May 18, 2007

via EDGAR and Facsimile

Mr. James Rosenberg
Senior Assistant Chief Accountant
Securities and Exchange Commission
Washington, D.C. 20549

Dear Mr. Rosenberg:

AFG is responding to the Staff's comments in your letter dated May 3, 2007, regarding the above-referenced filing. Comments in the Staff's letter are reproduced below and are followed by AFG's responses.

Notes to Consolidated Financial Statements, page F-6

A.  Accounting Policies, page F-6

1. In our telephone conference on April 18, 2007, management and/or its advisers indicated that the inclusion in the regression analysis of data points where both the Actual Loss and the Hypothetical Black Book Based Loss were $0 reduced correlation. Please explain to us the basis for this assertion. In order to help us understand the effect that $0 settlement values have on the results of your regression analysis, please also tell us, to the extent readily attainable, what the regression results would be if you:

(a) Excluded all data points where both the Actual Loss and the Hypothetical Black Book Loss are $0; and

(b) In addition to (a), also excluded data points where either Actual Loss or Hypothetical Black Book Loss are $0.

Please tell us how many of the 116,000 contracts you include in each of the regressions analyses described in (a) and (b). Please also provide any narrative insight that you believe would be helpful to interpreting the results of the regression analyses described in (a) and (b) relative to the regression analysis described in your April 23, 2007 letter.

Apparently, there may have been some misunderstanding of what was said in our April 18, 2007, telephone conversation. We believe we stated that excluding data points where both the Actual Loss and Hypothetical Black Book Based Loss were $0 would reduce correlation. Nonetheless, we performed the regression analysis you requested; results are displayed in the tables below. The first table shows the results of our initial regression analysis discussed in our letter dated January 10, 2007, and as modified to exclude items requested in (a) and

Mr. James Rosenberg
Securities and Exchange Commission
Page 2

(b) above. The second table shows the results of the hypothetical model discussed in our letter dated April 23, 2007, and as modified for (a) and (b).

	r-squared	# data points	% of data used
Original model with all records used	45%	116,304	100%
(a) Eliminate if both losses are zero	41%	85,957	74%
(b) Eliminate if either (or both) losses are zero	52%	39,623	34%

	r-squared	# data points	% of data used
Hypothetical model with 9% reduction in CRV	35%	116,304	100%
(a) Eliminate if both losses are zero	28%	61,024	52%
(b) Eliminate if either (or both) losses are zero	36%	28,221	24%

We believe that excluding data points from a regression analysis introduces bias into the exercise and detracts from the ability to obtain a true scientific result. We also believe that your question correctly identifies one of the key reasons that neither our original regression analysis nor the one you requested us to perform is highly correlated. When we include all the data pairs that look like Row 3 in our table from the March 15 letter, it provides a powerful counter-effect to the nine percent of the data pairs in our original regression that plotted as "perfectly correlated" points on a 45 degree regression line. (As we explained in our April 23, 2007 letter, those same perfectly correlated data pairs were effectively destroyed when we performed the alternative regression you requested, contributing to the overall less correlated outcome.)

Our express intent in designing the claim formula in the manner we have is to reduce our likely claim payouts, preferably all the way to $0, by basing our formula on actual losses even when the hypothetical Black Book Value indicates that a hypothetical loss has occurred. Throwing out the many data pairs that reflect this occurrence would effectively throw out the essence of the contract feature we are trying to analyze. Furthermore, what would be the basis for throwing out ($0 actual, $non-zero Black Book) data pairs but not throwing out ($1 actual, >$1 Black Book) data pairs?

One may be concerned that including the data pairs in which one item in the pair is $0 and the other is $non-zero is somehow biased toward a less-than-highly correlated result. However, we point out that the data pairs in which actual loss is $0 but the hypothetical Black Book loss is not $0 does not mean that the hypothetical Black Book loss might not be quite close to $0. Those data pairs that reflect that reality are included in our regression and would be highly correlated and contribute, all things being equal, to a higher rather than a lower R-squared.

