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:
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Objective definition
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Data collection and preprocessing
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Model selections
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Feature explanation
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Bias and variance trade-off
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Performance monitoring
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Risk and limitation communication
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Model output translation into business usage and strategy
Expertize in ...
Asset and Liability Management
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Interest rate term structure
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(Libor, OIS, and SOFR)
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Derivative pricing
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Prepayment
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Income simulation
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Pre-trade
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Risk measurement
Credit Risk Management
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Credit rating scorecard
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Probability of default
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Loss given default
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CECL
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Counter-party risk
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Collateral valuation & haircut
Stress Test
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Basel
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CCAR
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CMAST
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Stress testing
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Sensitivity testing
Capital Market
& Investment Strategies
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Security valuation
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Security lending
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Structured products
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Foreign exchange overlay
Analytics, Automation
& Machine Learning
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Automate quantitative processes
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Customize vendors’ models
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Build & validate ML models
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Detect ML bias and discrimination
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Market Basket Analysis
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Fraud Detection
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Anti-Money Laundry
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AI/ML bias prevention


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.