Transcription
Digital lending is rapidly changing how Filipinos access credit, from everyday expenses to small business funding. With traditional bank financing still out of reach, millions of households and micro entrepreneurs are turning to app-based lenders. These lenders are stepping in, using data and technology to deliver loans in minutes, not weeks.
But as the sector scales, so do bigger questions about credit quality, regulation, and long-term sustainability. So, what is really happening inside the country's fast-growing digital lending industry? Joining us now is Koko Marisha, the president and CEO of We Fund Lending Corporation, the operator of the OneHand platform. Hi Koko, thank you for being here with us.
Honor to be here Mikey. Thanks.
Yeah, Koko, let's start with the bigger picture. Talk to us about the state of digital lending in the country today.
Uh, digital lending right now is, I would say, on the rapid growth stage. Uh, it's been on a hypergrowth for the past five years. Uh, hypergrowth, um, defined as anywhere from, you know, upper double digits to even triple-digit growth. Rapid growth is, uh, mid- to high, uh, double-digit growth. So, yeah, it's still growing.
Okay. So, it's still growing double-digit, but not as high for it to be hypergrowth. What caused that, um, deceleration?
I guess, um, uh, in a good way. We're covering more and more of the credit invisibles. So, of course, now it's, uh, we expect it to be on a steady and sustained growth in the next five years.
Okay. Steady and sustained growth in the next five years. Interesting, because, um, the economy slowed to 3 to 4% in the last two quarters of 2025. How did that softer environment affect the demand for your products for consumers and MSMEs?
So, usually for our type of consumers, we're into grassroots, right? So, we cover those who are underserved and, uh, underbanked. Um, and so, usually, there's a direct correlation between, uh, the economy and, uh, our users, right? So, when, when there's a slowdown in the economy, usually, uh, we see a higher, uh, interest coming from our borrowers and users, right? So, for now, we, we see a lot, for example, the first-time borrowers, downloading the app, registering, and trying to gain approval.
Yeah, talk to us about that correlation, uh, Koko. Um, you said that, you know, when the economy softens, as it has in the last two quarters of 2025, there's an uptick in borrowers, particularly first-time borrowers. Um, what are the needs? What are their funding needs? What are they, um, you know, what, when they take, take those loans, what do they use them for?
So, usually, it becomes like consumption-based type of usage. So, of course, when there's a downturn in the economy, uh, there's a credit crunch, right? So, whether, uh, sometimes either they get laid off or reduced number of, uh, hours at work, so they need some bridge assistance or bridge loan for assistance, right? Uh, the pa- peligro, or for example, if you get paid, uh, on February 1st, uh, the next paycheck will be on Feb 15th, but you usually lose out on the money already on, you know, Feb 12th or 13th. So, they kind of like need that. So, the assistance they need is to pay for utilities, to pay for emergency, uh, maybe to pay for traditionally seasonal type of expenses, whether it's tuition. So, that's the type of, uh, uh, loan usage we see, especially on the downturn of the economy. Uh, but when there's, so it becomes a bit risky, right, in terms of collections. Uh, yeah, so that's what happens. But usually, when the economy is better, we see a lot of usage in terms of, uh, capital.
Yeah, that's what we want. We want the usage for capital needs because that's going to lead to productivity gains. In the meantime, um, you know, what are your typical loan sizes and, and what are the approval timelines behind them?
Okay, so we define ourselves as, uh, nano loans or nano lending. So, it's anywhere between 2,000 pesos up to 50,000 pesos, payable between 30 days to 150 days. Uh, and, uh, interest rates anywhere from 7% to, until March 31st of this year, 15%. Because we're regulated by the SEC, and there's an interest rate cap.
And sometimes, when, uh, usually traditional, uh, financial institutions hear about our interest rate, like banks, they find our interest rate a bit on the steep side. But again, what we're doing, right, like, um, fintech companies like OneHand, we're trying to positively disrupt the 5-6 industry, which, as you know, if you borrow 5 pesos today, in 7 days, you pay 6 pesos. So, that's 20% a week, times four weeks, that's 80% a month.