Mr. James Rosenberg
Securities and Exchange Commission
Page 3

2. In our April 18, 2007 telephone conference, there were discussions of at least two approaches management might take to developing the hypothetical contract that settles solely based on Black Book namely, (1) change the premium on the actual contract, but leave the contract residual value unchanged or (2) change the contract residual value on the actual contract, but leave the premium unchanged. The objective of both approaches would be to replicate a market transaction for a contract that would settle solely based on the Black Book. Under the first approach, it appears

that the change in the premium must be considered in determining the contract's settlement amount. Accordingly, it is unclear to us why the second approach, which we understand you used, would not also consider the premium in determining the contract's settlement amount (that is, the settlement amount for both the actual and the hypothetical contracts would both be based on the net cash inflows or outflows on the contracts as opposed to just the cash outflows, if any, at contract termination). Please describe for us the consideration management gave to defining the settlement amounts for purposes of the regression analysis. In your response, please tell us how the results of your regression analysis would differ had you defined settlement amounts as the net cash inflows or outflows on the contract, inclusive of the initial premiums received.

Please note that all premiums are collected in advance; none are on an installment basis. In addition, since few losses were expected when these contracts were written, premiums were relatively minor, averaging less than $200 per vehicle on the leases in our analysis. Raising the premium to any great extent would have made this product impossible to sell. Due to the low dollar amount of the premium and the inability to change it materially, we do not believe including the premium would significantly change the outcome of the analysis.

We envisioned the same premium being collected simultaneously in advance for both the actual contract and the new hypothetical contract, so that we could then focus all of our analysis on actual settlements vs. hypothetical settlements (e.g., entirely on contract outflows because the contract inflows are all identical and all received up-front at the same moment). If we changed our analysis to look at profit or loss per contract rather than incurred loss per contract (i.e. include the premium) we believe the correlation would be about the same or less. Looking at it another way, a call option is a derivative regardless of what you pay in premium to purchase the option, but if you ran a correlation at varying premiums, you would likely get a lack of correlation.

3. Please tell us if a regression analyzing the combined underlyings (i.e. greater of Black Book value or actual sales value) to the underlying that does not qualify for the SFAS 133, paragraph 10e(2) exception (I.E. Black Book value) or alternatively, a regression analyzing changes in the combined underlying to changes in the non-qualifying underlying would have yielded materially different results about the behavior of the residual value contracts than a regression analysis of (A) the settlement amounts described in your April 23, 2007 letter or (B) the settlement amounts described in comment 2 above. If materially different results would occur, please identify and explain to what you attribute such differing results. Please also explain to what extent you believe the sources of those differences provide insight into whether the use of either a settlement value approach or a change in underlying approach should be a choice among alternatives for evaluating whether your residual value contracts m eet the SFAS 133, paragraph 10e2 scope exception or, on the contrary, whether the sources of those differences cause you to believe that only one of the approaches is appropriate.

Mr. James Rosenberg
Securities and Exchange Commission
Page 4

We believe that both our original regression analysis performed January 10, 2007 and the later one you requested that is described in our April 23, 2007, letter represent a regression of changes of the combined underlyings against changes in the underlying which the SEC staff has interpreted to not qualify for the SFAS 133, paragraph 10(e)(2) exception. We believe that the FASB's focus on "settlement value" in paragraph 254 is consistent with, and not contradictory to, both paragraph 10(e)(2)'s reference to "behavior of the variables" and paragraph 58(c)'s reference to "changes in the combined underlying." The reason we believe all of these passages are consistent is that the underlying in every derivative is a forward price.

The contract residual value is originally set at our best estimate of a forward price based on Black Book. This estimate is based, in part, on data published by the Automotive Lease Guide, a provider of automobile residual value data. Note that there are no forward Black Book quotations or observable forward Black Book values in the marketplace, which calls into question whether a Black Book underlying actually does not qualify for the paragraph 10(e)(2) exception. But putting that argument aside, we do estimate a forward price for a vehicle at the expiration date of the contract, and CRV is set at that amount. In that sense, the option-style contract is struck "at the money" on a forward basis. Extending the analogy, forward Black Book represents the best estimate, assuming it is possible to do so for a non-financial asset, of the actual residual sales price of the vehicle. So the two underlyings we are comparing to each other all start at the same amount, but end at different amounts. T his fact may have been a major point of confusion up to this point.

Using the Row 1 example from our March 15 letter, let's assume the RVI contract lasted for four years and was entered into on May 1, 2003 to guarantee the residual value at lease termination on May 1, 2007. The CRV is set at the amount expected on May 1, 2003 to be the Black Book Value for that automobile on May 1, 2007.

