Predictive ML in Banking & Payments
19 companies using predictive ml technology in the banking & payments sector. Traditional ML algorithms for classification, regression, and scoring models
Directory
Companies by Funding
Klarna
AI-powered BNPL with agent features
Ramp
AI-powered corporate cards and spend management
Nubank
AI-driven digital bank for LatAm
Revolut
AI-powered financial super app
Monzo
AI fraud detection and budgeting
Brex
AI corporate card and financial stack for startups
Socure
Digital identity verification and fraud prevention
Quantexa
AI decision intelligence for risk
Feedzai
AI-native fraud and financial crime prevention platform for major banks
Persona
AI identity infrastructure platform
Alloy
Identity decisioning platform with 160+ data sources
Personetics
AI engagement platform for banks
Sardine
AI risk platform for fraud, credit, and compliance
ComplyAdvantage
AI-powered AML data and screening
Kyriba
AI-powered treasury management
Unit21
AI-powered fraud and AML platform
Trovata
AI cash management platform
Niural
EMMA AI agent runs payroll across 150 countries
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Frequently Asked Questions
How is Predictive ML used in banking & payments?
Traditional ML algorithms for classification, regression, and scoring models In the banking & payments sector, Predictive ML is applied by 19 companies tracked by AIFI Map, with $17.2B in combined funding. Leading companies include Klarna (AI-powered BNPL with agent features); Ramp (AI-powered corporate cards and spend management); Nubank (AI-driven digital bank for LatAm).
Which banking & payments companies use Predictive ML?
The AIFI directory tracks 19 banking & payments companies using Predictive ML, with a combined $17.2B in funding. Klarna, Ramp, Nubank, Revolut, Monzo, and 13 more. (Source: AIFI Map directory.)
What is the most funded Predictive ML banking & payments company?
Klarna is the most funded company using Predictive ML in banking & payments, with $4.2B raised. AI-powered BNPL with agent features Followed by Ramp ($2.3B).
How does Predictive ML compare to other AI technologies in banking & payments?
In the Banking & Payments segment, Predictive ML ranks #1 out of 6 AI technologies by adoption, with 19 companies and $17.2B in combined funding. The most widely adopted technologies in banking & payments are Predictive ML (19 companies, $17.2B funded); LLM / NLP (9 companies, $86.0B funded); Computer Vision (7 companies, $59.1B funded). While Predictive ML focuses on traditional ml algorithms for classification, regression, and scoring models, alternative approaches include LLM / NLP, which large language models for nlp, chat, document understanding, and text generation, and Computer Vision, which image and video processing, ocr, and document extraction.