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Financial Modeling

Quantitative modeling, automation, and machine learning (ML) are powerful tools for you and your institute to make better business decisions.


Our experience with over a hundred financial models in risk management and investment strategies can help you develop, validate, and audit your models.


Depending upon your unique needs, we can offer you such tools in a holistic process that can include:

  • Objective definition

  • Data collection and preprocessing

  • Model selections

  • Feature explanation 

  • Bias and variance trade-off

  • Performance monitoring

  • Risk and limitation communication

  • Model output translation into business usage and strategy

Expertize in ...

Asset and Liability Management

  • Interest rate term structure

  • (Libor, OIS, and SOFR)

  • Derivative pricing

  • Prepayment

  • Income simulation

  • Pre-trade

  • Risk measurement

Credit Risk Management

  • Credit rating scorecard

  • Probability of default

  • Loss given default

  • CECL

  • Counter-party risk

  • Collateral valuation & haircut 

Stress Test

  • Basel

  • CCAR


  • Stress testing 

  • Sensitivity testing

Capital Market
& Investment Strategies

  • Security valuation

  • Security lending

  • Structured products

  • Foreign exchange overlay

Analytics, Automation
& Machine Learning

  • Automate quantitative processes

  • Customize vendors’ models

  • Build & validate ML models 

  • Detect ML bias and discrimination

  • Market Basket Analysis

  • Fraud Detection

  • Anti-Money Laundry

  • AI/ML bias prevention

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Buck Gee

Former VP at Cisco & Executive Advisor

Buck Gee is an executive advisor to Ascend, a nonprofit Pan-Asian organization of business professionals. In the interview, she talks about not letting the fear of failure stop you.

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