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Pagaya, which uses AI and big-data analytics to manage institutional money, raises $102M Series D, bringing its total raised to $221.9M

Duncan Riley / SiliconANGLE :

SiliconANGLE Duncan Riley

Context & Ripple Effects

Pagaya's Series D lands just over a year after its $25M Series C led by Oak HC/FT, and the $102M round more than quadruples what it raised in that prior round, taking total funding to $221.9M. The company applies AI and big-data analytics to managing institutional money, with asset-backed securities as its core use case.

The round positions Pagaya as one of the larger checks in a cluster of AI-for-finance fundraises — from fraud-detection firm Seon's $80M Series C to cloud financial-planning vendor Vena Solutions' $115M Series D — and sets the stage for the SPAC merger at a ~$9B valuation that followed about fifteen months later.

First-order effects

  • Pagaya gains roughly $102M to scale its AI-driven management of asset-backed securities and institutional capital, on top of the $25M Series C it raised from Oak HC/FT the year before.
  • Institutional investors in the round are effectively underwriting an AI-native asset manager rather than a software vendor, deepening the capital behind algorithmic ABS management.

Second-order effects

  • Rivals applying machine learning to credit and fraud workflows — Seon among them — face a funding benchmark: Pagaya's round size raises the capital bar for AI firms selling into banks and lenders.
  • The scale-up strengthens Pagaya's pitch to banks seeking more efficient lending transactions, pressuring incumbents in ABS management to justify human-led portfolio management.

Third-order effects

  • The trajectory from a $25M Series C to a $102M Series D to a ~$9B SPAC merger sketches the playbook AI-finance firms followed in this cycle: raise fast on data advantages, then bypass the traditional IPO window via SPACs.
  • If AI-driven asset management keeps attracting institutional capital, the structural shift is toward allocation decisions in credit markets being made by models whose funders, rather than the funds' managers, capture the early value.

The trend: AI-native financial firms are compressing the path from Series C to public markets, with large late-stage rounds and SPAC mergers replacing the conventional IPO ladder.