Citicorp- Traveler Group merger: Challenging barriers between banking and insurance R94723020 陳怡樺 R94723054 溫晴婉 R94723041 陳筱君

Citicorp- Traveler Group merger: Challenging barriers

between banking and insurance

R94723020 陳怡樺R94723054 溫晴婉R94723041 陳筱君

Agenda

The introduction of Citigroup merger event. The regulatory overview involved in the

event. How the Citicorp-Traveler group merger

influence peer institution? Empirical analysis and results. Conclusion

Citigroup Merger Event

Citicorp

Citibank is the largest bank in U.S(1984) and in the world(1929)

Customer accounts in more than 100 countries

Issuing more than 60,000,000 credit cards

the largest credit card and charge card issuer and service in the world(1993)

Travelers Group

Travelers is one of the largest providers of personal insurance products in the United States

three major business ： Insurance 、 Brokerage 、 investment banking

Revenues ： investment banking(57%) 、 life insurance(12%) 、 property insurance(26%) 、 consumer banking(5%)

Before Merger

$USD Citibank Travelers Group

Sales $ 21.6 billion $ 27.1 billion

Net income $ 4.1 billion $ 3.4 billion

Assets $ 310.9 billion $ 386.6 billion

Stockholders’ equity

$ 21.9 billion $ 22.2 billion

employees 93,700 68,000

Merger event

Announced on April ,1994

merged into Citigroup Inc on October 8

Congeneric Merger

Co-CEO‘s ： Reed from Citicorp

Weill from Travelers

Each holds half of the equity of citigroup

exchange rate of stock ： Citicorp → 1 ： 2.5 ； Travelers → 1 ： 1

Merger event

Board of Directors ： 9 for Citicorp

9 for Travelers Date of Announcement

Citicorp’s stock price

$142.875 → $180.50

Travelers Group price

$61.6875 → $73.00

This is the biggest illegal merger in U.S.

Synergies

Complementary nature

cost cutting cross selling 3C capital efficiency

Diversification

Net income → $ 7.5 billion

legislation

1933 Glass-Steagall Act

1956 Bank Holding Company (BHC) Act

─ prohibit banks from underwriting insurance

Federal Reserve → a two year trial period before divesting the insurance underwriting business

1999 Gramm-Leach-Bliley Financial Services

Modernization Act

Alan Greenspan

Impact of this merger

Deregulation of bancassurance

→ passing GLB Act & repealing G-S Act

Sanction the creation of one-stop financial supermarkets

A wave of mergers – peer institutions

→ more competitive environment

How the Citicorp - Traveler group merger influence

peer institution?

Background

Merger events

Federal Regulation

Literature review

Merger events

Announcement on the morning of 6 April 1998

Significant abnormal return

Citicorp: 142.875→180.5 (26%)

Traveler: 61.6875→73 (18%)

Federal Regulation

Federal and state laws: Barrier between banks and insurance

National Banking Act: Authorize small bank to sell insurance

Bank Holding Company ( BHC ): Prohibit banks from underwriting insurance

Literature review

Kane: Deregulation result in the responds of peer firms stock price.

Eckbo: There’s no significant stock price reaction for rival firms ( Due to the arising competition )

Benefit from removal of barriers

Reducing risk

Increasing profits

Increasing implicit government guarantee

Statistic hypothesis

Null hypothesis 1 : The Citicorp-Traveler Group merger announcement will not significantly change the stock prices of banks or insurance companies.


Null hypothesis 2 : The stock price reaction of banks, life insurance companies, health insurance companies, and property/casualty insurance companies, are insignificantly different from each other surrounding the Citicorp-Travelers merger announcement.


Null hypothesis 3 : The stock price returns of large bank and insurance companies are insignificantly different from the stock price return of small bank and insurance companies surrounding the Citicorp-Travelers Group merger announcement.

Statistic Methodology

Multivariate Regression Model ( MVRM )

Seemingly Unrelated Regression :

each event has one indicator variable

Statistic Model R1t = a1+ b1Rmt+ c1Rmt-1+ d1ΔIt+ f1ΔIt-1

4

+Σγ1,iDi+e1t

i=-5

:

: Rnt = an+ bnRmt+ cnRmt-1+ dnΔIt+ fnΔIt-1

4

+Σγn,i Di+ent

i=-5

Variable Explanation

Rmt: The observed return on the value-weighted market index on day t

ΔIt: The change in the interest rate on day t for the 10 year constant maturity treasury ( It - It-1)

