To better understand what sort of progress companies have made in using risk analytics, we recently completed a global study capturing and synthesizing the insights from more than 450 risk management analytics professionals in three industries to examine how they use risk analytics to tackle industry challenges and market volatility.
The study was intended to assess companies’ current level of risk analytics maturity—their quantitative and qualitative tools and techniques designed to estimate the impact and frequency of specific risks, as well as their ability to use analytics to drive business outcomes and proactively manage risks and rewards. For banks, an outcome-based approach would manifest itself, for example, in the manner in which analytics is embedded in outputs such as pricing and performance management.
Across the industries we studied, banking is predicting the greatest increase in risk analytics investments, with 73 percent of banking respondents foreseeing more than a 10 percent rise in expenditure. In terms of specific capabilities, risk analytics spending is expected to increase most in areas of data quality and sourcing, systems integration and modeling. Risk analytics leaders in banking also invest at higher levels than leaders in other industries.
Banks are hoping to address specific business needs through these investments in risk analytics. One important goal is to improve credit performance and reduce credit costs. The percentage of nonperforming loans is still unacceptably high for most banks, and risk analytics offers the promise of reducing the number of bad loans and lowering costs by reducing capital and letting go of overly risky customers in addition to non-profitable accounts. With advanced risk analytics capabilities, banks can, for example, identify characteristics and trends of non-performing loans and take proactive steps with the counterparties to address issues or even refinance or restructure deals before more serious problems arise.
Banks also are looking to better understand the risks in their portfolio. The high concentration of mortgage investments in their portfolios has banks looking to increase their ability to analyze how their portfolios line up with their risk framework and current risk tolerances.
Regulation is another important factor pushing banks toward greater investment in analytics capabilities to better manage areas such as liquidity positions, evolving liquidity measurement techniques, counterparty credit risk, credit valuation adjustments and integrating these into capital stress testing. Analytics show promise of helping banks anticipate some of the unintended consequences of regulation. For example, requirements of increased capital can result in restricted lending, or limits on proprietary trading levels may result in lower liquidity in key bond markets, neither of which is desirable. Scenario analysis and modeling can help banks deal more proactively with such consequences by helping to assess the impact of different circumstances and responses.
In addition to financial risk factors, banks are also incorporating into their risk models effects of various world events and external factors—environmental, political and financial. In an increasingly connected world, natural and industrial disasters, as well as political crises, have generated waves of impact on many regions of the world. These multiple interrelations create complexity that makes effective risk modeling difficult.
However, developing effective risk analytics isn’t as simple as buying software off the shelf. Our research indicated that banks face five key challenges in improving their risk analytics capabilities:
- Integrating analytics and insights across multiple data sources, linking non-integrated divisions and functions.
- Harvesting and managing data across the enterprise, due in part to ineffective data governance, poor data quality and insufficient data integrity.
- Lagging analytics technologies, with companies not yet reaping the full benefit of IT advancements.
- Lack of expertise and skilled resources, leading to delays and project overruns.
- Inability to communicate results and insights effectively.
Risk analytics is increasingly important for banks as they cope with a complex regulatory and competitive environment and our research indicates that banks are clearly committed to improving their analytics technologies, tools and teams. At the same time, banks face significant challenges —particularly in the areas of skills, data and integrated approaches—that need to be addressed before risk analytics can fulfill its promise. The effort is worthwhile however as those banks which address these challenges effectively can employ risk analytics, not only to identify and mitigate risk, but to provide competitive differentiation in this difficult environment.
