Funds Transfer Pricing in a Financial Institution

Before we launch into the heart of the current topic involving usage of Funds Transfer Pricing, let me take you through a very brief introduction.

 Figure 1 below depicts one of the simplest forms of a hypothetical FTP scenario of a bank operating with just a single (2%) deposit on the liabilities side and a single (5%) loan on its assets side.

Figure 1 – A Simple FTP Scenario

Funds Tranfer Pricing

 With the Bank Paying 2% on its deposits and issuing loans at 5%, it operates with a 3% Net Interest Margin.  This is also called the Treasury Contribution.

We will now introduce to this picture a specific Market Based Pricing Curve (from several available) where the going rates for deposits and loans are 2.75% and 4.25% respectively. The bank is presently sitting above the current market average prices for both aspects of receiving funds, and lending or investing. (Note that it is paying less than the market average to depositors and issuing loans at a higher rate than the market average.)

The difference between the actual and market average for receiving funds or deposits (0.75% in the above case) is called the Liability Contribution (liability spread). The difference between the actual lending rate and the market average for same (which also happens to be 0.75% in this case) is called the Asset Contribution (Asset spread). The 2 spreads reflect the respective leverages enjoyed by the institution from both ends. Further, the difference between marker average for lending (4.25%) and deposits(2.0%) is called the spread due to Funding Mismatch. Greater the funding mismatch, higher are the opportunities open to the financial organization to maximize income with minimum risks. As the funding mismatch is narrowed down, the organization’s opportunities for maximizing income without straying into risk zone shrink.  Assume the Market Based Pricing Curve we used here is LIBOR. If we used some other pricing curve instead, the respective market averages would not have been necessarily the same.

 

Key Elements in Measuring FTP:

Use of different transfer pricing curves would result in the bank getting different indications for spreads that will eventually impact its decisions on the pricing of its products.  One of the transfer pricing curves that is very widely used by banks and most financing circles is the LIBOR Curve, which is considered a good proxy for a strong bank.

The first step to take in implementing a FTP is to define your transfer pricing curve. Next, each bank should ensure that the curve used is representative of

(a)    its ability to source different categories of funds in the market, and for

(b)    establishing an accurate cost of funds value for a loan or any other earnings credit for a deposit.

Notwithstanding  the theoretical scenario depicted in Figure 1 above, a healthy bank in real time would be carrying in its portfolio thousands of deposits comprising of different classes with different terms, and similarly different classes and terms of loans including mortgage loans.

 A comprehensive FTP leads to the  plotting of the relevant characteristics for each of its deposits and loans. A bank’s deposits and loans may be of either fixed or floating rate. Further, in the case of floating rate loans and deposits, floating could have commenced from the date of origin or from the last re-pricing date; this means they are “match funded”. Each payment would be assigned a match funded rate by the FTP system, and such individual rates would be amalgamated into a single rate using a special process called the time/balance weighted algorithm.

 There can be may ways the Banks can use the FTP. Here, we will discuss Funds transfer pricing used in:

(i)      Managing Principal Payments and Outstanding Loan Balances

(ii)      Plotting Margin against Credit Score

(iii)      Evaluating Origination of Loans by Officer

  (i)   Managing Principal Payments & Outstanding Loan Balances

As an example, consider a 5 year mortgage loan carrying an interest rate of 2.75% to be amortized over the 5 year period through periodic monthly installments. Each of these monthly installments comprises a partial retirement of the total principal component within the total outstanding balance; and is transfer priced by the bank with reference to the appropriate maturity point on the relevant transfer pricing curve. A weight is attached to each principal payment based on the time period & the portion of principal included in each installment is outstanding. This process enables an overall composite rate to be calculated. Presuming that the rate thus calculated is 1.12%, there will be a spread of 1.63% (2.75% less 1.12%) on the basis of calculation of spread already discussed under Figure 1 above.  This spread of 1.63% is indicative of 163 basis points required for covering all the related costs involved in originating and servicing the loan – inclusive of the targeted profit.

