How Indonesia’s BNPL Giant Leverages Data Science to Drive InnovationSeptember 1, 2022 0 comments
Data science and machine learning are some of the most complex yet important business concepts today. And many companies, irrespective of their niche, rely on them to deliver a better user experience to their customers.
But what role do data science and machine learning play in the development of innovative financial systems, especially in countries like Indonesia?
The lack of credit history data combined with the substantial use of mobile phones in Indonesia represents a sweet spot for fintech companies to deliver advanced user-friendly consumer financial solutions.
In this episode of Data Point of View, Laurie Hood, Chief Marketing Officer at Mobilewalla spoke with Joel Samuel, VP, Head of Machine Learning Engineer, at FinAccel, the parent company of Indonesian Buy Now, Pay Later (BNPL) platform Kredivo.
They discussed the importance of machine learning and data science in accomplishing business goals and delivering a better user experience, the challenges in finding data science specialists, fintech and e-commerce development in Southeast Asia, and the essence of starting small.
Key insights from the podcast
There are two main reasons to provide better solutions in Indonesia
Joel and FinAccel aim to provide better fintech solutions to the Indonesian market for two reasons.
“The first one is the low penetration of credit cards In Indonesia. There are only 17 million credit cards compared to our population, which is around 250 million nowadays. So, there are only 0.07 credit cards per capita. It’s really low. The second one is the high penetration of mobile phones.
Currently, Indonesia has more than 119 million mobile phones. It’s almost 0.8 mobile phones per capita. So, it’s a sweet spot. You have a mobile phone, but you don’t have a credit card.”
We believe in ‘fail fast and learn fast.’
Joel and his team strongly believe that projects should be done little by little. That way, even if you fail, you’ll have the opportunity to quickly learn from your mistake.
“We can spot if there’s something wrong with the model that we pushed to production. We also really believe in ‘fail fast and learn fast.’
We always push the production little by little to see the effect and the impact of the model. So, we start with the simple things and the small things.”
According to Joel,
“E-commerce is booming in Indonesia, and the country has three or four “unicorns” that started based on e-commerce. One of the challenges with e-commerce, not only in Indonesia, but all around the world, is cart abandonment.
And that issue is more about the payment options or the payment channels. Most people abandon the cart because they have a hassle with the payment – that’s FinAccel’s sweet spot.”
Regarding the view of data science by senior leadership, Joel shared that “since the beginning, we’ve had buy-in from the top level, with the thinking that if we want to disrupt the best player in the market, like the bank or the multi-finance company that is already there, the one thing that we can do is introduce data science methodology.
He explained that they solve the problem in a better way because the firm’s top level management believes that data science is a big opportunity.
“But even though we have already defined our aim or the initiative that’s come from the top management, we have to prove that we can deliver that initiative or the buy-in at the very first unit.”
A challenge for data science teams is building organizational trust. At FinAccel the team had regular meetings with the COO and CEO over the first two years the team was in place to present their results.
They also have a good monitoring workflow and framework so that they can quickly spot if there’s something wrong with a model that was pushed to production.
Joel and his team have built confidence by starting with a small problem, moving quickly to production, and then seeing the results fast.
This way management can immediately see the impact of their data science approach.
Watch Mobilewalla’s Data Point of View podcast featuring Laurie Hood and Joel Samuel here.