It's high, but if you go to a loan shark, those interest rates are, are even higher. What are, what, what defines a loan shark today? Today? Uh, how high are the interest rates? And, and I guess, with these guys, they don't operate there. I mean, or you guys are governed by the SEC, but these guys don't follow those rules. So, in terms of interest rates for loan sharks, how high do they go?
It's really tragic, right? Like, what the 5-6 can be as high as 80% a month. And not only that, right, Mikey? So, the sad thing is, we're trying to bring dignity into, uh, lending or borrowing because if you don't get to pay, of course, as you, I'm sure you've heard stories, loan sharks or other predatory lenders or even fintech lenders that are not compliant, they harass you. Uh, they, they sell your, uh, data to other unscrupulous, uh, financial institutions. So, it's really, um, a violation, right? You need the money, and then you get treated that way. So, that's one thing that we really want to eradicate.
Yeah. Okay. Koko, as you see stronger demand, are you also seeing higher credit risk?
Uh, on an economic downturn? Yes. Right. So, we do see a lot of first-time borrowers, but maybe a bit riskier based on our underwriting, uh, insights. Uh, but having said that, if, uh, the economy is on a growth path, uh, according to expectations, so we see, um, yeah, still a lot of number of borrowers, but lower risk.
Yeah.
Um, you guys are the biggest in terms of fintech lending in the country. So, you guys have a lot of data. You've got a lot of real-time data. So, Koko, what's that data telling you about the general health of the Filipino household and the average MSME in today's economy?
Okay. So, I can speak, maybe not, uh, Mikey, not on the MSME. Uh, uh, really, I can maybe define it as nanopreneurs. Okay. Okay. We do the grassroots. So, maybe Class C, upper D, of society and some nanopreneurs, which is maybe some online sellers, store owners.
So, what we're seeing right now, on a great note, right, is well, Filipino business, um, nanopreneurs love to borrow, but they also love to pay and pay on time. So, that means their credit scoring becomes higher each time as they repeat. Uh, so that's one. So, they get more loan amount, uh, longer tenor, lower interest rate. But at the same time, we love these kinds, and I think you mentioned, right, we love these kinds of borrowers because, um, they use other people's money, right, to generate more money for themselves, right? Which is fantastic, right? So, it's income generation.
Which should really help you keep your head above the water. Um, at an industry level, or, or perhaps just on your platform, what are delinquency and default rates like?
Okay. So, when I see this, I can only say a range, right? I can't say exactly the figure, but, and I can only speak about OneHand or WeFund.
So, um, for, usually the industry, uh, delinquency rates or NPL on an annualized basis, right, for a vintage is between 18 to 23%. OneHand is between 9 to 13%. So, we're, we would say we can confidently say we're the best in the industry. It's a bit high coming from financial, uh, institutions' perspective, but this really are the standard in our industry because of the, of course, higher risk.
Interesting, because most digital loans are unsecured, um, you know, without traditional collateral. How do you ensure repayment?
Actually, that, that's a fantastic question, right? And and people now talk about AI. And my answer to that question is AI. Um, AI determines the risk for us and the credit score or credit persona of a particular individual. So, maybe if I use your example, so let's say, uh, Mikey, uh, your, your this status, because this income, you live in a certain address that you place there. You upload one valid ID. So, my AI can determine if your, what you wrote in the application is the truth because I can scrape through your telco scores. Yeah.
Uh, mobile device, uh, data, um, social media footprint.
And I get all these data points in a matter of how?
Less than 5 seconds.
Less than five seconds. So, for a first-time borrower, from download to disbursement in your preferred e-wallet or bank, the whole process takes less than 5 minutes. For a repeat borrower, the whole process takes less than 45 seconds.
So, it's a very deeper and not human-centric KYC.
Yes.
Um, so, that said, you know, you are a fintech platform, so you lean heavily into AI.
Yes.
How, how much of it? How much do you lean into it right now in 2026?
