Group08 Proposal

 Visualizing Future of Crowd Funding with Yu’e Bao

PROPOSAL

POSTER

APPLICATION

REPORT

40 Thieves Members

 ¥  Wong Yam Yip
 ¥  Wu Jinglong
 ¥  Song Chenxi

Abstract

Yu’e Bao (余额宝) is an investment product offered by Alipay (支付宝), a mobile and online payment platform established by China’s multinational conglomerate Alibaba Group. In June 2013, Alibaba Group launched Yu’e Bao, in collaboration with Tianhong Asset Management Co., Ltd., to form the first internet fund in China. Since then, Yu’e Bao has become the nation’s largest money market fund and, by Feb 2018, has US$251 billion under its management. In Chinese, Yu’e Bao represents “Leftover Treasure”. Alipay users can deposit their extra cash, for example, leftover from online shopping, into this investment product. The money will be invested via a money market fund with no minimum amount or exit charges, with interest paid on a daily basis. While major banks offer 0.35% annual interest on deposits, Yu’e Bao may offers user 6% interest with the convenience and freedom to deposit and withdraw anytime via Alipay mobile app. Thus, Yu’e Bao became extremely popular in China.

Using various data visualization methodologies, coupled with analysis of survival and time-series, this project aims to build an interactive tool on R Shiny framework, to unearth the underlying treasures of associations between Yu’e Bao’s user profile, behaviour, time and other financial factors.

Dataset

Source: Alibaba Cloud TIANCHI Competition: The Purchase and Redemption Forecasts - Challenge the Baseline. The dataset from this competition comprises of Yu'e Bao user’s profiles, transaction behaviour over time, and financial interest rates, in 4 CSV tables:

There are 4 table to this dataset:

• user_balance_table.csv - contains the cash flow time-series data of 28,041 Yu’e Bao users for 14 months from 1st Jul 2013 to 31st Aug 2014. Cash flow data includes account balances, different types of deposits, withdrawals, interest earned and categories of purchase if funds are used to make online purchases.

• user_profile_table.csv
• mfd_day_share_interest.csv
• mfd_bank_shibor.csv

The user_balance_table.csv contains.....

The user_profile_table.csv The mfd_day_share_interest.csv The mfd_bank_shibor.csv

[[Image:Metadata.png|frame|none|alt=Alt text|Full dataset description of the data variables can be found here]

Visualization and Analysis

The main goal of the TIANCHI competition is to train a model to predict future cash flow of Yu’e Bao users to aid Ant Financial Services Group, Alibaba Group’s affiliate company operating Alipay, in its business of processing the cash inflow and outflow of its users. In contrast, our group choose to provide a alternate view of the data by implementing the below analysis and visualizations:

Data Exploration and Visualization

In this module, we aim to provide an interactive data explorer to visualize the data and in different ways. We will employ different visualization techniques, eg. treemaps, heatmaps, corrplots, to demonstrate the interaction and relationships between different combination of categorial and interval variables.

Objective 2: Survival Analysis and Visualization

Performing Survival analysis....

Objective 3: Time-Series Clustering and Visualization

dtwclust time series cluster....

Libraries

The below R libraries will be considered for the project

• shiny
• shinydashboard
• shinyWidgets
• dashboardthemes
• tidyverse
• lubridate
• ggplot2
• plotly
• lattice
• xts
• treemap
• d3treeR
• survival
• ggfortify
• survminer
• dplyr
• TSclust
• dtwclust
• cluster