DOST, AIM, and Unistar collaborate to harness power of AI, machine learning in assessing condition of repossessed second-hand motorcycle units for re-sale. Result: ARMAS, Automated Repossessed Motorcycle Assessment System, at a cost more less of Php5 million.
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- EDD K. USMAN | Twitter: @edd1819 | Instagram: @bluestar0910 | Facebook: SDN — SciTech and Digital News
ASIAN INSTITUTE OF MANAGEMENT, Makati City (SDN) — With traffic jams, road congestion in the Philippines, especially Metro Manila, now a life-struggle every day, two wheeled vehicles have become a necessity for many commuters.
Reporting to work, going to school, hitting the malls, or visiting friends or tourist spots are some of the many attendant reasons motorcycles in the Philippines have proliferated and its number continues to increase.
Whether for private use, or as commercial motorcycle taxi company, like Angkas, JoyRide, and Move It, only three legally operating in the country, the two-wheeled vehicles are a must in getting quickly to one’s destination because it can easily snake in and out of traffic grids.
Well, but not necessarily safer than four wheeled vehicles! In fact, the Highway Patrol Group (HPG) of the Philippine National Police (PNP) and cited in a news report by the Philippine Star, had registered at least 4,000 motorcycle crashes in 2023’s first quarter (Q1 2023).
An online news platform, ecomparemo.com, quoted Department of Transportation (DOTr) Assistant Secretary Mark de Leon as saying that Metro Manila alone registers a daily average of 262 road accidents.
Of this number, de Leon said, 50 percent are caused by motorcycles, 19 percent by pedestrians, and 14 percent by drivers of four or more wheels vehicles. It’s a grim statistic, then, for motorcycles.
Meanwhile, the Philippines in 2022, according to Statista.com, had “7.81 million registered motorcycles and tricycles” and, that, ‘between January and September 2023 there were an estimated 1.47 million new motorcycles, tricycles, and non-conventional motorcycles registered” in the country.
With that number of motorcycles, it is safe to believe that thousands and thousands were acquired through companies that provide financing. And of that number, surely there are those who bought their motorcycles through financing who were not able to pay the monthly amortization. In which case, their units are repossessed and flowed back to the market as second-hand motorcycles.
Out there, fortunately, there are companies that accept and sell used motorcycles because there is a market for second-hand units for those who prefer a cheaper alternative than the expensive brand-new units.
Before financing companies sell the units, they have to assess them to ensure buyers get fully functioning second-hand motorcycles. Assessment of a unit are, of course, made manually, with hardly any technology involved which, to say the least, humans are not perfect. Mistakes in assessment and analysis of the condition of second-hand motorcycles may happen. And could be costly to seller and buyer.
In connection with this, the Philippine Council for Industry, Energy, and Emerging Technology Research and Development, the Innovation Council of the Department of Science and Technology (DOST-PCIEERD), the Asian Institute of Management (AIM), and the Unistar Credit and Finance Corporation (Unistar) have collaborated to develop and come up with a technology that taps the power of artificial intelligence (AI) and machine learning (ML) in the assessment of second-hand motorcycles.
PCIEERD, headed by Dr. Enrico “Eric” C. Paringit, executive director, funded the project worth more or less Php5 million. AIM and Unistar co-developed the ARMAS technology.
On June 18, the three collaborators launched ARMAS (Automated Repossessed Motorcycle Assessment System) with PCIEERD and AIM turning over in an event at AIM the technology to Unistar through Ernesto Manzano, head of Asset Recovery Management.
Before ARMAS, it was learned that Unistar technicians were spending one man-hour assessing per motorcycle unit. That’s 3,000 man-hours a month per 3,000 units. But with the state-of-the-art technology, assessment lasts only five minutes, according to Unistar.
In his brief acceptance remarks, Manzano described Project ARMAS as “a significant milestone in our journey of innovation and excellence.”
Project ARMAS and its potentially game-changing impact
He also cited what could be the technology’s game-changing impact on Unistar’s work.
“By streamlining our assessment process, ARMAS will save time, reduce errors, and enhance the overall experience for our users. Project ARMAS is just the beginning. We will continue to refine, expand, and innovate, ensuring that our solutions remain at the cutting-edge of technology and continue to meet the evolving needs of our industry,” Manzano emphasized.
Paringit agreed with what the Unistar official said about ARMAS impact on the company’s assessment of motorcycles.
“Like I said a while ago, what they can save they can give it back to their customers by providing them reliable service, reduction of production costs, giving more competitive price,” the PCIEERD official said.
Paringit hopes the ARMAS technology “can be proliferated, scaled in other companies. Actually, this works for companies that are conscious about their data.” He also assured that PCIEERD does not accept and fund just about any project, emphasizing, “We scrutinize projects for their value to the company and to the public because it is the people’s money.”
In a separate statement, Manzano revealed that Unistar is presently accepting repossessed motorcycles belonging only to the four Japanese brands, Honda, Yamaha, Suzuki, and Kawasaki.
A media brief provided to reporters said Project ARMAS is an AI-based decision support tool aimed at streamlining asset recovery operations at Unistar, a local credit and financing institution for the motorcycle market. It will leverage Unistar’s unique and rich datasets.
One of the technology’s impacts involves Unistar being able “automatically evaluate the condition and health of repossessed motorcycles…prediction of the quality and resale value.”
With ARMAS, the financing company said allows a reduction of evaluation time of around 30 minutes done manually to only five minutes through automated evaluation.
Imagine the time saved, not the least man-hours, resources and, hopefully, little to no error. (/)