BPI pilots agentic AI for small business loan approvals

BPI pilots agentic AI for small business loan approvals
AI transforms loan approvals

Banks are increasing their use of data-driven tools to widen credit access for underserved borrowers, particularly small businesses that need faster funding decisions. BPI is now testing agentic artificial intelligence to shorten approval times while expanding its use of alternative data and new underwriting models.

Highlights

  • BPI pilots agentic AI to accelerate small business loan approvals, using alternative data and deep learning for faster application processing.
  • The bank develops an intelligent data stack by consolidating legacy system information and integrating external data to improve underwriting for SMEs and non-customers.
  • BPI's attributable net income drops 8.32% to P16.07 billion in Q3, with nine-month profit down 3.14% to P48.9 billion.

AI lending pilot and data strategy

As reported by BusinessWorld Online, Bank of the Philippine Islands is running a pilot program that uses agentic artificial intelligence to speed up loan approvals for small businesses. Maria Cristina “Ginbee” L. Go, BPI head of consumer banking and executive vice-president, said at a forum on Wednesday that the technology is being tested to make application turnaround faster and more efficient for business owners who need capital immediately.

The initiative forms part of the bank’s broader push to use alternative data, deep learning, data analytics and data science to build more data-driven models for loan decisioning and underwriting, including for non-customers. Go said BPI is also working on a major project to consolidate information held across the bank’s legacy systems while bringing in more external data to create what she described as a more intelligent data stack.

Implications for SME credit access

BPI is also setting up a new lending model for subsidiary BPI Direct BanKo, Inc. aimed at improving visibility into the small and medium enterprise sector through alternative data and AI. The bank says this is especially relevant for home-based businesses that often lack formal documentation, making them harder to assess under traditional credit processes.

Under the model, mobile advisers and loan assistants visit communities and businesses to observe inventories and sales on site, allowing the bank to derive what it considers a more realistic valuation of borrowers’ operations. The effort reflects a wider industry move toward combining field-based assessment with technology tools to reach smaller enterprises that remain outside conventional banking documentation standards.

BPI’s attributable net income declines by 8.32% to P16.07 billion in the third quarter. Its nine-month profit goes down by 3.14% to P48.9 billion.

In earlier coverage, we examined Pakistan’s directive on expanded SME lending as part of priority-sector finance targets.

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