Dear,
New regulation requesting central clearing of derivatives contracts and higher capital requirements, limited economic growth, and an overleveraged financial system are putting much pressure in collaterals management departments of financial institutions, for providing an efficient management of their instruments.
Unfortunately, collateral optimization is a discipline limitedly known for most of bank’s collateral managers.
Collateral optimization function has two main dimensions.
• Transactional management of the collateral rights.
• Utilization and distribution of the collateral rights.
In a future post we’ll look at the first dimension, but today we’ll focus in the efficient utilization and distribution of collateral rights.
The collateralization problem requires the allocation of a heterogeneous set of collateral pools to a number of assets with different values, maturities and risks estimations.
Solving the collateral optimization problem requires finding the optimal distribution of the collateral portions to the assets, which minimizes the bank’s capital requirements.
I’m sure you’re aware that in a real life example; solving the problem requires, evaluating a huge number of different combinations, of assets and collateral portions.
Traditionally, the process of allocating collateral portions against assets has been performed as a manual function. In this approach, collateral managers, choose the most suitable collateral portion, as collateral requirements are identified. They perform the function by trying to reduce maturity mismatches, estimating potential haircuts, etc.
Once the link has been established, it will not be dissolved till the collateral requirement disappears or the collateralization agreement expires.
While this could be considered an optimal allocation of the collateral rights in times of capital abundance, it’s far from being optimal in scenarios of capital scarcity.
The optimal solution requires considering, not just the new collateral rights and available portions, but the full inventory of the bank’s assets and collateral pools, and estimate if a more optimal distribution can be achieved, by redeploying the collaterals pool to the full inventory of assets.
Don’t forget that the reality is dynamic; and for instance, changes in the yield, rating of the counterparty, or the collateral value will impact the optimal solution of the collateral distribution problem.
As a consequence of these dynamically changing equation, collateral optimization requires continues rebalancing of the bank’s collateral allocation.
In order of running this process, the IT infrastructure of the bank requires a central repository of assets and collateral rights, which is at the core of the value proposition of the Integrated Financial and Risk Architecture of Bank Analyzer.
Currently SAP Bank Analyzer offers the Optimal Collateral Distribution functionality of the Basel III - Credit Risk module, which is insufficient for being considered a proper Collateral Optimization System for dynamically managed portfolios. But, we’re working in the integration of the necessary objects and results with external third-party systems, capable of running the optimization process.
In a previous post, we look at a practical example of the Bank Analyzer-Special Ledgers’ capabilities.
This is another good example; taking profit of the robust modeling of collateral data in the Source Data Layer, and the flexibility of storing the optimization and simulation results in the Special Ledgers of the Results Data Layer, we can build the central repository that the collateral optimization process requires.
Looking forward to read your opinions.
K. Regards,
Ferran.
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