UPDATED BY
Jessica Powers | Jul 11, 2022
REVIEWED BY
Jye Sawtell-Rickson | Sep 21, 2022

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. While the market size was estimated to be $7.91 billion in 2020, it’s expected to reach $26.67 billion by 2026.

And as the market expands, it’s important to know some of the companies leading the way. Below we’ve rounded up 25 finance companies that are putting AI to use.

Companies Using AI in Finance

  • Kensho Technologies
  • AlphaSense
  • Enova
  • Scienaptic AI
  • Socure
  • Vectra AI

 

ai credit
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Examples of AI in Credit Decisions

Credit is king. One report found that 80 percent of consumers prefer spending with their debit or credit card over cash. 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 utilizing a variety of factors that more accurately assess traditionally underserved borrowers in the credit decision making process. 

These companies help the financial industry rethink the underwriting process.

 

Location: Chicago, Illinois

Enova created the Colossus platform, which utilizes AI and machine learning to provide advanced analytics and technology to both non-prime consumers, businesses and banks in order to facilitate responsible lending.

Colossus helps customers solve real-life problems, such as emergency costs for consumers 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 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.

Ocrolus strives to make it easier and more equitable to verify individual loan status while being less invasive.

 

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 enhance 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 Systems provides several financial-based services, including an underwriting platform that gives banks and credit institutions more transparency while cutting losses.

With over $200 million of credit losses saved by the underwriting platform, Scienaptic’s AI connects unstructured and structured data, transforms the data, learns from each interaction and offers contextual underwriting intelligence.

 

Location: Los Angeles, California

Zest AI is an AI-powered underwriting platform that helps companies assess borrowers with little to no credit information or history.

The platform utilizes 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 analyzes thousands of data points 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 good and bad applications. Because of its accuracy, Underwriter.ai says it can reduce defaults by 25 to 50 percent.

 

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.

 

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Examples of AI in Managing 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 more and more 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 AI is helping financial and banking institutions improve predictions and manage risk. 

 

Location: Cambridge, Massachusetts

Kensho, an S&P Global company,  provides machine intelligence and data analytics to leading financial institutions like J.P. Morgan, Bank of America and Morgan Stanley.

Kensho’s software offers analytical solutions using a combination of 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: 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 environment, social and governance. Simudyne’s secure simulation software uses agent-based modeling to provide a library of code for frequently used and specialized functions. Some of the company’s partners include Mastercard and Microsoft, according to its website. 

 

Location: Menlo Park, California

Ayasdi creates cloud-based and on-premise machine intelligence solutions for enterprises and organizations to solve complex challenges.

For companies in the fintech space, Ayasdi is deployed to understand and manage risk, anticipate the needs of customers and even aid in anti-money laundering processes.

Ayasdi is helping banks combat money laundering with its anti-money laundering detection solutions. The sheer volume of investigations has been a major strain on financial institutions.

 

ai trading
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Examples of 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.

 

Location: New York, New York

Canoe ensures that alternate investment data can be collected and extracted efficiently, utilizing APIs, AI and advanced data science capabilities to ingest, validata and deliver crucial information.The technology modernizes data workflows and is infinitely scalable to serve customers of all sizes.

 

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: Bellevue, 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 combines proprietary deep learning technology and high-speed data storage to provide short and long-term forecasting applications. Alpaca’s technology also identifies patterns in market price-changes and translates its findings into multi-market dashboards. 

The company partnered with financial news giant Bloomberg to provide users with its “AlpacaForecast AI Prediction Market.” The program predicts short-term forecasts in real-time for major markets.

 

ai in banking
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Examples of AI in Personalized Banking 

Traditional banking doesn’t always cut it with today’s consumers.

A study by Accenture of 47,000 banking customers found 54 percent want tools to help them monitor their budget and make real-time spending adjustments. Additionally, 41 percent are “very willing” to use computer-generated banking advice. 

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: 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.

Financial institutions like TD Bank, J.P. Morgan and Standard Bank use Kasisto, according to the company’s website.

 

Location: Orlando, Florida

Abe AI is a virtual financial assistant that integrates with Google Home, SMS, Facebook, Amazon 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 and conversational banking. 

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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Examples of AI in Cybersecurity & Fraud Detection

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.

 

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: 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: Cambridge, Massachusetts

Darktrace creates cybersecurity solutions for a variety of industries and financial institutions are no exception.

The company’s 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.

 

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Examples of AI in Blockchain

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. 

For example, 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 ensures that organizations have the tools they need to bring extraordinary 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 also 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 across eleven blockchains.

The platform provides users access to 11 different blockchains and 7 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 by finding new access points for consumer credit products like home equity lines of credit, home improvement loans and even home buy-lease offerings for retirement. The company also offers solutions for startups and private companies to raise capital, manage equity and trade shares. 

Established by former SoFi founder Mike Cagney, Figure has funded more than $4 billion for 60,000 since its establishment in 2018.

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