Promoting digital payments technology among female migrant factory workers

1. Context

India has made substantial progress towards financial inclusion over the last decade. Data from the 2017 Findex survey, which interviewed 3000 lower and middle-class participants in India, reveals that 80% of people in India have access to bank accounts, an impressive increase from the 2014 level of 53%. This increase, along with the expansion of pro-poor financial schemes such as the Pradhan Mantri Jhan Dan Yojana and Pradhan Mantri Suraksha Bima Yojana has brought millions into the fold of formal financial services. Still, much progress remains to be made. While many have access to bank accounts, a bulk of these accounts lie dormant. This prevents the development of a safety net suitable for absorbing the costs of emergencies and job loss. In this context, digital options have been increasingly seen as simple and relevant tools to bridge the financial gap in India, especially in the context of women empowerment.

Our study is also related to the dramatic rise in internal migration in low-income countries. Worldwide, internal migration affects an estimated 763 million people (WEF, 2017); most of this phenomenon is characterized as rural-to-urban. One of the primary drivers of the decision to migrate is to be able to remit money back to migrants’ origin households.
Many of the female workers at Shahi Exports, our industry partner, are rural migrants who move temporarily to the city due to financial distress in their villages. According to our exploratory research and baseline data, they tend to remit a large share (close to 50%) of their wages back home. The standard modus operandi is to cash out their salary from their bank account and transfer the money through over-the-counter agent services (92% of our sample at baseline). By saving time and money, digital payment services have the potential to improve their financial wellbeing.
While these workers are aware of the existence of digital payment platforms, our scoping work and baseline data showed that they do no know how to use digital payment apps and are wary of losing money on these platforms (i.e., the level of trust in digital transfer technology is low). In addition to this, workers face other issues that prevent them from signing up for and using digital payment applications. Workers’ mobile phones must be registered with their bank account in order for them to use the Unified Payments Interface (UPI) applications. Additionally, in our piloting work, technological problems, such as server issues, limit workers’ ability to download and use applications.
In this context, the research studies the impact of training female migrant workers in India to use digital payment applications. Our team, a collaboration between Good Business Lab and IDinsight, in conjunction with Shahi Exports, designed a randomized controlled trial that studies the effect of a workplace intervention -- training sessions to use a digital payments application -- on take-up and use of digital payment applications. We are interested in studying the extent to which training programs of differing intensities may be effective and cost-efficient in improving take-up.
We randomize the implementation of digital payments application training sessions in 19 hostels attached to Shahi Exports factories. We vary the type of training on digital payments that workers receive. In one arm of the study, we provide individualized support, and in the other, we conduct larger group classroom training. In both treated arms, workers are taught how to download, set up, and use (send and receive money) digital payment applications.
We hypothesize that individualized training would be more effective in increasing take-up, compared to classroom-like training. Hence, the intensive intervention aims to overcome trust and cognitive barriers, as well as purely technological barriers.
Our intensive intervention seeks to achieve three goals:
1) Build knowledge of how to use digital payment applications
2) Develop familiarity with the applications
3) Develop awareness of the application’s value proposition (convenience, cheapness)
We expect these three goals to build trust and increase the use of digital payment applications.

2. Intervention

The first part of the intervention consists of a hands-on training session on digital payment applications. The two treatment arms are:

1) Classroom treatment:
This treatment arm will include information on digital payments with facilitated sign-up, opportunities for practice, and financial incentives. A trainer, as well as one trained assistant, will conduct the training sessions, which will consist of batches between 20 and 30 participants and will last one hour.

2) Individualized treatment:
In this treatment arm, the number of workers in each training batch will be smaller than the classroom treatment arm (5 participants per trainer). This will allow dedicating more attention to each of the participants to solve technical issues such as errors while downloading the app, setting up a UPI id, and creating a password. Training sessions will also be more resource-intensive, as two trainers will be assisted by 3-4 trained assistants who will pay individual attention to each of the participants.
During both types of training sessions, participants create a UPI id and learn how to send money using the BHIM app (See appendix: about the digital payments technology). Once participants have set up their UPI accounts, we send Rs. 50 to each participant and encourage them to practice sending money to the person next to them. Facilitators are available to troubleshoot as needed. The second part of the intervention is SMS reminders. Just before participants receive their next month’s salary, we will send a reminder SMS to workers in the treatment groups. This message will remind workers to use digital payment apps to remit money, making the digital payment method salient to the respondent, around the time she would be most likely to use it.

2020-01-27

2020-02-05

1. Use of digital payment applications for remittances
In the primary surveys, we ask whether the respondent uses digital payment applications to remit money. The variable is coded as 1 if the respondent reports using any of the following channels to remit money: mobile money, UPI-based digital payments app, net banking/bank application, and 0 otherwise.



