Risk Management & Analytics: 4 Factors to Consider When Choosing an ALM Model

4 Factors to Consider When Choosing an ALM Model

As interest rates rise, financial institutions are revisiting whether an in-house asset liability management (ALM) model or a third-party (outsourced) ALM model is the best option for monitoring and assessing interest rate risk (IRR). Many variables and factors need to be considered when making such a critical decision. The following four factors will help institutions identify when it is best to implement an in-house model and when to outsource to a third-party vendor to ensure compliance with regulatory mandates associated with measuring and monitoring interest rate risk:

1. Balance Sheet Complexity and Risk Positions

Third-party ALM vendors have been successful in providing customized IRR analyses to address the differing liability management needs of financial institutions. However, an institution with extensive asset and liability categories, extensive structured financing products or unique lines of business is a better candidate for an in-house ALM model. An Institution with a less complex balance sheet composition may want to consider the third-party IRR analysis option.

Additionally, third-party ALM models are great options for institutions with more dependable baseline earnings and less overall risk exposure, related to capital, credit, liquidity or other elements of risk. When there are fewer risks and a greater earnings cushion, a third-party model may be a sound alternative.

2. Cost and Staffing Considerations

Developing, implementing and maintaining an in-house ALM model often requires a significant budget commitment. Outsourcing the IRR analysis to a third party changes fixed costs to variable costs, shared by its collective users. While costs are incurred for outsourcing, specifically for project management and oversight, considering whether the reduction in fixed costs outweighs the variable costs incurred will be an important criterion in the decision-making process.

Moreover, staff traditionally used for maintaining an in-house ALM model are valuable resources that can be re-allocated to other assignments that require institution-specific or unique and nuanced analysis.

3. Regulatory Mandate and Institution Culture

Regulatory mandates for IRR analysis are consistent across institutions including: rate shocks, non-parallel yield curve moves and basis risk analyses. Third-party vendors can perform a standard set of IRR scenarios that can provide necessary assessments to meet both business and regulatory needs.

An institution’s culture is another consideration when choosing an internal or third-party model. If an organization’s internal stakeholders rely heavily on model outputs for critical financial and business strategy decisions, an internal model may be more appropriate. Your internal model team must have extensive knowledge about the assumptions and methods used in the analysis. However, if the ALM is primarily addressing a regulatory mandate, a third-party solution may be adequate.

4. Model Governance Requirements

Both the third-party ALM model and the in-house model require governance, but the scope of that governance varies. An in-house model requires more extensive governance because it involves policies, documentation, user controls and ongoing model-monitoring programs. An outsourced model still requires documentation based on assumptions and processes for providing data and reviewing results, but it is more limited. However, keep in mind, good governance, under either model, requires outcomes analysis to prove its dependency and accuracy. If the outsourced solution is the answer, a back test of model results will still need to be performed to assure the institution that the model can accurately predict outcomes.


The four factors stated will enable financial institutions to ask the right questions related to in-house vs. outsourced ALM model use. However, there are many more idiosyncrasies to consider beyond these four factors. A successful ALM model (in-house or outsourced) will need to define cash flow characteristics from the underlying data, apply the right assumptions, and accurately forecast IRR outcomes.

The Financial Managers Society (FMS) will soon publish its seventh edition of “Choosing the Right ALM Modeling Solution,” revised and edited by Christine N. Mills, Managing Director at MountainView Financial Solutions, a Situs Company. This report will provide detailed information on how to choose the right in-house or outsourced ALM model.

If you need help validating your ALM model, please email Andrew.phillips@situs.com

Banks Shunning Mortgages? Citizens’ Deal Proves Otherwise

On its face, Citizens Financial Group’s decision to buy a large mortgage lender seems to be a case of swimming against the tide.

Several banks have recently dialed down, or outright exited, large-scale mortgage lending as rising interest rates put a damper on refinancing activity.

A closer look shows the logic behind the $154 billion-asset company’s deal for Franklin American Mortgage. For starters, the $511 million acquisition, which is expected to close in the third quarter, will dramatically boost Citizens’ fee income at a time when all banks are struggling with weak loan demand.

And Franklin’s specialty — servicing homeowners’ monthly loan payments — is the part of the mortgage industry that typically performs well in a rising-rate environment.

Read more: American Banker

Tax Reform Could Prove a ‘Double-Edged Sword’ for Banking Industry, Analysts Say

U.S. bank profits are projected to reach pre-crisis levels but Current Expected Credit Loss (CECL) could slow overall balance sheet growth, according to a new report from S&P Global Market Intelligence that also questions the benefits of newly enacted tax reforms.

S&P Global Market Intelligence sees improving profitability for U.S. banks, including smaller community banking institutions, at least in the near term, according to its latest bank market reports.

Banks should experience additional expansion in net interest margins even as funding pressures and heightened competition stemming from tax reform mitigate the benefits of higher interest rates. That expansion, coupled with a lower corporate tax rate, should allow profitability to nearly reach pre-crisis levels, before credit quality sours and serves as a headwind to earnings.

As credit quality slips, banks will begin complying with a new reserve methodology, dubbed CECL, which could slow balance sheet growth as some institutions raise rates on loans, while others look to rebuild their capital bases.

Read more: ABL Advisor

Bitcoin Is the Market’s New Fear Gauge, Investor Says

The answers to which way the market will move next may lie in bitcoin, said Brian Stutland of Equity Armor Investments.

“Bitcoin is sort of becoming the new VIX, in sort of getting ahead of credit risk in the banking industry,” Stutland said on “Fast Money” on last week.

The CBOE Volatility Index, or VIX, is a long-held measure of volatility and fear in the marketplace illustrated by way of S&P 500 stock options prices. The index is sometimes referred to as the market’s “fear gauge.” But Stutland told CNBC that bitcoin is just as good of an indicator.

“There is huge correlation right now between VIX and bitcoin 30 days ago, 30 trading days ago, that is starting to measure out credit risk in the market,” Stutland said. “That’s what cryptocurrency is becoming. It’s becoming a way to sort of de-risk yourself from credit risk in the banking industry.”

Read more: CNBC

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