Machine learning and artificial intelligence are often used interchangeably, but the former is actually an advanced subset of the latter. Just because something is artificially smart doesn’t necessarily mean it can be learned.
Machine learning technology can adapt to different situations and learn as you go. The financial industry takes advantage of these functions, implementing machine learning in all facets of finance.
Machine learning in finance
Machine learning has a major impact in finance, from offering alternative credit scoring methods to accelerating underwriting. The financial industry is rapidly deploying machine learning to automate laborious processes, provide better opportunities for loan seekers to get the loan they need, and more.
From fraud detection to credit determination, these 10 companies are using machine learning to change what’s possible in finance.
To affirm
Site: San Francisco, California
What he does: To affirm is a payment service that allows consumers to simply fund items and pay for them over time. Consumers accept the amount in advance so that they know exactly how much they are paying. Affirm is accepted by a wide variety of retailers and businesses, including Wayfair, Expedia, Peloton and Casper, making larger purchases more accessible and affordable.
Impact on industry: Affirm can identify more consumers who deserve credit than traditional rating systems through intelligent underwriting models. These models use machine learning to more accurately assess repayment capacity and the fair price of risk at the point of sale. This helps reduce fraud rates and defaults while allowing users to have greater access to credit.
Agent risk
Site: Los Angeles, California
What he does: Agent Risk provides an active portfolio management product dubbed “The Machine”, which uses data from the past ten years as well as Nobel Prize winning articles for decision making. The company’s product consists of machine learning algorithms that help generate returns on inactive assets while protecting portfolios from market volatility.
Impact on industry: The benefits of active portfolio management have traditionally been available through high-end asset managers, but AgentRisk makes it more accessible.
Datavisor
Site: Mountain View, California
What he does: Datavisor uses unsupervised machine learning to catalyze fraud detection. With unsupervised learning, no retraining is necessary for machines to detect new types of fraudulent activity. Datavisor’s technology combines graphical analysis with clustering techniques to detect patterns in unlabeled data across billions of accounts.
Impact on industry: Datavisor technology protects over three billion accounts worldwide with its technology.
Merit
Site: Menlo Park, California
What he does: MeritCredit cards help young adults build their credit history. With a focus on students, the card also offers no annual fees and rewards users for their specific purchases. Deserve uses machine learning tools instead of traditional credit sources to approve its cardholders.
Impact on industry: Last year, Deserve received $ 12 million in funding to expand operations.
Enova
Site: Chicago, Illinois
What he does: Enova develops and provides a variety of financial products and services for businesses and individuals. The company’s brand, Enova Decisions, is used in many industries, including finance. The service helps businesses gain more customers through machine learning models that provide personalized risk and credit analysis.
Impact on industry: Enova Decisions a helped companies like online lender Headway Capital to automate decisions, assess default risk, and provide customers with real-time pre-qualified loans and prices.
Feedzai
Site: San Mateo, California
What he does: Feedzai works with global financial companies, banks and retailers to provide machine learning solutions for online and in-person risk management. For risks such as fraud and money laundering, Feedzai assesses and detects suspicious patterns in transaction and event data.
Impact on industry: According to a Feedzai case study, the company’s technology has enabled one of the top 10 banks in the United States to improve its customer account opening process, resulting in more applicants and a decrease in fraud losses.
FinTech Studios
Site: New York, New York
What he does: Fintech Studios is a smart research and analysis platform for finding financial professionals among millions of financial and business resources. From blogs and news to big data research and analysis, the platform uses artificial intelligence and machine learning to identify the most relevant information in 32 languages.
Impact on industry: Fintech Studios’ variety of products allow financial professionals, from financial brokers and advisers to hedge funds and private equity firms, to quickly access the information they need.
cabbage
Site: Atlanta, Georgia
What he does: cabbage provides lines of credit to small businesses and has worked with over 150,000 businesses. Its simple application process for businesses (accessible online or via a mobile app) uses machine learning algorithms to determine whether or not a candidate is approved, reducing the risk of human error.
Impact on industry: Kabbage recently received $ 200 million in funding to expand its services to large enterprises and continue to develop its machine learning technology.
Pendo Systems
Site: Monclair, New Jersey
What he does: Pendo Systems provides a machine learning platform to transform unstructured documents into structured data usable for the banking, capital and insurance markets. The platform is used to extract data for cases such as loan granting, tax returns, residential mortgages, and business finance.
Impact on industry: Through its automation of manual processes, Pendo claims to have saved banking and capital customers over $ 90 million.
risk
Site: New York, New York
What he does: risk is a fraud solution for e-commerce businesses. The machine learning solution identifies bad orders and prevents chargebacks for merchants. The Fraud Detection solution ensures fewer misidentifications of fraudulent activity and continually learns new fraud methods, staying one step ahead of bad orders and helping businesses retain more customers.
Impact on industry: Riskified helped a shoe retailer Finish Line to reduce chargebacks 70%, saw more precise load drops and ultimately allowed the Finish Line team to focus on other operations and business needs.
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