Di: equal to 1 on day i, 0 other wise

γ1,i:the excess return on day i for firm 1

Empirical Results

SUR Results by Industry

Mean abnormal return H0 ： (γ1)+(γ2)+…+(γn)=0

Life insurance company ： 1.02%(p-value=0.0423)significant

Sign test H0 ： P=50% Life insurance company ： 67%(Z=1.826)si

gnificant


One-day event period – 6 April 1998

Hypothesis: (γ1)+(γ2)+…+(γn)=0

Sample size

Mean estimateγi

Probability<F

%Positive

Z-Statistic

National banks 113 0.1089 0.7367 47 -0.607

State banks 117 0.2747 0.4233 57 1.572

Life insurance 30 1.0207 0.0423**

67 1.826*

Health insurance

26 -0.6842 0.4741 42 -0.784

Property/casualty insurance

67 0.1939 0.5893 55 0.855


Two-day event period – 6-7 April 1998

Hypothesis: (γ1)+(γ2)+…+(γn)=0

Sample size

Mean estimateγi

Probability<F

%Positive

Z-Statistic

National banks 113 -0.3366 0.2027 44 -0.1301

State banks 117 -0.0578 0.8645 50 0.0000

Life insurance 30 -1.3919 0.0247**

53 0.365

Health insurance

26 -1.1845 0.2807 35 -1.569

Property/casualty insurance

67 -0.1458 0.7452 51 0.122

Cross-sectional Analysis

Model 1 and 2 Indicator variables

State-chartered banks, life insurance,

health insurance, property/casualty insurance

hypothesis 2 Assets size ： size>$10b, $1b<size<$10b

hypothesis 3


Model 1 Large banks have significant positive abnormal

returns. Life insurance companies have significantly

positive abnormal returns. Life insurance companies have significantly

positive returns than other insurance company.

Model 2 Two-day event period provides better explanatory

power.

Cross-sectional Analysis: Model 1 and 2

Independent variables Model 1 Apr.6 Model 2 Apr.6-7

Intercept -0.2425(0.3922) -0.8526(0.0117)

State chartered bank 0.3124(0.3150) 0.4970(0.1792)

Bank $1-10 billion 0.2449(0.4633) 0.3206(0.4195)

Bank >10$ billion 1.3983(0.0031) 2.1473(0.0001)

Life insurance 1.4849(0.0174) 2.2632(0.0024)

Health insurance -0.2825(0.6178) -0.3309(0.6303)

Property/casualty 0.6277(0.1720) 0.7009(0.1997)

Insurance $1-$10billion -0.4521(0.3394) 0.0321(0.9545)

Insurance >$10billion -0.1227(0.8569) -0.0946(0.9070)

Sample size 373 373

F-statistic 2.166 3.513

Prob>F 0.0294 0.0006

R2 0.0454 0.0717

Adjusted R2 0.0245 0.0513


Model 3 and 4 To replace the size indicator variables with the log

of assets for the firm. An improvement in model fit. Results

The indicator coefficient for life insurance companies is significant.

Large banks have significant positive excess returns. Returns do not significantly vary with size for insurance

company industry.



Intercept -1.9948(0.0017) -3.1014(0.0001)


Life insurance 5.3909(0.0030) 7.6917(0.0006)

Health insurance 2.1643(0.1242) 2.7844(0.1068)


Banks log of assets 0.2778(0.0005) 0.3654(0.0002)

Life insurance log of assets -0.2885(0.1501) -0.4067(0.0983)

Health ins. log of assets -0.1007(0.5885) -0.0578(0.8001)

Property/casualty log of assets 0.1055(0.4643) 0.1229(0.4870)

Sample size 373 373


Prob>F 0.0035 0.0006

R2 0.0604 0.0716

Adjusted R2 0.0398 0.0512


Model 5 and 6 Does concentration of business in life

insurance products respond more positively? Omit the insignificant size coefficients. Add three product mix variables.

(Percent of the firm’s total revenue derived form three insurance products.)

Degree of concentration Insignificant



Intercept -1.9948(0.0017) -3.1014(0.0001)


Life insurance 3.1694(0.0016) 5.4610(0.0001)

Health insurance 1.2112(0.2373) 1.0676(0.3908)


Banks log of assets 0.2778(0.0005) 0.3654(0.0002)

% of revenues in life insurance -0.3532(0.7705) -2.4207(0.1002)

% of revenues in health ins. 0.4857(0.6541) 2.1085(0.1098)

% of revenues in property/casualty 0.4385(0.7501) 2.6109(0.1190)

Sample size 373 373


Prob>F 0.0091 0.0001

R2 0.0540 0.0837

Adjusted R2 0.0332 0.0635

Conclusion

Peer institutions benefit. Despite the increased competitive threat This was not a wealth transfer

Life insurance companies benefit. Management of risks Cross-product sales revenues Lower distribution costs

Large banks benefit. too-big-to-fail Implicit government guarantees Economies of scope

Thanks for your attention!

Documents

Citicorp- Traveler Group merger: Challenging barriers between banking and insurance R94723020 陳怡樺 R94723054 溫晴婉 R94723041 陳筱君