top of page

Why HQS?

We reveal the story behind your data -- to drive better business decisions by bridging the gap between it and your business processes and strategies.


​We create initiatives (and provide the quantitative tools) to answer senior management concerns, leverage unused data, and provide strategic solutions.


With our years of experience at major financial institutions, we deeply understand what problems quantitative processes can best solve and how to implement strategies to improve business effectiveness and efficiency.

We have proven success in translating regulatory guidance into the policy and designing, implementing, and maintaining model risk management framework for both the second (risk) and the third lines (audit).


Through hands-on management of over 100+ financial models used in risk management and investment, we have board perspectives and provide a holistic modeling process.

With HQS, you will now have access to the expertise and tools that the very largest financial institutions routinely use, and will be tailored to your institution's needs.


Meet the Founder

  • LinkedIn

Jenny Yu is a financial modeling executive with over 25 years of successful global experience in helping senior management make better business decisions using her expert analysis and recommendations. Having worked with major global financial institutions, Jenny has the unique ability to reveal the real story behind the data, bridge the gap between data/algorithms and business processes, and leverage this insight to provide strategic solutions for the stakeholders. Jenny concentrates her practice on model risk governance and financial modeling. Jenny previously served as the director of model risk management at the Federal Home Loan Bank Pittsburgh, where she was responsible for designing and implementing a model risk management framework from the ground up. She led the development of validation models and automated in-house benchmarking processes that have increased benchmarking coverage from less than 5% to full coverage on the balance sheet. She expanded the frequency from every three years to annually or quarterly, or as needed. The framework substantially improved business effectiveness, efficiency, transparency (understanding black boxes), and flexibility while reducing risk and cost. Prior to that, Jenny built the team from scratch and established the model risk audit program covering hundreds of models used in investment strategies and risk management at BNY Mellon. The framework included testing highly impacted models and communication with the recommendations and model risk/limitation to key stakeholders. Jenny was the 2013 global innovation winner for her idea of connecting the dots and balancing risk and return. Before BNY Mellon, Jenny had been a statistician for seven years at PNC. She developed and validated quantitative models used in credit risk management, investment analysis, and corporate strategy. Jenny has a master's degree with double majors in Quantitative Finance and Real Estate from the University of Wisconsin-Madison.

Team Experience and Success Stories

High interest rate modeling challenge

A bank usually uses a model to estimate the expected return when purchasing a fixed-income instrument. We identified the critical model assumptions and their impact on model output including the expected returns. The returns from different interest rate models diverge dramatically due to the rapid increase in interest rates. We communicated the finding with management and proposed solutions, such as considering a model risk cushion in the pre-trade guideline.

Award-winning idea to help increase profitability

Created an award-winning idea to help the business increase profitability. Most banks have estimated sophisticated risk measurement for regulatory requirement. We were able to help one bank to connect the dots, balance risk/cost and return/profit, improve business efficiency and profitability,  and won the 2013 BNY Mellon “Global Innovation Award".

True stories
behind data

Revealed the true stories behind data: what data can tell us and what it cannot. The bank did not have sufficient mortgage default data by itself, so it used nationwide data. The model from the national data could reasonably help the bank rank-order the riskiness of loans. But when the bank estimated credit loss CECL, it needed to tune the probability of default or loss given default to ensure they reflected bank's portfolios. There is a similar application for mortgage prepayments.

“In addition to her exceptional technical skills in modeling and quantitative analytics, I’m impressed by Jenny’s people skills. She has used her excellent communication and relationship-building abilities to build high-functioning teams and achieve outstanding results in three major financial institutions."

Shaheed Dil

Senior Managing Director


Advisory Team

Dedication. Expertise. Passion.

Our advisory team comprises seasoned financial experts who possess a wealth of experience in the industry. With a strong commitment to integrity and professionalism, we provide our clients with comprehensive and personalized financial solutions to help them achieve their long-term financial goals.

bottom of page