Towards a CFO-CRO collaboration model: the real challenges for banks

By Andrea Partesotti | 24 May 2018

Bank internal functions related to risk (CRO) and finance (CFO) nowadays have become key actors for a huge amount of regulatory and management/market requirements.

Recent regulatory requirements, for instance, ask banks to develop comprehensive stress exercises which necessarily involve skills from risk management, planning and accounting departments. All results must be coherent and comparable, also if produced by different “owners”. FINREP and new accounting rules IFRS 9, for instance, are accounting topics that need to be considered in risk management processes… This means that a more effective collaboration between CFOs and CROs is required.

The new framework for risk and performance management has been the leit motiv of the Prometeia event ‘The new frontier of Integrated Balance Sheet Management’ in Istanbul, where international practitioners and regulators exchanged views on how far and how long this trend will take.

Data and data governance

The need to share “dimensions”, input and output data to guarantee metrics and processes’ coherence and comparability presumes a switch from dedicated datamarts to an integrated “data lake” (input) and “reporting room” (output): in other words, an integrated data model with no redundancies and a thin need for downstream reconciliation. Not an easy task: every process no more ‘owns’ its data, resulting of course in more organizational and infrastructural complexity to be dealt with.

State-of-the-art technology available today lowers the total cost of ownership of data governance projects and time to deliver. What is important to understand, though, is that the creation of common data lakes and warehouses is not simply an IT project: it involves process ownership (business functions must be involved) and workflows and requires a deep functional knowledge in order to ‘map’ data needs correctly and completely.

Analytics and calculation engines

The need to share analytics with capabilities to produce a huge amount of detailed information and aggregate them into significant KPIs, again, is only possible through a transition from specialized to shared simulation engines. Coherence is what you get, with no need of downstream reconciliation and comparable and easy (or easier) algorithms to interpret results. Flexibility in methodological evolution is what you lose, though, besides a more complex organizational structure requiring a strong discontinuity with current processes.

The real challenge here is the creation of a common methodological framework requires banks to look for a meeting point between the ‘bottom-up’ silo-based algorithms (typical of CRO calculation models) and the ‘top down’ but maybe too ‘simplistic’ models (typical for example of many CFO planning processes).


Pretty much the same applies for model development and calibration. Prometeia sees a growing need to share hypotheses, models and scenarios in order to avoid redundant metrics and inefficiencies, and to guarantee coherence and allow interpretation of more robust, calculated results.

As a matter of fact, risk and performance metrics are significantly influenced by behavioral assumptions and models. Sharing them is an unavoidable step to enable the interconnection between CRO and CFO frameworks, but requires a strict coordination both in estimation (hypotheses must be comprehensible and agreed by all the actors and downstream processes that use a model as an input must be shared before model selection and calibration) and in model change phases (all possible impacts must be managed).

Despite the not negligible costs, Prometeia’s experience in the EMEA integrated balance sheet management industry suggests that the benefits in terms of coherence and consistency will become more and more worthwhile for banking strategies.

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