Numeraxial
Mitigating Risk amidst Uncertain Regulatory Environment

There’s a famous adage ‘With great power comes great responsibility’; when it comes to leveraging the power of financial data, organizations today have a responsibility to manage the sheer volume of sensitive data to meet the stringent regulations. In the wake of the 2008 financial collapse as well as subsequent scandals that have swayed the banking and the financial sector, Wall Street have found himself under greater scrutiny than ever before. Financial data being generated at unprecedented rates today critically challenges organizations to develop a data-centric view across their enterprise systems to address enterprise risks in a precise and efficient manner. “To protect companies portfolios and assets, the right selection and use of investment, risk and data analytics tools and expertise is critical to achieve companies performance goals,” says Jean. G. Ndoutoum, Principal, Numeraxial. This is where Numeraxial comes in with its robust risk analytics platform “RAP” that enables financial organizations to assess, measure, manage and mitigate investment risks while developing a holistic view of the compliance posture.

Numeraxial’s risk analytics platform is a user-friendly web-based SaaS application designed for managing portfolio risk of financial securities in synch from back-middle to front office. The framework provides real-time risk analysis across all asset classes, risk control, risk budgeting, counterparty credit risk, operational risk and liquidity risk. According to Mr. Ndoutoum, risk management is not only part of the regulatory compliance, but one of the principal part of the investment process for financial institutions, wealth and asset managements and banks business units, including trading desks, hedge funds and traders. Numeraxial’s risk analytics computes various risk metrics which can be calculated in real time or in customized defined batch schedule.

The firm’s intuitive platform can be integrated with the major platforms like Trade Station, Bloomberg Terminal, Reuter Terminal or MS Excel for desktop applications as APIs. This helps organizations achieve their business objectives by providing unmatched transparency into their portfolio’s performance, characteristics, risk and more. This type of integrated enterprise risk system empowers organizations for both buy-side and sell-side to use data from nearly any source, including market data providers, portfolio or loan accounting systems, trade capture systems, clearing systems, and more to meet all data compliance requirements.

The granularity, high-resolution of tail distribution and accuracy that we have in our risk accreditations is where we as a company make a real point of differentiation

In turn, the approach enables organizations to evaluate risk posture quickly and easily, and analyze key risks.

“In addition to our SaaS based platforms, we also provide sophisticated advisory and consulting services to family offices, small, medium and large firms on portfolio optimization, algorithmic trading and emerging and frontier market analysis,” says Mr. Ndoutoum. The firm’s trading algorithms library and standards-based trading models enable organizations to navigate the market easily and improve trade execution. Numeraxial also takes a standard approach of performing stress testing, which is a reasonable and prudent risk management exercise that banks of all sizes should integrate into their risk management and financial activities. This procedure of data granularity and outlook involves a far more comprehensive analysis and an automated process that cuts across business lines, showing higher performance across several key dimensions, including earnings strength, capital adequacy, and asset quality. The company also brings in the element of automation to improve efficiency, empowering customers to move from a typically regulatory-driven exercise to a routine business workflow that contributes an additional dimension to the banks’ risk appetite measurement.

“The granularity, high-resolution and accuracy that we have in our risk accreditations is where we as a company make a real point of differentiation,” asserts Ndoutoum. Past years, Numeraxial was completely focusing on machine learning in the context of financial risk management. Given the excitement around AI today, the question on ‘which works better for modeling credit risk’ is inevitable. The firm is planning to bring in AI-powered solutions to help organizations in optimizing their portfolio performance efficiently.