WP0AB29942S686840	At 5-1-03	At 5-1-07	Change
"Forward" BBV for 5-1-07	$82,674	$74,900	$7,774
"Forward" Combined Underlying* for 5-1-07	$82,674	$79,000	$3,674

Using the example from Row 4:

1NXBR12EX1Z514294	At 5-1-03	At 5-1-07	Change
"Forward" BBV for 5-1-07	$7,746	$6,750	$996
"Forward" Combined Underlying* for 5-1-07	$7,746	$6,750*	$996

*The "forward" combined underlying is the greater of Black Book Value or Actual Sales Value at the contract settlement, or lease termination, date.

As you can see from the above examples, the change in the "Forward" BBV underlying (row 1, final column in each example) determines the Hypothetical Black Book Loss (i.e. Black Book settlement value) and the change in "Forward" Combined Underlying (row 2, final column in each example) determines the Actual Loss (i.e. Actual settlement value).

Mr. James Rosenberg
Securities and Exchange Commission
Page 5

Thus, these examples illustrate why we believe that a "settlement value approach" and a "change in underlying approach" is one and the same, and why we do not see a conflict in the literature between paragraphs 10(e)(2), 58(c), and 254.

Earlier telephone requests from the Division of Corporation Finance requested that we perform a regression of levels of the underlying, an approach that we believed would bias the result to imply that the two variables were highly correlated. A regression of levels for the two examples above would have plotted the data pair (74900, 79000) for the Row 1 lease and (6750, 6750) for the Row 4 lease. Note however that even under our regression methodology, the Row 4 data pair plots out as perfectly correlated. Under the methodology you requested at the April 18 teleconference, the Row 4 data pair does not plot as perfectly correlated. This helps explain why correlation declined in the "pro forma" example you requested we run in our April 23, 2007 response wherein we reduced CRV for a hypothetical contract that was required to be settled on Black Book (i.e. the 9% of contracts that were settled on Black Book in our initial analysis, and therefore perfectly correlated with Actual Sales Value, were no longer perfectly correlated).

In prior correspondence with the Staff, we stated that we believe we should not be performing a regression analysis of value levels and were encouraged when the Staff indicated in our April 18^th telephone conversation that it would not object to using a correlation analysis focusing on settlement values as outlined in paragraph 254 of SFAS 133.

4. Please tell us whether your residual value contracts have contractual terms that adjust settlement value for the effects of excess wear-and-tear, excess mileage or other aspects unique to the nonfinancial asset to which the residual value contract relates. If such features exist, please describe them fully and explain further how you concluded your residual value contracts qualify for the SFAS 133 paragraph 10e(2) exception. If such features do not exist, please confirm, it true, that the settlement of each of y our residual value contracts is based on an underlying associated with a nonfinancial asset that is unique. See SFAS 133 Implementation Issue C5.

None of the 116,000 leases in our analysis had terms that adjust settlement values for the effects of excess wear-and-tear or excess mileage. Our residual value contracts insure unique non-financial assets that are not readily convertible to cash; it generally takes 30 to 60 days to sell a vehicle. Each leased vehicle's residual value is based on a unique set of characteristics including make, model, style, year, mileage, color and condition. In accordance with DIG Issue C5, the non-financial asset (the leased auto) is owned by the party (the insured) who would not benefit under the contract from an increase in the price or value of the non-financial asset. If the leased auto increases in value, the insurance contract becomes less beneficial to the insured.

Please note that AFG's residual value business is in run-off. Using a discounted cash flow approach, we estimate that marking to fair value all of the remaining residual value contracts outstanding as of December 31, 2006, would result in a charge of less than $3.2 million (one-tenth of one percent of equity), net of tax. We have not attempted to analyze prior periods due to the onerous amount of time involved in the calculations.

Mr. James Rosenberg
Securities and Exchange Commission
Page 6

If you have any questions or comments regarding the information set forth above, please feel free to contact me at (513) 579-6633 (FAX: (513) 369-5750).

		American Financial Group, Inc.
		BY: s/KEITH A. JENSEN
		Keith A. Jensen
		Senior Vice President
cc:    Ibolya Ignat	Kathy Cole
Lisa Vanjoske	Ashley Carpenter
Todd Hardiman	Nilima Shah
Stephanie Hunsaker