Pagaya vs Sift

Sift has a disclosed valuation of $1B, while Pagaya's valuation is not publicly available, making a direct size comparison difficult. Sift employs 400 people.

Pagaya has raised more in total funding at $600M, compared to Sift's $162M — a gap of $438M. Combined, the two companies have completed 5 known funding rounds.

Pagaya holds the higher Awaira Score at 70/100, compared to Sift's 61/100. The Awaira Score is a composite metric factoring in valuation, funding, stage, team size, and market presence — a 9-point gap that reflects meaningful differences in scale or traction.

Pagaya was founded by Gal Krubiner in 2016. Sift was founded by Jason Tan in 2011. Visit each company's profile on Awaira for a full founder biography.

Pagaya: Pagaya operates an AI financial underwriting network that processes consumer loan applications on behalf of lenders, using machine learning models that evaluate creditworthiness across a broader set of data signals than traditional credit bureau scores, enabling lenders to approve more applicants while maintaining or improving default rates. The Tel Aviv and New York company monetises by taking a network fee on loan volume processed through its AI underwriting system, funded by institutional investors who purchase the approved loan pools.\n\nThe company went public on NASDAQ via SPAC merger, having raised over $600 million in combined public and private funding from investors including Oak HC/FT and Viola Growth. Pagaya reports processing hundreds of billions of dollars in loan applications annually across personal loans, auto loans, and mortgage products, with network partners including SoFi, Ally Financial, and US Bank embedded in its origination technology. The business model operates as an AI network sitting between lenders who originate applications and institutional investors who fund approved loans.\n\nPageya competes in the AI credit underwriting market against ZestFinance, Upstart, and traditional credit bureau scoring models from Fair Isaac. Its network model, where multiple lenders access the same AI infrastructure and their collective data improves model performance over time, creates compounding advantages compared to single-lender AI implementations. The company has navigated regulatory scrutiny around AI lending decisions and disparate impact as financial regulators increase oversight of alternative data use in credit decisions. Sift: Sift is an AI-powered fraud prevention and digital trust platform founded in 2011, headquartered in the USA. The company specializes in identifying and preventing fraudulent transactions, account abuse, and payment fraud for digital commerce businesses. Its core platform uses machine learning algorithms to analyze user behavior patterns, transaction data, and device information in real-time, enabling merchants and financial services companies to distinguish between legitimate and fraudulent activity. Sift's primary products include fraud detection APIs, chargeback management tools, and account abuse prevention systems. The platform processes billions of transactions and events annually, building predictive models from this data to improve detection accuracy over time. The company serves e-commerce platforms, payment processors, financial institutions, and subscription services globally. With $162M in total funding and a $1.0B valuation, Sift operates at Series E stage, indicating substantial market traction and investor confidence. The company competes in the broader fraud prevention and fintech security sector alongside players like Stripe Radar, PayPal's fraud tools, and specialized fraud detection vendors. Its competitive positioning centers on machine learning sophistication, real-time processing capabilities, and integration flexibility for digital commerce ecosystems. Sift has maintained consistent growth since its inception, expanding its customer base and product capabilities to address evolving fraud threats in digital commerce environments. Sift combines behavioral analytics with machine learning to provide real-time fraud detection at scale for digital commerce platforms.

Sift was founded first in 2011, giving it 5 years of additional market experience. Pagaya was founded later in 2016. In AI, even a year or two of head start can translate into significantly more training data, customer relationships, and institutional knowledge.

Pagaya has approximately 500-1000 employees, while Sift has approximately 400. A larger team often signals higher revenue or venture backing, but in AI, smaller teams are increasingly capable of building at scale.

Yes, Pagaya and Sift are direct competitors — both operate in the AI Finance space and likely target overlapping customer segments. This comparison is especially relevant for buyers evaluating both platforms.