This paper analyzes the use of credit during the Covid-19 pandemic in the context of a cash transfer program. Under a Difference-in-Differences approach, I show causal evidence of how the implementation of a cash transfer program impacted the population s credit use patterns, using a combined set of microdata: SISFOH (a household targeting system), the national household survey, and the credit register for Peru. Exploring a discontinuity in the rule for granting emergency income to the poorest population, I show that individuals who received a monetary subsidy increased their total lending in the financial system, in contrast to those individuals who did not. This is worrisome as it is also presented an increase in the interest rates and days of arrears. Furthermore, I also explore some dimensions of population heterogeneity (education, age, gender, informality, among others), finding a differentiated impact according to certain characteristics of individuals. I put a special effort into the informality analysis since, even in the absence of an exogenous identification, this variable presents significant results and passes certain tests of identification.