Risk-Based Analysis of Financial Reserves
April 26, 2016 – Charlie Francis
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Reserves give governments flexibility. Most finance professionals agree they’re essential buffers, but managing reserves and picking the proper amount are not easy tasks.
In 2013, the Government Finance Review published a case study on Colorado Springs, CO by Shane Kavanaugh called “A Risk-Based Analysis of General Fund Reserve Requirements.” Inspired by this study, I decided to conduct and document a similar analysis for my city because our Council debated the appropriate level of reserves during the Great Recession.
Kavanaugh described how reserves are a form of risk mitigation and continued:
“The main question is how much money to maintain in reserve – how much is enough, and when does it become too much? (Emphasis added) This can be a sensitive question, since money held in reserve is money taken from constituents, and it can be argued that excessive reserves should be returned to citizens in the form of lower taxes.”
My perspective on reserves changed to emphasize risk mitigation. Previously, I viewed reserves as a pot of money accumulated on the basis of a combination of best practices recommended by standard-setting bodies like GFOA and Standard & Poor’s; with comparisons to benchmarked cities.
But no matter my perspective on reserves, I needed to start by engaging Council and others.
A Prerequisite to Analysis: Getting Everyone on the Same Page
The above passage and the occasionally nasty Council debates convinced me it was critical to keep everyone on the same page about what the facts were as I conducted the analysis and used it to inform policy recommendations.
Luckily our city had already implemented OpenGov to communicate financial information instantly, accurately, and intuitively. This helped focus discussions on policy rather than on line-items, while also reducing exaggerations; because data was at our officials’ and citizens’ fingertips via smartphones, tablets, and desktops. So now that everyone was on the same page, I felt more comfortable initiating the reserve analysis and began my work.
Conducting the Reserve Analysis
Step 1: Calculate the right level of reserves
I used GFOA’s recommended “Triple-A” Approach to calculate the reserves I needed to hedge against uncertainty:
- Accept. First, we accepted that we are subject to uncertainty, including events that we haven’t even imagined.
- Assess. Next, we assessed the potential impact of the uncertainty. Historical reference cases were a useful baseline.
- Augment. The range of uncertainty we really face will almost always be greater than we assessed it to be, so we augmented that range. Historical reference cases provide a baseline, but that baseline may not be adequate to account for all future possibilities.
This framework helped me group my risks in two buckets: primary risk factors and secondary risk factors. The primary risk factors were:
- Revenue volatility during economic fluctuations
- Infrastructure failure risk due to deferred maintenance
- Catastrophic events
And the secondary risk factors were:
- Lawsuits and litigation
Using the case study as a template, I conducted the risk analysis that resulted in recommended reserve levels. I show the risk factor calculations for revenue volatility below, and you can see others at the end of this post:
Primary Risk Factor – Revenue Volatility
|Revenue Source||Exposure to Risk||Augmentation Factor||Targeted Reserve|
|Sales Tax||$400,000 annually – 2 years||1.5||$1,200,000|
|Transient Occupancy Tax||$250,000 annually – 2 years||1.5||$750,000|
|Parking Revenues||$200,000 annually – 2 years||1.5||$600,000|
|Property Tax||$250,000 over 24 months||1.5||$375,000|
Step 2: Segment reserves into different categories to improve transparency
We segmented reserves into different categories to make the reserves’ purpose more transparent. For example, a reserve for “emergencies” and a reserve for “economic uncertainty” clarified the purpose of the reserves better than one all-encompassing reserve.
Budgetary Uncertainty Reserve:
- $3,250,000 – Revenue Uncertainty
- $1,200,000 – Sales Tax Uncertainty
- $750,000 – Transient Occupancy Tax Uncertainty
- $600,000 – Parking revenue uncertainty
- $375,000 – Property Tax Uncertainty
- $325,000 – Other Revenue Uncertainty
- $800,000 – Pension payment uncertainty
- $300,000 – OPEB payment uncertainty
$4,350,000, or approximately 35 percent of General Fund revenues, formed the Budgetary Uncertainty Reserve.
- $1,000,000 – Critical infrastructure failure
- $1,000,000 – Extreme events
- $500,000 – Expenditure spikes from lawsuits
- $300,000 SIR – Workers Compensation (2 events @ $150K per event)
- $100,000 SIR – General Liability (2 events @ $50K per event)
- $100,000 SIR – Uninsured events (2 events @ $50K per event)
$2,500,000 or approximately 20 percent of General Fund revenues, formed the Emergency Reserve.
I found that the risk-based assessed reserve levels should total $6.85 million in liquid assets. While current reserves were $9.4 million – exceeding the reserve threshold by $2.55 million; only $2.5 million were liquid.
The city embarked on a plan to liquidate the General Fund’s interfund loans and then use the excess reserves to fund pension and OPEB irrevocable trust funds to offset GASB 68 and GASB 75 liabilities respectively; and to annually monitor and adjust reserves to this policy through the budget adoption process.
Informed public policy development, with a risk mitigation methodology for determining reserve requirements, protects the interests of the silent, yet very content, majority of citizens who respect professional financial management.
Appendix: Additional Calculations
Primary Risk Factor – Infrastructure
|Consequence of Total Failure
|% of Total Failure per Failure
|Probability of Failure
(b) x (c) x (d)
|Seawalls and Bulkheads
Net book value
Replacement value (est)
Net book value
Replacement value (est)
Primary Risk Factor – Extreme Events
|Consequence of Incident
|Probability of Incident
(b) x (c
|Earthquake||$2,000,000 Emergency Response
$2,000,000 Annual Loss of Property Tax
|Wildfire||$500,000 Emergency Response
$500,000 Annual Loss of Property Tax
|Landslide||$500,000 Emergency Response
$500,000 Annual Loss of Property Tax
|Flood||$250,000 Emergency Response
$250,000 Annual Loss of Property Tax
Secondary Risk Factor – Expenditure Volatility
|Expenditure Source||Exposure to Risk||Augmentation Factor||Targeted Reserve|
|Worker’s Compensation Incidents||$ 150,000||2||$300,000|
|General Liability Incidents||$ 50,000||2||$100,000|
|Pension Employer Contributions||$1,600,000||50%||$800,000|
|Retiree Health Care||$ 150,000||2||$300,000|
Charlie Francis is a municipal finance expert. He has more than forty years of local government financial management experience in both the public and private sector, including twenty years of experience as a Chief Financial Officer. Most recently, he served as the Director of Administrative Services and Treasurer for the City of Sausalito where he earned the unofficial title of “OpenGov super user”. He has also served as a finance manager for the Town of Colma, CA and as CFO and acting City Manager for the Cities of Indian Wells, CA and Tracy, CA.
Questions or comments? Email Charlie at firstname.lastname@example.org.
Category: Government Finance