Sponsored statement: Moody's Analytics

Can ALM practices be improved?

Moodys Analytics logo

The Past: Traditionally, ALM has been focused solely on interest rate risk quantification.  

The Present: Now, regulators and industry participants are broaden-ing the scope of ALM to encompass the totality of financial risk management. And ALM’s mission is clear: maximise value creation and minimise value destruction.

The Future: To meet the needs of banks in the future, ALM has to make the transition from a back-office expense centre to an integrated front-office balance-sheet management function that helps to guide the business.

The transition is under way.

Ten strategies to next-generation ALM
Some of the challenges involved in implementing Basel III include:

1. Create a suitable risk management program. Your bank has an institution-specific risk appetite, book of business and a risk profile; therefore, it’s critical to identify the subset of risk management tools that best quantify risk given the complexity of your balance sheet and the goals of your organisation.

2. Be prospective. Don’t let your ALM risk management practice be about turning the crank and checking boxes. It’s not about restating the past, it’s about predicting the future. Create an enterprise view of risk, and robust and granular cash-flow-based stress-testing practices.

3. Build a valuation discipline that looks beyond earnings. Risk should be viewed with multiple tools that are based on different underlying assumptions.  A short-term view (earnings focus) should be complemented with the long-term view (market value).

4. Create an early warning system – you’ll get better outcomes. Creating a risk management framework that is responsive to evolving market dynamics can identify emerging risks.

5. Align treasury risk management functions with the lines of business. Aligning treasury functions with risk management processes across liquidity risk, capital management and FTP provides controls that disincentivises individual lines of business from taking excessive risk.

6. Use granular data to model cash flows with statistically parameterised behaviour models. The impact of consumer behaviour on cash flow matters, and non-linear information can be destroyed with too much aggregation.

7. Modelling the joint dynamics of credit and market risk. Jointly modelling these two risks will result in a more prospective view of balance-sheet capital and earnings exposures to risk.

8. Tie risk exposures to capital. By more clearly defining the impact of risk on capital and explaining the causes for loss events, banks can more clearly integrate decision-making into both tactical and strategic processes.

9. Tie compensation to risk-adjusted performance. Reduce the incentive to take excessive risks by clearly linking compensation to risk-adjusted performance.

10. Keep up with the latest developments in risk management. Remaining competitive is an ongoing process.

View the article in PDF format

You need to sign in to use this feature. If you don’t have a Risk.net account, please register for a trial.

Sign in
You are currently on corporate access.

To use this feature you will need an individual account. If you have one already please sign in.

Sign in.

Alternatively you can request an individual account here