Discover Our Services

We provide a wide range of services that can help meet the needs of our clients. Whether the need is standardized or bespoke we have solutions or resources to help.

Quant On Demand

Providing access to quants on an as-needed basis.

  • Development and implementation of customized quantitative models for risk management, trading, and investment analysis.

  • Development and deployment of big data analysis and machine learning solutions.

  • Providing consulting services related to governance, risk, and compliance, including FRTB, CCAR and LIBOR transition.

  • Designing and development of bespoke risk management strategies and derivative pricing for various asset classes.

Quant On Demand

Quantitative Modelling

Creation of mathematical or statistical models to analyze and understand complex systems.

  • Development of quantitative models to meet specific needs of our clients using advanced statistical techniques, machine learning algorithms, and other analytical tools.

  • Model implementation, ensuring model integration with other systems and processes and effectiveness in management of risk, strategies, and investment decisions.

Quantitative Modelling

Model Risk Management

Identifying, assessing, and mitigating the risks associated with using quantitative models.

  • Rigorous testing, validation, and documentation of quantitative models to ensure their accuracy, reliability, and effectiveness. Back-testing historical data, stress-testing models under different scenarios, and other techniques to ensure that models are robust and reliable.

  • Development of comprehensive documentation for quantitative models, including model assumptions, inputs, outputs, and limitations.

  • Establishing effective model monitoring processes to ensure continuous model performance analysis.

  • Enhancement and improvement of quantitative models, incorporating new data and analytical techniques.

Model Risk Management

Big Data & Machine Learning

Analyzing and extracting insights from large and complex data sets.

  • Offering a range of machine learning algorithms that our clients can use to analyze financial data and gain insights.

  • Delivering machine learning based risk management services that allow our clients to identify, measure, report and manage financial risks.

  • Using big data analytics to help clients identify patterns and trends in large amounts of financial data leading to more informed business decisions.

  • Analyzing data, identifying trends, and making predictions and forecasts.

  • Empowering our clients with tools to visualize data effectively.

Big Data & Machine Learning

Case Studies

Take some time to discover our work and see for yourself the passion and expertise we bring to every project.

Client #1

International Bank

Fixed Income Risk Management

Pre-payment Models

Following its acquisition of independent fixed-income broker dealer, the Global Systemically Important Financial Institution (referred to as “the Bank”) necessitated the integration of the broker dealer’s third-party non-agency mortgage prepayment model.

Client #2

Utility Company

Energy and Natural Resources

Power Purchase Agreements

The utility company had the imperative to accurately assess and proactively manage the valuation and risks associated with their renewable Power Purchase Agreements (PPAs), encompassing both fixed-shape and ‘as generated.”

Client #3

Credit Rating Agency

Model Risk Management

CMBS Models

A prominent credit rating agency sought assistance in validating CMBS models.

Client #4

International Bank

Quantitative Risk Management


International Bank required a comprehensive Risk Factor Inventory and FRTB Implementation.

Client #5

Asset management firm

Model Risk Management

Algo Trading Models

Asset Management necessitated the validation of two distinct algo-trading models: a dark pool model and an advanced model utilizing extreme gradient boosted trees.

Client #6

Utility Company

Market Risk Management

Energy Risk Analytics

Utility company wanted to enhance its Market Risk Management capabilities due to changes of their commercial strategy.

Client #7

International Bank

Quantitative Risk Management

Market Risk Analytics

Bank’s Market Risk Management Department needed a simulation engine that would allow to model correlated fat-tailed random variables.

Client #8

International Bank

Quantitative Risk Management

Credit Risk Analytics

Bank’s Credit Risk Management Department wanted to assess credit risk rating and default rating migration and mark-to-market risks in various lending/trading books.