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Prometeia wins the RiskTech100® 2019 Award for Capital Optimization

An ever harder task for banks, requiring a more and more integrated approach to balance sheet risk management: where risk management meets finance and strategic planning

 

Effective capital optimization is essential for any firm to generate the highest possible return on capital given the stringent bindings of regulation. This process represents an ever harder challenge for banks, requiring a more and more integrated approach to balance sheet management and a strong collaboration model between risk management, finance and strategic planning.

Prometeia has long invested in such integrated solutions, both technologically and methodologically, and recently received the RiskTech100® Capital Optimization award by Chartis.

We discussed these issues with Andrea Partesotti, Prometeia’s director and head of the Enterprise Risk Management Area.

What do you think made Prometeia stand out in this category?  
In the current regulatory environment, the optimization of capital resources is becoming a critical factor to compete in the financial services industry.

From one side, the prudential regulation requires increasing capital buffer to banking institutions, in order to survive under the most severe stress scenarios. From another side, shareholders demands higher and stable returns on their equity investments, stressing the importance of ensuring an adequate risk-adjusted profitability in the long-run.

Optimizing capital means achieving two goals at the same time: maximizing the risk-adjusted profitability of the bank under the constraints set by a stringent capital regulation. Prometeia has always been a leading provider in Balance Sheet Management solutions: capital optimization is a key component of the integrated balance sheet management process.
 
What new launches or product changes could have had an impact on this win? 
In 2017 and 2018 Prometeia has invested considerably in the development of a new generation of Balance Sheet Management solutions, to support the decision-making processes and the regulatory compliance of CRO and CFO departments. 

In this direction, we have launched three major releases of our ERMAS platform, addressing namely:

  • the regulatory requirements set by the latest EU Stress Testing exercise, with particular focus on Interest Margin, RWAs and Provisions;
  • integrated simulation tools for Planning & Control departments, designed to support ALM, Capital and Fund Planning in one consistent technological framework;
  • advanced models for stochastic projections of KPIs and KRIs, in particular to digitalize complex processes such as Reverse Stress Testing and the Recovery & Resolution Planning.

All these developments are designed to ensure a proper allocation of capital resources and maximize the risk-adjusted profitability of banks.

What are the key market trends that are shaping this space? 
Capital optimization has always been a cross-departmental issue: capital requirements are typically monitored by CRO functions, capital allocation is generally led by finance & control departments, capital management is traditionally seen as a Treasury officer’s responsibility. 

Despite this common ground, we rarely see banking groups relying on a unique methodological and technological framework to support capital optimization needs. Nevertheless, we believe that an increasing number of financial institutions will move towards a new model of collaboration between Risk and Finance functions, in which capital optimization and other Balance Sheet Management processes will be managed jointly, leveraging on the same data and analytical tools.
 
What is next for Prometeia in this field now? 
In Prometeia we still see a big potential in evolving methodological and technological solutions for the integrated balance sheet management. We believe that a big gap shall be filled not just in terms of IT architectures but also in the cultural approach to risk-adjusted performance. A systematic capital optimization and active Balance Sheet Management are becoming a ‘must’, not just academic exercises as they were considered only ten years ago. 

In this line, we think that new advanced technologies like Big Data and High Performance Computing are putting the premises to dramatically increase the sophistication of the analysis and make these models available in the ordinary decision-making processes.