Changing regulations and new accounting standards are creating enormous challenges for financial organisations. SAS explores why, to successfully meet these new requirements, organisations need to rethink the way they operate
Banks’ risk and finance divisions typically operate separately, with limited interaction. But together, they can begin to identify how different business assumptions might affect their financials, and from there create an IT modernisation strategy that goes beyond effectively managing, for example, the new International Financial Reporting Standard 9 and Current Expected Credit Loss processes, to one that helps the organisation gain better insights into not only its risks but also its opportunities.
The banking and insurance environments are coloured by significant regulatory issues that cause business disruption. To meet all these requirements, chief financial officers (CFOs) and chief risk officers (CROs) – as those charged with budgeting and supervision – must now work together to deliver balance sheets and income statements that incorporate risk data. They must also satisfy shareholders with enterprise-wide capital, liquidity, and profit and loss (P&L) optimisation through budgeting and forecasting. However, these two roles tend to work from different perspectives. While the CFO is interested in presenting the financial results based on sophisticated analytics using the most appropriate models, the CRO is more concerned about the quality and the governance of these models rather than the results they will generate.
In this vein, the CFO has traditionally been the face of investor relations, while the CRO has often been described as a ‘chief worrier’, brought out when things go wrong. These roles must continue to remain separate, but by more closely aligning the skills of CFOs and CROs, financial institutions will further improve the relationship between the two, ensuring both of these key roles collaborate if and when things do go wrong.
The bottom line is that the forward-thinking, analytically oriented CRO will pursue – in co‑operation with the more risk-aware CFO – sophisticated and growing collaborations supporting the long-term transformation of risk management into an innovative source of value creation for the organisation.
Together these two groups demonstrate how different business assumptions might affect the company’s financials and create the best strategy for the organisation. Making finance more risk-aware will prevent risk analytics data becoming compartmentalised within risk, where it would be invisible to the finance department. More interconnected data and information sharing between risk and finance will allow finance departments to use regulatory data in key processes such as budgeting and stress-testing.
The impact of new analytics approaches, such as scenario-based analytics, with the right shared risk platform will enable CROs and CFOs to assess scenarios relevant to their firm’s business strategy. And, for the CRO, advanced analytics will help build better models more quickly to support scenario-based risk and finance analyses.
The need for seamless risk and finance integration
But the increasing demand for risk and finance integration also has implications for the underlying data and computational architecture. There is increased convergence between data and computing environments. Data architecture will increasingly need to coexist with computing components, providing dynamic aggregation and integration capabilities. This leads to a broader footprint and coverage of risk operations, with systems being increasingly open and exposed to third parties.
Innovation in risk has often come from firms with complex trading books. This may also be the case with risk and finance integration: these firms recognise the need to use analytical insights from a combined risk/finance dataset to stay ahead of the competition. They have established advanced approaches to managing individual risk types and understand that a silo mentality is limiting their understanding of a firm’s performance. They can also see where to make changes to improve efficiency and reduce costs.
The driver for consolidating risk systems is often the integration of regulatory charges and a multidimensional view of risk. Risk data takes centre stage when considering regulatory risk. New risk data architecture is needed to focus on the integration of time-series data, and finance and regulatory reporting is increasingly moving towards a model-free framework.
This has wide-ranging effects on, for example, data management and technology. Closer integration of risk and finance means financial institutions will be looking for an advanced framework that integrates, validates and transforms multiple data feeds from several sources. Regulations require them to implement a comprehensive data model that integrates the components of risk systems. This can potentially also capture the risk factor datasets. A consolidated P&L platform can bring together pricing, valuations and a framework for explaining and simulating the P&L. This single, consolidated platform will be focused on risk and performance analytics based on enterprise reference data.
Internal consolidation strategies will drive initiatives
This has knock-on effects for risk analytics, such as the use of Monte Carlo simulations – in banking, for example. A powerful engine is required to simulate upwards of 1,000 risk factors using correlated random numbers. It must also be seamlessly integrated into the risk management process. Other requirements include economic capital calculations for proprietary option books of interest rates, foreign exchange, precious metals and commodities, sensitivity analysis, scenario generation, exposure calculation, balance sheet optimisation, underwriting risk and behavioural analytics. These risk and finance analytics also require skilled resources and backtesting models, calibrating and providing extensive risk data analysis.
And what about disclosure, financial reporting and governance? Banks, as with all other financial institutions, will want a common reporting architecture for internal and regulatory requirements, following a factory approach and having readily customisable features. Governance is a key aspect of the development, support and maintenance of risk applications for all business areas. The starting point from a business perspective, however, usually remains credit risk.
Credit is the foundation of a wide variety of applications
Credit analytics covers a number of subtopics, including credit portfolio management, fraud analytics and credit trading. Credit risk is therefore part of:
- Application processes, with pricing, calculation of limits and credit portfolio management
- Transaction processing, with fraud analytics and real-time credit checks
- Enterprise risk, with risk aggregation and counterparty credit risk
- The finance department, through risk-aware accounting, product control, valuations and performance analytics.
What does this mean in practice? What does the changing face of credit look like? There are plenty of new institutions, such as financial technology – or ‘fintech’ – firms, entering the market space. This has led to increasing demand for real-time analytics and payments systems based on micro-transactions. This, in turn, creates demand for completely new types of analytics, leveraging new data.
Enabling better integration choices
It no longer makes sense to approach risk and finance individually. Closer integration of risk and finance creates the rocket fuel powering the transformation of credit risk and other risk categories.
There will of course be plenty of challenges in the emerging risk and finance landscape, along with a number of new opportunities. There is likely to be more risk-aware finance, more risk data used in finance and an expanded role for performance metrics, as well as the emergence of enterprise performance frameworks.
With risk and finance processes at the heart of every financial institution, the modernisation, consolidation and integration of these processes and their underlying technologies is both the enabler of and prerequisite for the required transformation. The industry accepts that there is no ‘silver bullet’ to achieve this transformation; however, SAS is working with leading innovative banks, insurers and change management partners to provide a game-changing approach to risk and finance platform integration.