I would say AI is in our DNA. So, in every aspect of the process, uh, from customer acquisition down to collections, it's all, uh, enabled by AI. So, for example, like for C, uh, customer service, right, to, to remind you, uh, of payment. Uh, of course, we do have, I think we're one of, if not the only one with a 7 days a week, 9 to 9:00 a.m. to 9:00 p.m., uh, customer service live. We also have chatbots. We also have, uh, AI reminders, uh, uh, for, to, to collect and remind you of your payment obligations. So, but that, that's, that's it. That's the whole process. There's an orange thread, which is AI, that powers it.
Completely streamlined. Okay. In terms of your borrower profile, what is the percentage of males to females? Is there a particular, are, are there any, out of all the data that you look into, does anything really stand out?
I would think what stands out, and, uh, apologies to the males, right, we, we love lending to women. Okay. Seriously. I think the lowest risk in terms of gender would be females, especially housewives or, um, females between 25 to 40 years old, usually residing, actually, in Metro Manila, because we found out they have the lowest risk component because they use the money to either fund their online businesses, either to, you know, the nature of the, uh, the usage would be for their families, right?
Um, and so they are actually more inclined to pay us back. Yeah.
Um, so sometimes, in contrast, in contrast, contrast the males, okay, so this is just data, right, again, uh, uh, males, 20 years old to 40 years old, usually non-university, university graduates, also in Metro Manila, the default rate is higher because the usage sometimes tends to be not on businesses, but maybe some,
vices.
Maybe can be on vices. Yeah.
Okay. All right. So, females are less risky borrowers. Okay. What happens when people are unable to pay? What then happens?
So, uh, for, for us, right, because we're not collateralized, as you mentioned earlier. So, uh, so there's, there's it's unsecured.
So, what happens is, uh, that's it. So, in, in a way, when, when we remind them and, uh, they don't get to pay, uh, we usually, at least for OneHand, give them, uh, a payment plan. And if they still can't pay within that, uh, uh, prescribed payment plan, then we report that credit data, that bad history, or whether good history or bad history, we do have a credit bureau, bureau called CIC, Credit Information Corporation. So, all financial, uh, financing and lending institutions, even banks, would have to submit data every. And so, there's a credit database. So, the next time they loan, and whether us or any other financial institution pulls data from CIC, and they have a bad credit history, so the likelihood that they will be approved will be, um,
So, interesting.
Not so good. So,
all that big data is able to, you know, give you the latitude to give loans without the unsecured, you know, without the traditional collateral. Very interesting. How else do you see AI and, and, and the big data you collect from it changing this industry?
So, I think that's the biggest change where you mentioned where, right now, I think what happens is, I think the noble purpose of our industry, specifically OneHand, is for giving credit history to the invisibles, right? The, it's, it's so tragic, right, because the minute anyone doesn't have any credit footprint, then the more they can't use higher, uh, or better financial services like higher loans or even insurance or, and the like. So, once you give them a credit footprint, it leads really to, you know, uh, financial inclusion, financial empowerment, national development, right? So, that's, that's how, um, we're doing it, and that's why we, uh, that's a purpose of, uh, uh, fintech, because we do serve the ones that, uh, traditional financial institutions like banks, don't cater to, because banks use, uh, traditional data, proof of billing, proof of address, ITR, proof of employment. We don't use any of that. We use alternative data.
There are gaps that you guys fill. There are strengths and their weaknesses. At the same time, we're seeing more partnerships between digital banks and traditional banks, uh, to scale. Um, on that note, OneHand recently secured a credit facility from HSBC. Um, you know, this bank-fintech model is becoming pretty dominant as everybody looks to scale. And, you know, even as you lend out, you yourself, you guys at OneHand, you guys need also financing. You always also look to borrow from the banks. Talk to us about, um, about this dynamic.
