Series A funds Entrée Capital, Founder Collective, OIF Ventures, Endeavor Scale-Up Ventures and January Energy also participated.
According to Pagaleve co-founder and CEO Henrique Weaver, the money will be used primarily on technology, to improve the user experience, in addition to increasing the current base of 500 retailers to 1,000 by the end of the year, when they also hope to reach serving a few hundred thousand consumers - while today there are tens of thousands.
"We are proud to be able to close an investment round like this, amidst a turbulent global economic backdrop. This only strengthens our commitment to democratize the access to installment payments for millions of Brazilians," said Henrique.
Buy now, pay later
Founded a little over a year ago, Pagaleve works in the B2B2C model, with a focus on e-commerce. The fintech bets on four installments, with no card or interest, and no minimum amount for installment through Pix. The user only pays if he or she is late. In this case, a fee of R$ 20 is charged per late installment, regardless of the value.
On the one hand, for the final consumer, Pix is a simpler payment alternative for retail purchases. The main advantages for retailers are to improve the cash flow, increase sales and attract new customers. Reserva, Lupo, Multilaser and Ri Happy are some of the 500 retail partners.
Pagaleve proposes to serve three publics poorly served by the market: people who do not have a credit card; people who have a card, but have problems dealing with the limit; and those who do not like to use a card, especially young people from generation Z, for fear of losing control of their spending and because of high interest rates.
Also according to the CEO, the approval is done in just 5 seconds, transaction by transaction, based on machine learning algorithms.
"Pagaleve has built a risk engine unlike anything that has existed in Brazil, combining cutting edge technology, machine learning algorithms, and a deep knowledge of the local market. The result of this is a high approval rate, speed of information processing, while we have defaults within our risk appetite," concludes Henrique.
Series A funds Entrée Capital, Founder Collective, OIF Ventures, Endeavor Scale-Up Ventures and January Energy also participated.
According to Pagaleve co-founder and CEO Henrique Weaver, the money will be used primarily on technology, to improve the user experience, in addition to increasing the current base of 500 retailers to 1,000 by the end of the year, when they also hope to reach serving a few hundred thousand consumers - while today there are tens of thousands.
"We are proud to be able to close an investment round like this, amidst a turbulent global economic backdrop. This only strengthens our commitment to democratize the access to installment payments for millions of Brazilians," said Henrique.
Buy now, pay later
Founded a little over a year ago, Pagaleve works in the B2B2C model, with a focus on e-commerce. The fintech bets on four installments, with no card or interest, and no minimum amount for installment through Pix. The user only pays if he or she is late. In this case, a fee of R$ 20 is charged per late installment, regardless of the value.
On the one hand, for the final consumer, Pix is a simpler payment alternative for retail purchases. The main advantages for retailers are to improve the cash flow, increase sales and attract new customers. Reserva, Lupo, Multilaser and Ri Happy are some of the 500 retail partners.
Pagaleve proposes to serve three publics poorly served by the market: people who do not have a credit card; people who have a card, but have problems dealing with the limit; and those who do not like to use a card, especially young people from generation Z, for fear of losing control of their spending and because of high interest rates.
Also according to the CEO, the approval is done in just 5 seconds, transaction by transaction, based on machine learning algorithms.
"Pagaleve has built a risk engine unlike anything that has existed in Brazil, combining cutting edge technology, machine learning algorithms, and a deep knowledge of the local market. The result of this is a high approval rate, speed of information processing, while we have defaults within our risk appetite," concludes Henrique.