Liquidity Risk

How to be certain to be liquid enough in all possible scenarios

Modelling and validation

Liquidity risk is firmly rooted in the banking sector since the balance sheet often has a mismatch in maturity between the assets and the liabilities. Additionally, the regulatory focus on liquidity is represented in the pillar I capital requirements through the Liquidity Coverage Ratio (LCR) and Net Stable Funding Ratio (NSFR) and in Basel Pillar II in the Internal Liquidity Adequacy Assessment Process (ILAAP).

Also, insurance companies and investment funds have inherent liquidity risk in their business models. An increasing focus on liquidity risk can be seen by their regulators (EIOPA and ESMA).

RiskQuest has experience in modeling of liquidity risk and validation of liquidity risk models and has shown to be able to apply the knowledge gained in banks in the liquidity risk modeling in insurance companies and investment funds.

Data collection

The modeling and stress testing of liquidity risk requires a thorough understanding of the balance sheet, to identify the products/assets and their potential maturity profiles and cash flows. This often requires a combination of behavioral modeling, and expert input.

By using RiskQuest's end-to-end liquidity risk expertise, the focus lies on collecting data from various sources, understanding the collected data and transforming and aggregating data such that it is usable for intended modelling purposes. The process revolves around backtracing from the end-product dataset to the raw data sources, ensuring quality on every step of the way. By using RiskQuest's in-depth knowledge of models, methodologies and data architecture, we provide tailor-made data solutions for every model.

Model implementation

Model implementation stands between a model and its actual usage. It is at this stage that we consider how data flows through the model and how other applications and people will interact with it. Yet don’t make the mistake to only start thinking about implementation at the very end of the modelling phase, or you may find yourself with a conceptually stunning model that cannot be implemented. At RiskQuest we understand the importance of sound implementation and work towards a model that is not only great by design, but also usable in day-to-day business.

Model governance

We help our clients to manage the risks related to the use of mathematical models in their day-to-day business. These risks refer to the chance of unintended consequences resulting from model development, inputs or outputs.

We achieve this by establishing Model governance which is a set of activities, policies and procedures that formalize model and model risk management activities for implementation. In particular model governance identifies a set of model stakeholders (e.g. model owner, model validator) and defines their roles within the process.

Over the past years, RiskQuest has contributed to the model governance policies for almost all of its clients being Dutch banks, insurers and pension funds.

Project management

For a successful liquidity modeling project, the communication between different departments is important. Since knowledge of the different assets on the balance sheet requires input from outside the model and risk departments. The translation between finance and risk is an important role of the project managers, as well as ensuring that requirements and different use cases of the model are fulfilled.


Validation Liquidity Risk model

Validation of liquidity models at a development bank

Hans Heintz