2. Effectiveness of training sessions
During the training sessions, we collect data on whether the participant can send money to someone’s UPI id. It is coded as 1 if she can send money to someone’s UPI id during the session, and 0 otherwise.

During the training sessions, we also collect data on whether the participant can send money to someone’s bank account similar to the modus operandi to remit home through digital payment platforms. It is coded as 1 if she can send money with someone’s bank account during the session, and 0 otherwise. We will use this as a robustness check.

3. Quantification of the extent of the different barriers:
We collect the following indicators from the participants during the training sessions, which are all the necessary steps enabling participants to send and receive money:
1) Whether the participant attended the training
2) Whether the participant has her mobile phone linked to her bank account
3) Whether the participant has mobile balance to send verification SMS from her phone
4) Whether the participant has the required elements (ATM card, mobile phone and SIM card)
5) Whether the participant was able to download the app
6) Whether the participant was able to set up her UPI id

4. Use of digital payment applications for non-remittance purposes

We collect data on whether the respondent uses her phone for the following tasks:
1) to make bill payments, not for goods
2) to buy goods
3) to receive money from someone living in the city
4) to receive money from someone living outside of the city
5) to repay money she had borrowed
6) to lend money to someone

We will create an outcome variable equal to one if any of the above indicators is 1 and 0 otherwise.

The eligible population for the study is female garment workers at Shahi Exports Private Limited, Karnataka, India, who live in 19 selected Janodaya hostels (Janodaya is the NGO managing migrant hostels linked to Shahi factories). Our sample consists of 819 migrant women in these 19 hostels, all of whom use smartphones.
There are two treatment arms and one control arm. Both treatment arms include information on digital payments with facilitated sign-up, opportunities for practice, and financial incentives.

Randomization was carried out at the individual level, stratified by units and reported mobile phone registration at baseline. Within each stratum, a third of the sample was randomized into the soft intervention treatment group (n=273), a third of the sample was randomized into the intensive intervention treatment group (n=273), while the remaining third of the sample in a control group (n=273) did not receive any intervention.

The unit of analysis is the individual/respondent. The primary unit of treatment is also the individual. We chose to conduct randomization at the individual-level as we believe spillover risks are very limited, considering the barriers at stake.

The eligible population for the study is female garment workers at Shahi Exports Private Limited, Karnataka, India, who live in 19 selected Janodaya hostels (Janodaya is the NGO managing migrant hostels linked to Shahi factories) and own a smartphone. These hostels were sampled out of convenience and availability but reflect the overall population of migrant workers in Shahi garment industry in the Karnataka region. Our sample consists of 819 migrant women in these 19 hostels, all of whom use smartphones.
There are two treatment arms and one control arm. Both treatment arms include information on digital payments with facilitated sign-up, opportunities for practice, and financial incentives. In the “Classroom treatment” arm, the batch size is between 20 and 30 participants per trainer; in the “Individualized treatment” arm, one trainer works with up to 5 participants. Participants in both treatment arms also receive two reminder SMS messages.

Randomization was carried out at the individual level, stratified by units and reported mobile phone registration at baseline. Within each stratum, a third of the sample was randomized into the soft intervention treatment group (n=273), a third of the sample was randomized into the intensive intervention treatment group (n=273), while the remaining third of the sample in a control group (n=273) did not receive any intervention.

The unit of analysis is the individual/respondent. The primary unit of treatment is also the individual. We chose to conduct randomization at the individual-level as we believe spillover risks are very limited, considering the barriers at stake.

With only two treatment arms, this impact evaluation will not provide evidence on the relative effects of each intervention type (training sessions and SMS reminders). We expect the bundle (training plus SMS reminder) to have a stronger effect than smaller combinations (training sessions and SMS reminders alone). We do not expect any negative complementarities between the interventions.

Randomization took place using the statistical software package Stata. We conducted randomization using the following procedure:
1) Collect baseline data from hostels: Prior to randomization, we conducted baseline data collection in 19 hostels, saturating each hostel
2) Stratified random assignment by unit and mobile registration dummy: Within each stratum, we randomly assigned a third of the sample to control, a third of the sample to the soft intervention and a third of the sample to the intensive intervention. In case the total number of individuals in a stratum is not divisible by 3, we randomly decided whether the last individual (and second-last individual) was in either of the treatment arms or control.

We conducted randomization once, after baseline was completed.

Randomization took place at the individual level

No

819 participants (migrant women)

819

273 (equally divided)

10pp

Financial Inclusion : promoting digital payments among migrant factory workers