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Citicorp- Traveler Group merger: Challenging barriers between banking and insurance

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.

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Citicorp- Traveler Group merger: Challenging barriers between banking and insurance

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

  2. 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

  3. Citigroup Merger Event

  4. 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)

  5. 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%)

  6. Before Merger

  7. 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

  8. 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. Merger event

  9. Synergies • Complementary nature • cost cutting • cross selling 3C • capital efficiency • Diversification • Net income → $ 7.5 billion

  10. 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

  11. 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

  12. How the Citicorp - Traveler group merger influence peer institution?

  13. Background • Merger events • Federal Regulation • Literature review

  14. Merger events • Announcement on the morning of 6 April 1998 • Significant abnormal return Citicorp: 142.875→180.5 (26%) Traveler: 61.6875→73 (18%)

  15. 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

  16. 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 )

  17. Benefit from removal of barriers • Reducing risk • Increasing profits • Increasing implicit government guarantee

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

  19. Statistic hypothesis • 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.

  20. Statistic hypothesis • 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.

  21. Statistic Methodology • Multivariate Regression Model ( MVRM ) • Seemingly Unrelated Regression : each event has one indicator variable

  22. 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

  23. 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

  24. Empirical Results

  25. 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)significant

  26. SUR Results by Industry

  27. SUR Results by Industry

  28. 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

  29. Cross-sectional Analysis • 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.

  30. Cross-sectional Analysis: Model 1 and 2

  31. Cross-sectional Analysis • 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.

  32. Cross-sectional Analysis: Model 3 and 4

  33. Cross-sectional Analysis • 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

  34. Cross-sectional Analysis: Model 5 and 6

  35. 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

  36. Thanks for your attention!

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