Objective
I am looking to leverage my background in finance along with my knowledge of Python and SQL to design and implement business solutions using predictive analytics, machine learning and artificial intelligence. With my skill set and background I believe I can provide an immediate and positive impact for a data driven organization.
When we are at the edge of our limits is where we learn and grow the most. Operating at the edge allows us to both learn and grow exponentially while pushing the boundaries of our capabilities. Over the last year I decided to push my limits and get out of my comfort zone as a financial analyst and develop a broader skill set that I can leverage by completing and earned certificates in data science and analytics through UCLA and online courses. Through the certificate programs and personal projects, I have a working knowledge of Python, R, and SQL. With my background in the financial services industry I have extensive experience with financial modeling in Excel and the Microsoft Office suite of products.
Experience
East West Bank, Senior Analyst
May 2021 - Present
• Aggregate and consolidate bank loan portfolio data sets using Microsoft Excel, Microsoft SQL Server, and Alteryx Designer.
• Developed new research methodology to identify data quality issues in bank loan portfolio data sets using SQL queries and Excel pivot tables.
• Research and resolve errors resulting data quality issues within the loan portfolio data sets. Interpret portfolio datasets characteristics to anticipate developing and existing risks through changes in loan population and characteristics between quarterly and monthly periods.
• Conduct analysis and loan portfolio impact research on changing macroeconomic conditions, portfolio data set characteristics changes, and financial forecast changes.
• Lead analyst during monthly and quarterly close allowance process. Mentored and developed junior analysts.
Pacific Asian Consortium in Employment, Portfolio Analyst / Loan Counselor
July 2020 - April 2021
• Reviewed and processed 42 PPP loan applications totaling $2.1MM in approved loans over a two-month period. Reviewed loan documentation and applications for consistency with SBA/PPP policies and procedures.
• Reviewed SBA Community Advantage loan files and completed credit addendums as necessary to ensure consistency with SBA policies and procedures. Worked with loan officers to complete loan modifications, deferral requests, and collateral analysis for existing borrowers within the loan portfolio.
• Collected collateral from borrowers in default, found equipment wholesalers and sold collateral to reduce loan losses on borrowers in default.
• Created a risk rating questionnaire tool using Microsoft Forms and Microsoft Excel for loan officers and business counselors to use to assess and monitor borrower risk during annual reviews, site visits, and pre-screens.
CIT Bank NA, Senior Corporate Banking Analyst
September 2014 - August 2018
• Under the direction of the lead Underwriters and Portfolio Manager, developed and updated financial models that assessed the impact of the borrower refinancing or assuming $1 million - $80 million in new debt under different economic scenarios for use in credit memos presented to senior bank leadership for credit decisions.
• Using financial models developed along with syndication decks I created the charts, tables, and graphics used showing borrower revenue forecasts, industry verticals and research, capitalization tables, and waterfall charts used in the credit memos for presentation.
• After OneWest Bank (OWB) was acquired by CIT, I was the lead analyst responsible for transferring the OWB database (ACBS) of historical and future reporting and financial covenants for the 80+ borrowers in the Corporate Banking Group into the CIT tracking system (ET&T).
• Responsible for on boarding customers and working with Enhanced Due Diligence Group to perform KYC validation on customers and borrower in adherence to bank and regulatory requirements.
• Lead Analyst for the Portfolio Monitoring Group during the quarterly ALLL process to determine bank reserves. Coordinated with a team of other analysts and three different departments within a three-week time period to create and maintain seven portfolio wide reports across hundreds of borrowers for presentation to senior bank leadership during quarterly portfolio monitoring meetings.
• As the primary analyst assigned to Corporate Banking and Power Project Finance Group portfolios, on a quarterly basis I entered information from financial statements for 150 different borrowers and counter parties into Moody’s financial spreading software.
• Created and updated the templates used for financial covenant compliance calculations of financial ratios in accordance with legal agreements for compliance worksheets and annual loan reviews for borrowers within the Corporate Banking Group and the Power Project Finance Group.
