Finance, Loans & Insurance

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

Predictive Model for Prosper.com

Application Area: 

Project Details

Term: 

2010

Students: 

Natasha Sood, Nikhil Goenka, Salil Das, Sourabh Kukreja, Vikas Shah

University: 

ISB

Presentation: 

Report: 

Prosper is the world's largest peer-to-peer lending marketplace, with more than 1,020,000 members and over $213 million in funded loans. Borrowers’ list loan requests between $2,000 and $25,000 and individual lenders invest as little as $25 in each loan listing they select. It rates all the borrowers’ and using those ratings lenders decide if and how much they want to invest.

Which Bank Should you Buy?

Application Area: 

Project Details

Term: 

2007

Students: 

Eric Grant, Yasuo Mutsuura Xiaomin Shi, Omarr Tobias, Xiaoyu Zhang

University: 

UMD

Presentation: 

Report: 

The goal of this project is to help banks that intend to grow through acquisition determine which banks to purchase. This is done by building a model to explore operational characteristics of different banks. Analysis is based on a dataset of over 1000 branches of the top five banks in the DC/MD/VA area

Predicting Customer Churn For A Credit Card Company

Application Area: 

Project Details

Term: 

2005

Students: 

Cecily Rekart, Craig Lowenstein, Crystal Trainor, Ernest Chrappah, Maieka Hansard

University: 

UMD

Presentation: 

A major credit card company with travel offices in UK, France, Britain, and Germany is experiencing high rates of customer defection: 20%-30%. The project goal is to create a predictive model to predict which current customers are likely to leave.

Characterizing Pilgrim Bank's Loyal Customers

Application Area: 

Project Details

Term: 

2007

Students: 

Michael Isble, Karl Olson, Johan Rong, Ampun Janpengpen, Hyun Kim

University: 

UMD

Presentation: 

Report: 

Pilgrim Bank is a small retail bank in Texas. The goal of this project is to identify profiles of customers who would likely be retained, year over year, by Pilgrim Bank.

Understanding the determinants of mortgage loan approvals

Application Area: 

Project Details

Term: 

2003

Students: 

Chris Baden, Nima Baradar, Dawn Bui, Curtis Hardrick, Subramanian Hariharan

University: 

UMD

Presentation: 

A large U.S. mortgage company processes loan applications from borrowers, such that underwriting is done with software & rules determined by the company. The project goal is to help the company improve their decision making process regarding loan approval

Characterizing Buyers of Caravan Insurance

Application Area: 

Project Details

Term: 

2007

Students: 

Chih‐Hau Huang Masami Mabuchi, Muthita Songchitruksa, Nopakoon Visitrattakul

University: 

UMD

Presentation: 

Report: 

This report is intended to understand characteristics of a caravan insurance policy buyer. The
dataset consists of 9,822 customer records and includes socio‐demographic data of the area
where a customer lives and product ownership data of the customer. The aim of this profiling analysis
is to acquire managerial insights to create competitive strategies useful for making business decisions.

Profiling Student Loan Deferment

Application Area: 

Project Details

Term: 

2007

Students: 

Carlos E. Canales, April Humber, Irakli Nadareishvilli, Khalid Hasan, Soojung Jung

University: 

UMD

Presentation: 

Report: 

Recent studies have shown that the cost of higher education has been rapidly increasing over the past few decades. In some instances, students seeking financial aid may receive some federal funding; however, federal funded grants and loans may not be enough to cover all academic expenses. Students in need of additional funds often have no choice but to seek private student loans.

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