AmBank Brings First Auto Finance Digital Approvals to Malaysia

  • Emma Sandler
  • November 27, 2017
  • 0

© Can Stock Photo / szefei

AmBank — one of the largest banking groups in Malaysia — launched the first digital instant approval service for auto finance in Malaysia, the company announced at a press conference today.

The instant approval service is offered through a Mobile Application Terminal (MAT), according to a separate press release. AmBank plans to expand the product to other retail services. MAT allows users to submit loan applications, capture documents’ images, and obtain approval for financing within 30 minutes at preferred dealer locations if all required conditions are met, Chief Executive Datuk Sulaiman Mohd Tahir said during the press conference, according to a published report.

“We expect to hit 7,500 applications to be made via MAT monthly,” he said. “AmBank’s auto finance has about 11% share of the market,” according to a published report.

Auto loans make up 48% to 49% of AmBank’s retail financing portfolio, according to the report. Malaysia is unique among Southeast Asian nations in having its own automotive brands — Proton and Perodua, according to the Oxford Business Group. In addition, Honda, Toyota, Volvo, and Jaguar Land Rover are present in the country. Chinese automaker Zhejiang Geely Holding — which also owns Volvo — acquired a 49.9% stake in Proton in 2017. “Malaysia is still an economy experiencing high growth relative to developed economies, with increasing per capita income,” the 2016 report said.

So far, AmBank has deployed 800 MATs to its 2,500 car dealers as well as 150 staff at 175 branches nationwide, Sulaiman said.

“We have deployed MAT since July 1, to 138 AmBank sales advisors. We have received more than 2,400 hire purchase application via the terminal nationwide,” he said, adding that MAT’s successful loan approval rate is between 40% and 50%.

Additional features for MAT include features like a biometric reader that allows customers to perform thumbprint verification and optical character recognition to capture information from documents.

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