IMCA Capital Partners LLC, CREDIT ANALYST
February 2014 - Sep 2014
• Developed an in-house lending model for forecasting borrower cash flows and predicting future sources of repayment of funds lent while facilitating the approval of the first $500,000 in house funding transaction.
• Partnered with senior management and credit team to develop and create credit guidelines and procedures for leasing and cash advance transactions for amounts up to $500,000.
• Due diligence review of credit applications with recommendations provided on the financial strength of customers in various industries throughout all stages of the lending process while facilitating between internal sales teams (30 sales associates) and eight external brokers/lenders.
Bank of Hawaii, Credit Analyst
October 2011 - April 2013
• Assisted loan officers in underwriting and structuring credit facilities between $500,000 - $5,000,000 by developing cash flow models illustrating repayment capacity for bank clients operating in various industries (automotive dealerships, general and sub-contractors in construction industry, law firms, and quick service restaurants).
• Lead Analyst assigned to the Bank automotive dealership and worked with the senior relationship officer to model and structure leasehold mortgages ($300,000 - $800,000) and revolving lines of credit (+$2 million).
• Reviewed loan agreements and documents to support loan officers in determining appropriate covenants for credit facilities and monitoring for compliance through calculation and documentation on compliance review worksheets.
• Prepared credit amendment memorandums using and compiling various sources of information for credit officers.
Languages
Programming Languages
Experience
InterestS
Camping
Hiking
Rock Climbing
Backpacking
Education
UNiversity of HAwaii at Manoa
BACHELOR’S IN BUSINESS ADMINISTRATION
Major: Finance, Minor: Economics
Certificates
Moody’s ANalytics: Certificate in COmmercial Credit
UCLA EXTENSIOn: Certificate in DATA SCIENCE
DataCAMP: Data Science with Python
Contact
Email: simonhchen@gmail.com
Address: CULVER CITY, CA
Sample Data ANALYTICS Projects
Kaggle Lending Club
The complete loan data for all loans issued by Lending Club from 2007-2015 has been made available through Kaggle. The data includes loan status (Current, Late, Fully Paid, etc.) and payment information. Additional data features include credit scores, number of finance inquiries, address including zip codes, and state, and collections among others. The file is a matrix of about 890,000 observations and 75 variables.
Notebook Goals:
Using this data, I selected several features from the data set that were chosen using the traditional Five C’s of Credit (Character, Capacity, Cash Flow, Condition, and Collateral) framework.
Methodology
With the chosen features, three different Machine Learning models (Logistic Regression, Balanced Bagging Classifier, and Gradient Boosted Trees) were implemented to determine predicted probabilities of default and expected loss for a subset of the loan portfolio.
Results:
Loan Portfolio Testing Set Size: $12,649,356,475.00
Logistic Regression Modeled Expected Loss: $6,146,165,704.52
Balanced Bagging Classifier Modeled Expected Loss: $2,199,313,102.50
Gradient Boosted Trees Classifier Modeled Expected Loss: $2,695,019,391.91
Map of Coronavirus Cases in the United States by County as of 5/17/2020
New York Times Coronavirus Case Tracking
The New York Times is releasing a series of data files with cumulative counts of coronavirus cases in the United States, at the state and county level, over time.
Notebook Goals:
Using this data, I have created a SQLite Database using the Python Pandas and SQLAlchemy packages. The notebook contains Exploratory Data Analysis examples using raw SQL queries showing the growth of cases in Los Angeles country, Southern California (excluding Los Angeles), and a heat map of the United States showing the number of cases by county using Plotly
Kaggle Dunnhumby Dataset
This dataset hosted on Kaggle contains household level transactions over two years from a group of 2,500 households who are frequent shoppers at a retailer. It contains all of each household’s purchases, not just those from a limited number of categories.
Notebook Goals:
The notebook will look at households that the datasets provides transaction and demographic data for.
From there households are broken out by age groups and income group.
Plot Average Weekly Spending for all age and income groups.
Plot Average Weekly Spending for a specific demographic group: Age Group (15-34) and Income Group 50-74K.
Chart the spending patterns of two specific households during the active adveristing campaigns.
How do you define a successful campaign? Increase customer spending? Or increased customer visit?
