Grab Finance automates eligibility and risk checks across six markets using in‑app transaction signals and localized compliance workflows

Many individuals and small businesses across South-east Asia remain outside formal credit systems because they lack traditional credit records. To address this market, the financial services arm of a regional superapp built alternative credit assessment models using behavioral data generated within its own ecosystem.

On 5 February 2026, Grab Finance announced its digital transformation initiative to cope with the different  financial‑regulation and data‑protection regimes that make it difficult to standardize credit decisioning while still complying with local rules.

The key is to automate eligibility checks, pre‑approved offers, and risk assessment for millions of drivers, merchants, and passengers without relying solely on bureau data. Additionally, the fragmented regulatory landscape meant credit, banking and data protection laws differ significantly across Southeast Asian countries, requiring localized compliance and explainability without losing regional consistency.

To address these challenges, the firm implemented a regional decisioning architecture that:

  • Integrates behavioral and transactional signals such as ride frequency, merchant revenues, and payment history into risk models
  • Automates credit eligibility assessment and pre-approved offer generation across multiple customer segments
  • Supports localized workflows and regulatory compliance for six countries while maintaining a consistent core platform
  • Deploys 22 automated decision workflows spanning drivers, merchants, and passengers in under eight months

According to the firm’s Regional Head, Lending Risk Platforms, Andre Tan, the system can now “deliver contextual, real-time credit offers across multiple verticals within the Grab super app. This enables us to expand financial inclusion by providing credit access for underserved users who are economically active but often overlooked by traditional lenders.“

Said Nikhil Behl, President (Software), FICO, the technology partner providing the decisioning platform, said: “When a taxi driver in Jakarta can get credit based on their ride patterns, or a food merchant in Bangkok can access working capital through their delivery history, that’s not just innovation, it’s economic transformation at scale. The project “translates everyday digital behavior into signals that help assess creditworthiness for those previously unseen by traditional lenders.”