According to Accenture’s Reinventing Operations in Asset Management report, risk management in the middle and back office is a top five concern among asset managers. While investment risk rightfully receives a great deal of asset managers’ attention, other risk management activities often take a backseat.
Emerging risks—particularly those relating to new technologies, regulation, cyber threats, changing investor sentiment, growing interest in complex portfolios and LIBOR retirement—are likely a large part of this. They are frequently dealt with in a reactive manner, with only a limited number of tools, data and automation practices in use.
The risk burden is certainly not going to lighten anytime soon. According to Accenture’s 2019 Global Risk Management Study for Capital Markets, the external risk environment in financial services is getting more and more complex, with new threats continually emerging. Many of these threats are interconnected with pre-existing risks, making them even more difficult to manage.
So, how can your organization become more proactive in anticipating and mitigating risk—moving toward forward-thinking, predictive safeguards?
Four keys to improved and proactive risk management for asset managers
01. Tap into the value of emerging technologies
Whether it’s conduct risk, cyber threats or financial crime, the accelerating rollout of new technologies like automation, artificial intelligence (AI), machine learning and analytics is reshaping asset management businesses’ risk profiles.
These new technologies could not only inherently decrease risk themselves, but can also be used within the risk management function to more intelligently monitor and mitigate risk across the organization. Indeed, our risk study respondents that have deployed machine learning feel much more confident that they have prepared their business for volatile future scenarios.
Asset managers should be closely monitoring the maturity curve and roadmap of innovative technologies to understand their applicability to specific areas across operational risk.
For example, smart analytical tools can help identify and prevent a range of threats. They can detect data anomalies that indicate financial crime and trawl networks to identify malware. But they are currently underused: Only 10 percent of capital markets businesses surveyed as part of our study are deploying machine learning, for instance, for risk management.
02. Relentlessly focus on measurement
What are your biggest operational risks and how would you know if you’re improving their mitigation? It is difficult to get the attention of executives when speaking only in general terms. Wherever possible, start an effort to quantify the downside risk as well as the upside opportunity. Hard numbers around risks also help asset managers better understand where to invest operationally, where to staff up and where to seek help.
Additionally, ensuring external partners and service providers are considered under your operational risk umbrella is important. If a partner is not adequately managing their risk, that could eventually become your issue. This should be factored into the way a firm’s risk is quantified.
As products and instruments become more complex, and as technology becomes more disruptive, having a documented, fact-based understanding of your risk areas could help more effectively deploy attention and capital. A “measurement mindset” is also vital to demonstrating the business value of operational risk management. Start with a baseline and then measure progress along the way.
03. Use data to enhance the scalability of your risk function
The siloed nature of the risk function at some asset management firms, combined with a lack of standard tools, can make it a difficult function to scale. In fact, when surveyed, asset managers indicated compliance, risk and regulatory requirements as their fourth most difficult function to scale. As asset management evolves further, the demands of this function are expected to only grow, making its scalability crucial in a highly cost-sensitive industry.
One of the underlying requirements is that an effective use of data is especially important when trying to scale risk management. According to our risk study, 63 percent of participants are urgently working to improve their ability to collect enterprise-wide data, and 66 percent are honing their ability to analyze it.
Why? Because data scales. It lends itself to automation and generates intelligent, actionable insights. The same data set can often be used for multiple purposes. Asset managers should therefore fully assess the data that is most valuable to the operational risk management function, make that data robust and more available, and provide the tools to fully analyze it. This can allow the risk management function to more effectively hone its focus, while assessing the impact of key risk areas.
04. Act swiftly when it comes to regulatory risk
Faster is usually better when it comes to understanding and managing regulatory risk. In our recent asset management report, “evolving regulation” was cited as the greatest risk-related concern in the industry. Other Accenture research has found that only 10 percent of risk executives are highly confident in managing the impacts of evolving regulation.
Whether it’s the General Data Protection Regulation (GDPR), uncleared margin rules (UMR) or the LIBOR retirement over the last few years, the earlier that regulations like these are on an asset manager’s radar, the easier compliance appears to be.
Our risk study pointed out that leading risk functions have deployed AI and machine learning-based technologies that scan speeches, news outlets and regulators’ websites for information that would indicate if a new regulation is being considered. These tools then track proposed regulation as it is passed into law. When it is, they scan, synthesize and de-duplicate relevant regulatory text before it is ingested into the organization, where it is analyzed in order to create actionable objectives.
While regulations can be complex, ambiguous, and disruptive, it is often the firms that understand their substance earliest that are eventually able to comply most effectively.
Creating a risk management function that supports innovation
How soon can your risk landscape be ready for the emerging threats ahead? The answer depends surely in part on how proactive you become. Our risk study found that, as businesses experiment with new digital technologies, risk managers do not feel ready for the follow on effects and are urgently seeking to improve their ability to spot and assess potential unintended consequences.
If the use of AI in the front office, distributed ledger in the middle office, or robotic process automation in the back office will be a driver of scale in the next five to 10 years, then risk functions should already be considering their impacts, including which processes, documentation or approvals should accompany the deployment of new tools.
Innovation is virtually impossible without a mature capability to manage potential risks. If risk management trails innovation, it could either slow the firm’s adoption of new technology or, potentially worse, cause a firm to become out of touch with the operating environment.
This is why better risk management has been identified by our thought leaders as a critical trend in 2020. For more Accenture insights on risk management, follow this link or contact me at ross.tremblay@accenture.com.
