Dynamic Provisioning: results of an initial feasibility study for Croatia Evan Kraft Director, Research Department Croatian National Bank* *The views expressed in this presentation are the author’s and not necessarily those of the Croatian National Bank.

Why dynamic provisioning? Bank lending is procyclical Provisioning is believed to be a cause of lending procyclicality Provisioning that looked at the borrower “over-the-cycle” would decrease fluctuations in bank profits and lending, and help stabilize the economy

What determines provisions? Research suggests that provisions –Increase as bank profits increase (“income- smoothing”) –Decrease as GDP falls –Decrease as loan growth increases (over- optimism)

Economists vs. Accountants: probable vs. expected losses Current provisioning practice is backward- looking, based on recognition of events that have already occurred Accounting standards support this partly because it decreases discretion and gives a good picture of the bank at a moment of time Economists feel that this approach fails to recognize future losses that are sure to happen but we don’t know exactly when (i.e. during the next recession)

Provisioning during a recession is not fun Harder to raise capital during a recession Lower profits or even losses make it painful to create provisions Increased provisions are usually seen by markets as a sign of problems and lead to further share price declines

Dynamic provisioning in Spain New element: the statistical provision A new type of general provision Statistical provision based on expected losses for 6 categories of assets Provision rates range from 0.1% (loans to firms with grade “A” long-term debt ratings) to 1.5% (current account overdrafts and credit overdrafts)

The Spanish system The basis for the statistical provision is the sum of the provisions on each of the six asset categories The statistical provision itself is the difference between the bank’s provisions and the standard basis Tp = Sp + Gp + St where –Tp is total provisions –Sp is specific provisions –Gp is general provisions –St is the statistical provision

The statistical provision The statistical provision is thus calculated as: St = (w1*a1 + w2*a2 +….w6*a6)- (Sp + Gp) –Where w1 is the risk weight of asset class 1 and a1 is the amount of asset class one in the balance sheet. Note that, in good times, Sp and Gp will be below their long-term averages, and St will then be positive. That is, banks have to form general provisions in good times Similarly, in bad times, banks get to decrease their statistical provisions—money is released.

How the statistical provision “flattens” provisions

Some things to note The loss probabilities for different asset classes are based on 16 years worth of data (two business cycles). The Spanish system assumes that losses in the next business cycle will be the same on average as in the last business cycle. The Spanish system seems to be incompatible with IAS 39.

Can Dynamic provisioning work in Croatia? Provisioning does seem to be cyclical…

Dynamic provisioning in Croatia But some banks do have irregular provisioning time profiles

A first try simulation 1: total provision = actual x ( actual) –(4.78 is the average for the whole banking system over the whole time period studied) simulation 2: total provision = actual x (bank's average Q4 96 to Q2 03 – actual)

A look at the first try Actual and simulated provisions for average of 35 banks

Large Bank 1

Large Bank 2

Large Bank 3

Effect on profits Large Bank 2

A new approach Idea: try to estimate how rapidly the average provision is falling over time, controlling for the business cycle Result: provisioning falling 0,06 percentage points per year

Another try simulation 3: total provisions= bank fixed effect - 0,061 time simulation 4: total provisions= actual - 0,061 time - 2

What it looks like Average for all banks

Is it adequate? Requires confidence that future decreases in provisioning will follow at the same pace as past decreases Produces negative overall provisions for some banks in some quarters Not very simple and probably not too robust

Concluding thoughts Dynamic provisioning seems attractive as a way to decrease financial instability But it is easiest to implement in stable markets with long data series and stable provisioning levels One can either be patient and wait for more data or look at other ways to achieve the same goals.