Finance, Loans & Insurance

Predicting Customer Purchase to Improve Bank Marketing Effectiveness

Application Area: 

Project Details

Term: 

Fall 2017

Students: 

Sandy Wu, Andy Hsu, Wei-Zhu Chen, Samantha Chien

University: 

NTHU

Presentation: 

Report: 

A bank marketing dataset from UCI Machine Learning Repository was adopted for this project (https://archive.ics.uci.edu/ml/datasets/bank+marketing). The dataset is about a Portuguese banking institution with records of direct marketing campaign phone calls, and the final outcomes indicating whether success campaigns are also included in a binary format (yes/no). A success campaign indicates the customer has finally subscribed a term deposit at the end of the campaign.

De-anonymization of Insurance Applicants' Sensitive Information

Application Area: 

Project Details

Term: 

Fall 2017

Students: 

Rosalie Dolor, Maxim Castañeda, Jay Lee

University: 

NTHU

Presentation: 

Report: 

Over the years, as the life insurance industry has expanded, the need for clear regulatory laws has grown as well, originating entities like the National Association of Insurance Commissioners (NAIC). Through the NAIC, insurance regulators establish national standards and best practices, conduct peer reviews and coordinate their regulatory oversight to better protect the interests of consumers while ensuring a strong, viable insurance marketplace.

Preparing for e-invoice donation drops in Taiwan cities

Application Area: 

Project Details

Term: 

Fall 2016

Students: 

Neil Huang, Ian Lin, Leo Lee, Martin Hsia

University: 

NTHU

Presentation: 

Report: 

1. Business Problem
In 2017, a new regulation about invoice donation was issued. All the invoices issued will be
transformed into e-invoice instead of paper invoice. However, this regulation will cause great
donation drops, and this is a problem for central and local government in Taiwan.
This project provide forecast of the next 2 month e-invoice donation amount to central
government. With this forecast, central government could know which city or county would
confront a donation amount drop in the future and ask local government to take actions.

Forecasting Top 3 Cancer Rate in Each Gender for New Insurance Product Design

Application Area: 

Project Details

Term: 

Fall 2016

Students: 

Kuan-Yu Chen, I-Chun Chao, Edward Song, Yi-Wei Lai, Yen-Ju Tseng

University: 

NTHU

Presentation: 

Report: 

There are some reasons to work on this topic. Medicare doesn’t compensate that much because of the strict compensation policy. Due to the policy constraint, medical report for compensation is required. The size of tumor cannot really show the severity which is contrary to the policies nowadays. And the most expensive treatment, target therapy content, will not be paid. That’s why the cancer insurance products come out – try to complement the gap that Medicate doesn’t cover.

Forecasting Unemployment rates in the UK and EU

Application Area: 

Project Details

Term: 

2017

Students: 

Rajesh Manivannan, Kartick B Muthiah, Debayan Das, Devesh Kumar, Chirag Bhardwa, Sreeharsha Konga

University: 

ISB

Presentation: 

Report: 

Problem Description:
Unemployment benefits are a huge cost to governments and are highly dependent on
projected unemployment rate for the country. Unemployment benefits are social welfare
payments to unemployed individuals. The definition of unemployed individual varies from
among different governments. Each year Governments allocate a certain percentage of
their financial outlay to meet these requirements.

Forecasting industrial production growth for the BRICS nation

Application Area: 

Project Details

Term: 

2017

Students: 

Kaushal Narayan, Nigib Sharma, Divya Upendra, Sthitapragnya Kalita, Rahul Singh, Anshul Khandelwal

University: 

ISB

Presentation: 

Report: 

THE KEY QUESTION: How should the BRICS bank allocate its short-term (around 2 years) loanportfolio
to the 5 constituent countries?
DETAILS – The newly formed BRICS bank, now known as the New Development Bank, has recently
issued its first loan in April 2016 to Brazil, China, India, and South Africa in the renewables energy
space. As an ongoing engagement, the bank has reached out to our team of consultants to help decide
what portion of its loan portfolio it should allocate to each country. Since the bank’s loans are primarily in

Predicting Companies Delisting to Improve Mutual Fund Performance

Application Area: 

Project Details

Term: 

Fall 2014

Students: 

Ta-Wei Huang, Eugene Yang, Po-Wei Huang

University: 

NTHU

Presentation: 

Report: 

Stock is removed from an exchange because the company for which the stock is issued, whether voluntarily or involuntarily, is not in compliance with the listing requirements of the exchange. Companies that are delisted are not necessarily bankrupt, but most of bankrupt company will be finally delisted from the exchange. To earn extra high returns on the stock market, mutual fund managers in Taiwan sometimes invest in high risk companies that might to be delisted in one year.

Predicting First Day Returns for Japanese IPOs

Application Area: 

Project Details

Term: 

2011

Students: 

Vivek Kumar, Gaurav Jain, Mahadar Rohan Anil, Tejas Vikram Pahlajani

University: 

ISB

Presentation: 

Report: 

The goal of this project is to predict the First Day returns on Japanese IPOs (based on first day closing price), using public information available prior to the offer. Such a predictive model could be used to predict whether a new IPO coming on the market will make first day gains or not, and use the result to decide whether to invest in the IPO.

Predicting Changes in Quarterly Corporate Earnings Using Economic Indicators

Application Area: 

Project Details

Term: 

2011

Students: 

Prashant Kumar Bothra, Piyush Mathur, Chandrakanth Vasudev, Harmanjit Singh

University: 

ISB

Presentation: 

Report: 

The purpose of this project is to check the validity and potentially strengthen an existing theory of business forecasting developed by Joseph H. Ellis (former research analyst at Goldman Sachs).

Prosper.com: Improving Lending Through Modeling Defaults

Application Area: 

Project Details

Term: 

2010

Students: 

Lindsey Cohen, Ross Dodd, Wells Person, Amy Rzepka

University: 

UMD

Presentation: 

Report: 

Prosper.com is an online peer-to-peer lending system for borrowing money and investing in loans
through an open and transparent auction model. Prosper.com borrowers create credit profiles
containing information lenders can review before determining whether to invest or not in a
borrower. Even with this information, one challenge Prosper.com lenders face is being able to

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