Anticipation and Expectation: What today’s risk analytics are all about

In the post “What’s Trending in Investment Management,” we discussed the macro, business and technology drivers for modern market risk analytics systems. Because firms’ transactional systems operate in near real-time, their risk analytics systems need to operate on a similar timescale. To achieve this, they need one end-to-end platform, with integrated data and operations across the front, middle and back office.

Such a future-proof system, out of necessity, must have:
1. A scalable and robust suite of global risk optimization, simulation, reporting and analytic capabilities for broad, multi-asset class portfolios.
2. Common data sets and re-use of algorithmic engines for speed of analytic production. A modern risk management system must enable information transparency and data re-use across the firm. At the end of the day, it has to provide a common financial analytic language that facilitates communications among and between business teams.
3. A flexible and tailored library of analytic models customizable to meet firm needs and simulation capabilities for different risk scenarios. This information should be accessible in multiple formats, including a role-based user interface or via APIs integrated with in-house systems.
4. Anticipatory analytics to uncover insights and predict and recommend the next-best analytic action.
5. Because such a system requires significant yet elastic computing power, it must be natively cloud-based – built “for” the cloud, not just built “in” the cloud.

The benefits of such a solution include:
1. Near real-time speed in analytics driven by elastic processing horsepower
2. Cloud-based “security,” “partition-ability” and “global access” for all business areas across the firm
3. Data centers that are customized to firm’s business and data access needs
4. A solution architecture that works “on demand” to support the firm’s business the way it needs it, when it needs it
5. An open platform that can easily communicate with other systems

Some risk management analytic vendors have gone a different route. They have chosen to modify existing legacy systems and upgrade their IT infrastructure, build more data centers, and hire more people to cleanse data. If clients and regulators want more analytic power, these vendors will attempt to modify existing solutions to meet the new requirements.

There are two fundamental problems with this approach. First, legacy technology cannot handle computing requirements either in volume or complexity. Second, clients will resist paying more for services where costs scale with complexity. But beyond that, clients also demand greater computer power, as they want customizable and flexible analytics. This is why the role of technology in risk analytics is often misunderstood—even the biggest data center has finite capacity yet still has to scale.

In 2014, Axioma created a multi-asset class risk management solution, Axioma Risk, which is a unified enterprise-wide risk solution that spans the front, middle and back offices. Axioma Risk is cloud-based and that’s no accident.

We turned to both the cloud and algorithmic solutions for data cleansing. Many of the issues with data are routine and process-driven, and most of what data analysts do is repetitive. Because that’s the case, the latest algorithms can do the job. But it requires a lot of computing power to run these algorithms. The cloud provides on-demand scalability and elasticity at a much lower cost than traditional computing resources. It delivers the flexibility and customization our clients demand—better, faster and cheaper.

Selecting the right risk analytics system enables superior insights to drive investment performance and risk mitigation. Modern risk management scorecards, like the one below, provide an evaluation framework to determine your firm’s strengths and gaps in market risk management. This is the health check we recommend as you begin your evaluation process and move down the selection path.

Being able to implement state-of-the art investment decision support as well as anticipating and managing risk is fundamental for a firm’s competitiveness. From the ground up, Axioma Risk was designed to deliver the uncommon insight needed to take a pre-eminent position among your competitive set. I invite you to learn more about Axioma Risk.

Steve Mann

Steve Mann is Chief Marketing Officer at Axioma. Steve was most recently Chief Marketing Officer and a Collaborating Consultant at Adjuvi, a boutique management consultancy. Before that he was Chief Marketing Officer for LexisNexis in North America from 2011 to 2014, where he built a new marketing organization focused on enhancing inbound and outbound efforts to drive marketing effectiveness. 

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