like insurance, and even negotiate bills. Trim has saved more than $20 million for its users, according to a 2021 Finance Buzz article.


ai cybersecurity fraud detection
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Companies Using AI in Cybersecurity and Fraud Detection for Banking

Every day, huge quantities of digital transactions take place as users move money, pay bills, deposit checks and trade stocks online. The need to ramp up cybersecurity and fraud detection efforts is now a necessity for any bank or financial institution, and AI plays a key role in improving the security of online finance.

Here are a few examples of companies providing AI-based cybersecurity solutions for major financial institutions.

More on AI CybersecurityAI Cybersecurity: 24 Companies to Know


Location: San Jose, California

Vectra offers an AI-powered cyber-threat detection platform, which automates threat detection, reveals hidden attackers specifically targeting financial institutions, accelerates investigations after incidents and even identifies compromised information. 

A Vectra case study provides an overview of its work to help a prominent healthcare group prevent security attacks. Vectra’s platform identified behavior resembling an attacker probing the footprint for weaknesses and disabled the attack.


Location: Palo Alto, California

Jumio’s KYX platform helps businesses establish trust with online customers. The platform validates customer identity with facial recognition, screens customers to ensure they are compliant with financial regulations and continuously assesses risk. Additionally, the platform analyzes the identity of existing customers through biometric authentication and monitoring transactions. Jumio is commonly used in education, healthcare, retail and gaming industries.


Location: Mountain View, California

Utilized by top banks in the United States, f5 provides security solutions that help financial services mitigate a variety of issues. The company offers solutions for safeguarding data, digital transformation, GRC and fraud management as well as open banking. 

An f5 case study provides an overview of how one bank used its solutions to enhance security and resilience, while mitigating key cybersecurity threats. The company’s applications also helped increase automation, accelerate private clouds and secure critical data at scale while lowering TCO and futureproofing its application infrastructure.


Location: San Francisco, California

Darktrace’s AI, machine learning platform analyzes network data and creates probability-based calculations, detecting suspicious activity before it can cause damage for some of the world’s largest financial firms.

Bank One implemented Darktace’s Antigena Email solution to stop impersonation and malware attacks, according to a case study. The bank saw a rapid decrease in email attacks and has since used additional Darktrace solutions across its business.


Location: Jacksonville, Florida

FIS provides a host of banking and financial solutions. One way it uses AI is through a compliance hub that uses C3 AI to help capital markets firms fight financial crime. Announced in 2021, the machine learning-based platform aggregates and analyzes client data across disparate systems to enhance AML and KYC processes. FIS also hosts FIS Credit Intelligence, a credit analysis solution that uses C3 AI and machine learning technology to capture and digitize financials as well as delivers near-real-time compliance data and deal-specific characteristics.


ai finance blockchain
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Companies Using AI in Blockchain Banking

AI and blockchain are both used across nearly all industries — but they work especially well together. AI’s ability to rapidly and comprehensively read and correlate data combined with blockchain’s digital recording capabilities allows for more transparency and enhanced security in finance. AI models executed on a blockchain can be used to execute payments or stock trades, resolve disputes or organize large datasets.

Here are a few examples of companies using AI and blockchain to raise capital, manage crypto and more. 


Location: New York, New York

TQ Tezos leverages blockchain technology to create new tools on Tezos blockchain, working with global partners to launch organizations and software designed for public use. TQ Tezos aims to ensure that organizations have the tools they need to bring ideas to life across industries like fintech, healthcare and more.


Location: Chicago, Illinois

Wealthblock.AI is a SaaS platform that streamlines the process of finding investors. It helps businesses raise capital and handle automated marketing and messaging and uses blockchain to check investor referral and suitability. Additionally, Wealthblock’s AI automates content and keeps investors continuously engaged throughout the process.


Location: Denver, Colorado 

Shapeshift is a decentralized digital crypto wallet and marketplace that supports more than 750 cryptocurrencies. The platform provides users access to nine different blockchains and eight different wallet types. ShapeShift has also introduced the FOX Token, a new cryptocurrency that features several variable rewards for users.


Location: San Francisco, California

Figure uses blockchain and AI to streamline the home loan process. Its platform finds new access points for consumer credit products like home equity lines of credit, home improvement loans and even home buy-lease offerings for retirement. Figure Marketplace uses blockchain to host a platform for investors, startups and private companies to raise capital, manage equity and trade shares.

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