Savvy investment managers know the importance of taking downside protection during a bull market like the one that currently exists. However, despite the growing use of data and technology to manage and monitor market and credit risk more effectively, most financial services firms continue to lag in their abilities to use risk data and technology.
In fact, just 1 percent of banking and capital markets executives surveyed believe they have achieved “mastery” in these areas, according to Accenture’s 2013 Global Risk Management Study. Regulatory complexity that’s fueled by Dodd-Frank, Basel III, the Foreign Account Tax Compliance Act and other regulations is helping to make it increasingly difficult for investment professionals to manage market, credit, and liquidity risk effectively.
As investment managers look to identify and create opportunities for their clients, they’re also working more closely with clients to assess and communicate operational risk as part of evaluating each client’s investment objectives, according to Ernst & Young. Investment professionals can strengthen their risk management capabilities and improve financial performance by using predictive analytics and data visualization tools in a number of different ways.
For example, investment managers can strengthen investor confidence by using predictive analytics and data visualization techniques that can help clients see the potential risks and opportunities associated with different types of investment vehicles. And an investment manager who’s working with a patient investor could use predictive analytics and data visualization tools to demonstrate the potential risks and benefits of investing in, say, exchange-traded funds (ETFs) tied to commodities stocks such as gold and silver.
Data visualization tools can help investors see how investments in commodities stocks may be underperforming over the short-term but may be poised to outperform the market over the next several years.
Additionally, data visualization tools can help investment managers and individual investors see how such investments are currently performing, the top potential risks associated with a particular class of ETF funds (e.g., political volatility in specific regions such as Ukraine that can influence the price of gold stocks), as well as mapping longer-term performance expectations based on a comprehensive set of variables.
Investment managers can also use data visualization capabilities to gain a deeper understanding of credit risk associated with existing or potential investments made on behalf of clients.
Let’s say an investment manager has a client who’s interested in investing in municipal bonds. The investment manager can use predictive analytics and data visualization techniques to gain a comprehensive view of different variables that may lead to a rise in interest rates such as inflation or federal monetary policy and use these insights to help direct his client to the investment that best suits his risk appetite.
Arming investment managers and other investment professionals with the use of predictive analytics and data visualization tools can help drive optimal investment performance for their clients and business performance for their companies.
- We invite you to watch our complimentary, on-demand webcast: “Risk Management in Financial Services with EY.” In this webcast, Alexander Brash, Senior Manager at Ernst & Young LLP, will provide an overview of analytical challenges within the Operational Risk domain. This is an area of increasing regulatory concern, where advanced tools and techniques can help bring enterprise-wide data together to tell a comprehensive risk profile story, identify issues, and target areas for accelerated remediation.
- Subscribe to our blog to stay up to date on the latest insights and trends in big data, big data analytics and financial services.