Financial Inclusion in LatAm
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Financial Inclusion in LatAm

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Description

Financial inclusion remains one of the main obstacles to economic and human development in Latin America. For example, in Argentica, Chile, Colombi...

Prizes
These will be the awards once the competition is over:1st Place: 10.000 pts 2nd Place: 9.000 pts 3rd Place: 8.000 pts 4th Place: 7.000 pts 5th Plac...
Competitors
  • Carlos Villarroel
  • Claudio Andres Balmaceda
  • Juan Acostupa
  • Evy Nav
  • Raul Vila
  • Sebastian Alibaud
  • Junior Valentin Llanos
108 Competitors Published at: 03/17/2020
Total Prize
$0
This competition is finished
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Timeline

Begin
2020/03/17
Finish
2020/06/17
Complete
2020/07/01

Competition start: 2020/03/17 00:00:00
Competition closes on: 2020/06/17 00:00:00
Final Submission Limit: 2020/07/01 00:00:00

This competition has a total duration of 3 months, within which you will be able to make your submissions and obtain results automatically. Once the first part of the competition is over, you will have one week to choose your best model and submit it to be graded and considered for cash or points prizes. 

This competition does not have a "Late Submission" option.


Description

Financial inclusion remains one of the main obstacles to economic and human development in Latin America. For example, in Argentica, Chile, Colombia, and Mexico only 9.1 million adults (or 13.9% of the adult population) have access to or use a commercial bank account.

Traditionally, access to bank accounts has been considered an indicator of financial inclusion. Despite the proliferation of mobile money in Latin America and the growth of innovative, state-of-the-art solutions, banks continue to play a key role in facilitating access to financial services. 

Access to bank accounts allows households to save and facilitate payments, while helping businesses increase their credit capacity and improve their access to other financial services. Therefore, access to bank accounts is an essential contributor to long-term economic growth.

The goal of this competition is to create an automatic learning model to predict which people are most likely to have or use a bank account. The models and solutions developed can provide an indication of the state of financial inclusion in Argentica, Chile, Colombia, and Mexico, while providing an understanding of some of the key demographic factors that could drive people's financial outcomes.


Evaluation

The evaluation metric for this challenge will be the percentage of respondents for whom you predict the binary "bank account" classification incorrectly, i.e. the Accuracy of the model.

Your presentation file should look like this:

unique_id                   bank_account
<string>                    <number>
uniqueid_1 x Argentina              1
uniqueid_2 x Argentina              0
uniqueid_3 x Argentina              1  


Rules

Competitors can register and submit solutions as individuals (not as teams, at least for now).

As this is a learning competition, apart from the rules of the DataSource.ai Terms of Use, no other particular rules apply.

Maximum 10 solutions submitted per day.

Please note that there is no division of the public/private ranking table for this challenge.

Note: We reserve the right to modify these rules at any time as needed.


These will be the awards once the competition is over:
1st Place: 10.000 pts 
2nd Place: 9.000 pts 
3rd Place: 8.000 pts 
4th Place: 7.000 pts 
5th Place: 6.000 pts 
6th Place: 5.000 pts 
7th Place: 4.000 pts 
8th Place: 3.000 pts 
9th Place: 2.000 pts 
10th Place: 1.000 pts

Points: 10000pts

Total Prize: $0


Financial Inclusion Survey Data

The main data set contains demographic information and which financial services are used by approximately 33,610 people throughout Latin America. This data was extracted from various surveys ranging from 2016 to 2018.

The data has been divided into "train" and "test". The test set contains all information about each individual except whether the respondent has a bank account or not.

Its objective is to accurately predict the probability that an individual has a bank account or not, i.e., Yes = 1, No = 0.

About the Data
You are asked to make predictions for each unique identification in the test data set about the probability that the person has a bank account. You will train your model with 70% of the data and test your model with the final 30% of the data.

  • Train.csv is 70% of the data, in four Latin American countries (i.e. Argentina, Chile, Colombia, Mexico)
  • Test.csv is 30% of the complete data set of Latin American countries.
  • SampleSubmission.csv is an example of what your submission file should look like. Note that the unique_id variable of the submission file is:
 
uniqueid + " x " + country name

The order of the rows does not matter, but the names of the unique identifiers must be correct. The "bank_account" column is your prediction of the probability that the user has a bank account.

Two or more countries may have the same unique_id, so your presentation file must have uniqueid x country.

Definition of Variables
  • country = Country interviewee is in.
  • year = Year survey was done in.
  • uniqueid = Unique identifier for each interviewee
  • location_type = Type of location: Rural, Urban
  • cellphone_access = If interviewee has access to a cellphone: Yes, No
  • household_size = Number of people living in one house
  • age_of_respondent = The age of the interviewee
  • gender_of_respondent = Gender of interviewee: Male, Female
  • relationship_with_head = The interviewee's relationship with the head of the house:Head of Household, Spouse, Child, Parent, Other relative, Other non-relatives, Dont know
  • marital_status = The martial status of the interviewee: Married/Living together, Divorced/Seperated, Widowed, Single/Never Married, Don't know
  • education_level = Highest level of education: Non-formal education, Primary education, Secondary education, Vocational/Specialised training, Tertiary education, Other/Dont know/RTA
  • job_type = Type of job interviewee has: Farming and Fishing, Self employed, Formally employed Government, Formally employed Private, Informally employed, Remittance Dependent, Government Dependent, Other Income, No Income, Dont Know/Refuse to answer

For this competition stage, you need to send your submission file with this details:

# of columns:
Column names: ,
# of rows:

This competition is finished


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