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Financial data analytics play a significant role in effective capital allocation

Financial Services Writer

Financial data analytics enabling more effective capital management has become a critically important element in banking and financial services. A recent McKinsey & Company survey, which looked specifically at German banks, highlights capital issues facing all banks:

  • In recent years, banks have markedly increased capitalization, both from a regulatory and an economic standpoint. Further increases are likely.
  • Banks have improved their capital-management practices. For example, leading banks are reallocating capital more frequently than the traditional annual cycle in order to optimize returns.
  • Efficiency of capital deployment and balancing risk-taking against profit-seeking have taken a more prominent and pervasive role in banks. Capital management has evolved to include more functions in the bank than the finance function and traditional associated committees.

Capital is expensive, and management of bank capital is becoming increasingly complex. Appropriate metrics and analytical models are needed to properly measure and maximize returns on capital under these challenging conditions.

Balancing profit-seeking and risk-taking

Banking, by its very nature, is a risky business. Banks actively seek out opportunities to take on and manage risk to generate profits.

A primary example is lending money to a customer: The bank stands to earn interest on the loan, but there is risk of non-repayment. This simple example quickly becomes complicated when you consider that each potential borrower represents a unique level of repayment risk. Further, each loan product, such as an unsecured credit line versus an insured mortgage on an owner-occupied home, represents a different level of exposure to loan default.

Performance metrics that do not appropriately account for risk can result in the destruction of bank capital. In extreme cases, this can even lead to the destabilization of global financial markets, as seen in 2008. The question that needs answering, then, is how do banks determine which opportunities provide the best returns despite the risks?

Keeping the field level

It's vital to be able to compare the risks of capital investments in various business lines on an "apples to apples" basis. In other words, there should be a level playing field on which to assess returns on capital, recognizing that different business lines expose the bank to different levels of risk and may use different amounts of capital. Metrics that can be effective in measuring returns on a risk-adjusted basis include return on risk-adjusted capital (RORAC) and risk-adjusted return on capital (RAROC).

Optimizing capital allocation decisions with analytics

RAROC is a widely used metric that effectively provides a risk-adjusted measure of profitability. In a presentation on RAROC for the Global Association of Risk Professionals, Commercial Bank International Head of Enterprise Risk Management Yousef Padganeh describes RAROC as the after-tax, risk-adjusted expected return divided by economic capital. Economic capital, or capital for unexpected losses, is the sum of various capital elements such as market risk, credit risk, operational risk and strategic risk. It represents a probabilistic estimate of risk capital required for the bank to remain solvent. Conceptually, the RAROC model is straightforward. However, the individual data elements and calculations required for the RAROC calculation add many complex elements to the equation.

From a pricing perspective at the individual customer level, a sound objective is to ensure that riskier customers pay higher prices than less risky customers, all else being equal. However, as Padganeh points out, the reality is that this objective is not being achieved as commonly as one may expect. This tends to occur because pricing is more often determined at the product level rather than at the customer level on a risk-adjusted basis.

Contemporary financial data analytics tools can handily manage the required computations to allow for customer-level, risk-adjusted pricing. They can also aid with the broader RAROC calculations needed to compare performance of internal consumers of the bank's capital. It is in a bank's best interest to use these tools to ensure all decisions and performance measurements appropriately and effectively consider risk. Sign up for a free trial of IBM Planning Analytics today, and start optimizing your organization's performance.

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