Singapore-based credit scoring and risk models assessment solution Bizbaz has announced a strategic partnership with Philippine retail bank Rizal Commercial Banking Corporation (RCBC Bank) to integrate AI-driven credit scoring to expand lending and increase financial inclusion.
Bizbaz said in a statement on Thursday that as part of the partnership, RCBC will pilot Bizbaz’s artificial intelligence (AI)-driven credit assessment and scoring tool which aims to broaden access to loans, especially within the micro, small and medium enterprises (MSMEs), unbanked, and underbanked communities.
The initiative will also support the reduction of non-performing loan (NPL) risks, offering improved predictability assessments.
“The current credit system is broken, with most banks in Asia relying on financial history-based credit risk systems. With most of the Asian population not even having a credit score, the current system is obsolete,
For MSMEs, he said this translates to access to a credit lifeline that would otherwise be unattainable.
For banks like RCBC, he said that this aligns with their commitment to financial inclusion and innovation, increasing predictability, reducing NPL risks, and leading to long-term cost savings.
According to the statement, in the Philippines, 78 percent of the bankable population falls either unbanked or underbanked, positioning the country among the top ten nations with a significant unbanked population.
Cited World Bank, it said Southeast Asia has witnessed a steady rise in NPLs in recent years, with a projected increase in the NPL ratio to 5.9 percent in 2023 from 5.7 percent in 2022, surpassing the global average of 4.2 percent.
In the Philippines alone, it said the NPL ratio stands at 4.2 percent.
“RCBC strives to be at the forefront of emerging technologies and data-driven innovations,
“With this partnership with BizBaz, we can maximize AI’s massive potential and unlock more opportunities for our countrymen, especially the MSMEs,” said Eugene S. Acevedo, RCBC President and Chief Executive Officer.
Bizbaz is an institutional-grade AI-driven credit scoring and risk models assessment solution for the unbanked and underbanked in Asia.
The firm creates a customer or business risk profile by analyzing financials, health, lifestyle, and social footprints.
Leveraging personality-based and voice-based risk assessments, Bizbaz determines suitability for loans.
The streamlined process facilitates faster and more efficient credit scoring, reducing the time borrowers wait for loan approval and mitigating bank default risks.
Its current clients, including a national Indonesia-based bank, have seen increased revenue between two to three times, reduced customer acquisition costs by up to 40 percent, and reduced bad debt default by up to 50 percent.
Bizbaz previously closed its $4 million seed funding in October 2022, led by HSBC Asset Management in addition to investments from Vynn Capital and SOSV.
“We are thrilled to announce our strategic partnership with Bizbaz, making a significant leap forward in our commitment to financial inclusion in the Philippines,
“We believe that by integrating AI into our credit score assessment process, we are not just innovating; we are pioneering a path towards greater access and opportunity for MSMEs,” said Lito Villanueva, Executive Vice President and Chief Innovation and Inclusion Officer of RCBC.
Ma. Pamela Katrina Cabudoy, RCBC Group Head of Data Science & Analytics, said the bank is looking forward to test and learn using alternative and radical data points for predictive AI scoring.
According to her, this will allow the bank to know our MSMEs deeply and be able to aid them with their capitalization needs; whilst balancing the risks.
Bennett Clarence Santiago, RCBC Chief Credit Officer, also said that RCBC has been exploring the use of AI-based scoring for MSMEs.
“A challenging market due to lack of traditional data, the use of AI would allow us to access thousands of non-traditional data that would give insights on potential MSMEs propensity and ability to pay,” he added.
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