Societe Generale (SocGen) is a French multinational banking and financial services company. With over 1,54,000 employees, based in 76 countries, they handle over 32 million clients throughout the world on a daily basis.
They provide services like retail banking, corporate and investment banking, asset management, portfolio management, insurance and other financial services.
While handling customer complaints, it is hard to track the status of the complaint. To automate this process, SocGen wants you to build a model that can automatically predict the complaint status (how the complaint was resolved) based on the complaint submitted by the consumer and other related meta-data.
The dataset consists of three files: train.csv, test.csv and sample_submission.csv.
Column | Description |
---|---|
Complaint-ID | Complaint Id |
Date received | Date on which the complaint was received |
Transaction-Type | Type of transaction involved |
Complaint-reason | Reason of the complaint |
Consumer-complaint-summary | Complaint filed by the consumer - Present in three languages : English, Spanish, French |
Company-response | Public response provided by the company (if any) |
Date-sent-to-company | Date on which the complaint was sent to the respective department |
Complaint-Status | Status of the complaint (Target Variable) |
Consumer-disputes | If the consumer raised any disputes |
Please submit the prediction as a .csv file in the format described below and in the sample submission file.
Complaint-ID | Complaint-Status |
---|---|
Te-1 | Closed with explanation |
Te-2 | Closed with explanation |
Te-3 | Closed with explanation |
Te-4 | Closed with non-monetary relief |
Te-5 | Closed with explanation |
The submissions will be evaluated on the f1 score with ‘weighted’ average.
70.87%