You know, when, as you asked that question just now, it made me look back five years ago when we started looking for funding from traditional banks. It was really tough, Mike. It's really, really tough because, uh, at one, at that point, and I don't fault them for it, traditional banks didn't want to lend to fintech lenders like us because, like, what, what do you guys do? How, AI? You use that, or you don't use any collateral. You just have one valid ID, and you can approve a loan in less than five minutes. So, really, do you have that system? Well, well, yes, we do. And, and AI, well, now five years after, you look back, AI is all over, and even banks are using it quite aggressively. And so, because of that, uh, banks, I'm proud to say, and I, yeah, that I, I can confidently say that we are the first fintech, pure fintech cash lender that any traditional bank in the Philippines funded. Okay. And so, we paved the way for that. And, uh, I would, and I'm happy to say that all the banks who have funded us has 3x to 10x their portfolio with us over the last three years. And so, we use this funding to actually increase our loan book to cater to more of the underserved, and that's what powers it.
Okay. Very interesting. Yeah. I wanted to ask you, um, in terms of size, I want to understand your platform today. How many active borrowers do you have? What's the size of your loan book, and, and what are monthly disbursements like?
Okay. So, it, in terms of the active, uh, users, we have at any given time, uh, like right this very second, about between two to three million, uh, active borrowers with no default.
Uh, we, our loan size typically is about 6,000 to 7,000 pesos average, uh, loan size. Our disbursement, specifically for OneHand, is between 3.5 to 4.5 billion a month.
Mhm. Mhm.
And so, for entrepreneurs, for the people watching today, that, that want to cater to this nano market, um, what is your advice to them? How, how, how do they tap them, and how do they create products that would appeal to them?
Not all AIs are made the same. Any college kid with a garage can make an algorithm, right? But at the end of the day, what makes an AI smart is the number of data that goes through it and how the AI tweaks and learns from all that data to risk assess each borrower accurately in order to lessen the default. So, my advice is really to have a strong AI. And I think we're very fortunate that we do have a gold standard in terms of AI risk assessment and collections. So, that's one. So, that's the, the advice is, uh, um, very strong AI backbone, strong branding, uh, compliance, very polite customer service, and of course, very high energy and competent team behind it.
Yeah. Okay. On another front, I want to talk to talk to you about interest rates and the cost of credit. Um, as we all know, the BSP has been on an easing cycle since August of 2024. Um, you know, they've been coming, interest rates have been coming down in baby steps. Does this necessarily translate to lower borrowing costs for your lender, for your, uh, consumers?
Not as much as we want to. Uh, it doesn't necessarily translate because we don't, of course, we don't necessarily, uh, um, we don't get directly from the BSP. We have a, a middle layer that we get our funds from. Um, but every time, actually, uh, BSP lowers its rates, we try to negotiate with our funders if we can lower our funding cost as well.
Mhm. As the economy stabilizes, where do you see the next phase of growth coming from for digital lending?
Depends on which aspect of digital lending migrates. So, for example, um, the good, the great thing about digital lending or fintech like us, we disrupt, we positively disrupt. So, I think we've already disrupted the 5-6 industry. So, we, we, I hope that we're making progress with that, that we're lessening the usage of 5-6 by humanizing and dignifying lending at that level. So, in the future, I think, in terms of that aspect, is in having value-added services together with that product. So, for example, not just simply cash loan, why can't you, as a cash, uh, loan borrower, can I give, uh, HMO with you? Can I offer you free movie tickets? You know, so something value-added that can actually, uh, increase your, uh, usage, uh, experience, right? And apart from that, what else can we disrupt in the lending industry? So, we're right now actually looking at OFW lending industry. How can we tech-enable that to make it more pleasant, quicker, more dignified?
That's another conversation altogether, but I just heard we have like less than a minute left. Okay. So, talk to us in a nutshell about how AI can, and how you guys can are looking to disrupt the OFW industry and go ahead.
So, OFW industry right now, uh, it's got, uh, the lending process, uh, can take anywhere from 24 hours to even as long as 7 days. We plan to make it in less than 10 minutes, and purely app-based. So, abangan.
Wow, abangan. That's going to change the game, and it's going to make it easier for our, our, our other Filipinos all over the world to send money home and, and give it low growth, high population. We're going to be, we're going to be in this OFW, uh, era for a while. And at least you're, you're there to help them. So, thank you so much, Koko, with, um, OneHand and WeFund.
Thank you. Thank you for having me.