How strong are your RWA analytics capabilities


How strong are your RWA analytics capabilities?

Six simple questions to assess your RWA management framework

At the height of the financial crisis, managing and optimising risk-weighted assets (RWA) became a top priority for financial institutions. Ever since, performance adjusted for regulatory capital costs has become one of the key measures in steering a bank. While top management as well as investors and key stakeholders pay close attention to the consumption of capital in the bank, reporting is often geared towards meeting regulatory measures, and in many cases does not provide insights towards the risk-takers themselves. Meeting regulatory requirements is essential, however, truly understanding the relationships between income and capital usage allows banks to provide clarity on their profitability, and typically plays a central role when defining the overall strategy.

Active capital management requires analytics solutions that provide transparency on capital performance, explaining drivers behind variations to risk takers, and hence embedding RWA into the business.

RWA Analyzer article

Six simple questions to assess your RWA management framework

To bring your capital management to the next level, front office needs to be able to actively engage and understand RWA variations in real time. It is critically important for financial institutions to provide automated and structured bottom-up RWA analyses rather than performing occasional ad-hoc deep-dives. The following questions could help you determine your need for an RWA analytics solution…

The key to successful RWA analytics: a bottom-up approach

We believe that the core of any RWA analytics solution should be the quantification of risk driver contributions at the most granular level. For example, for credit risk the RWA change of each facility is to be broken down to driving factors including at a minimum PD, LGD, EAD, maturity, and FX contributions. Aggregating across the facility-level contributions then provides insights into trends and variations at divisional, business unit or sub-portfolio level, whilst allowing for deep-dives to more granular levels.

A number of potential use cases are:

  • Understanding the key drivers behind RWA variations
  • Data quality monitoring
  • Assessing changes in portfolio composition and monitoring against the capital plan
  • Tracking credit quality trends, and understanding the capital performance of new originations
  • Quantifying the impacts of changes in models

Deloitte RWA Analyzer

Deloitte has developed an “RWA Analyzer”, which helps banks generate actionable insights from their RWA data. The solution provides a single platform for multiple stakeholders, allowing users to perform multi-layered analyses and deep-dives down to the facility level. The analyses are presented in a visually consistent interface, and allows for automated reporting.

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