The ability to make a prepayment assumption is supported by most Transfer Pricing systems. As we proceed with the projection of contractual cash flows, payoff of the loan is advanced with the application of additional principal reduction. This results in the shortening of the lifetime of the principal outstanding. Each of the cash flows comprising of contractual and prepayment components would be transfer priced.

 (ii)   Plotting Margin against Credit Score

The respective values when plotted, results in a Scatter Graph (Scatter Plot) with hundreds or thousands of tiny dots. The scatter graph is then analyzed to ascertain such information as the Weighted FTP Rate, Weighted FTP Spread and Weighted Average Rate as percentages. The plot will also indicate the Average Loan Size and Total Portfolio Balance in addition to showing the Number of Records and the Weighted Credit Score.

 Besides the above key information to be extracted from the scatter plot, its trend line will give you an indication as to how strong or weak your weighted average rate is for the given portfolio. This is made possible through a comparison of the existing correlation between your pricing and the borrower’s credit rating. Further, the scatter plot also depicts the relationship that exists between FTP Margin and Credit Score. The trend line generally is slightly downward sloping.

 You may also see the extent of your loans priced below the preferred threshold. These loans with low credit scores represent loans with higher risks. If this were to be the case, it shows a pressing need for the bank to aggressively attract borrowers of higher quality, and also to enforce more rigid guidelines in its pricing of lower quality credits.

(iii)   Evaluating the quality of loans

With regard to evaluation of origination of loans by officer, Incremental Analysis (often underutilized) is a very useful tool that can yield the desired results. With incremental analysis, the institution can focus on current activity in isolation of other irrelevant historical data. It can also be used as a good indicator as to how your loans and deposits are being priced currently, by comparing the directional narrowing down or widening of the combined spread for the portfolio. It is a good measure for rewarding officers through an appropriately designed effective incentive scheme based on the NII contributed by each Officer after transfer pricing.

Considering the volume of initiated loans only, without the spread could give a completely deceptive picture of the contributions to the organization by the loan officers. Volume may contain low quality loans with low rates and/or higher risks disbursed by a loan officer to simply “add to his cap” without considering their probable adverse effects on the organization; but when you combine volume with spread (after transfer pricing), you can see the rankings of the loan officers changing.

 The above evaluation could be further refined by introducing to this equation, another factor called Segmenting the Time Dimension which is capable of yielding results for officers by spreading the loan origination over a preferred time span into the past. The chosen time span may be appropriately divided in into (say) 4 segments. Snapshots of results obtained for the last four most recent time periods immediately preceding the current period will help establish trends of historical pricing of products. A typical Time Segmented tabulation will have in its first 4 columns, snapshots of results obtained for the four preceding time periods. The fourth column gives the total volume for the preceding three periods together with the relevant average pricing rate. The next 3 columns (that is columns 5 to 9) give projections for the next 4 future time period runoffs for the current portfolio with regard to maturities, amortizations and prepayments. Segmenting the Time Dimension greatly facilitates the management in ascertaining the impact of maturing spreads on portfolio performance. Its nothing new as all the software’s provide the time dimensions along with the measures.  Loan Officers can be ranked according to volume of loans disbursed during the earlier defined past time period. By ranking them again by combining average FTP spread and the balance time spread (net income effect), the management gets a good insight into the pricing decisions made by those officers.  Historical performance of each officer can be further analyzed into pricing trends by product for any given year. By comparing the spread thus obtained with that of the bank’s overall spread for the identical product, the bank gets a historical perspective pertaining to each officer’s handling of pricing of new balances by product. This information will help the management understand if under-performing pricing trends (if any) are deliberate deceptive measures or an on-going problem.

 By analyzing the principal runoff for the current portfolio pertaining to any officer or any product, the management can gain a good insight into desirable new volumes and rates for achieving budgetary targets.

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