Patenting and Licensing of Financial Innovations

Patenting and Licensing of Financial Innovations1

by

Praveen Kumar and Stuart M. Turnbull

C.T. Bauer College of Business

University of Houston

July 17, 2006

1We thank Josh Lerner for helpful comments. Tian Zhao and Guowei Zhang provided excellent researchassistance. All remaining shortcomings are our responsibility.

Abstract

Recent court decisions, starting with the State Street decision in 1998, allow business methods to

be patentable and now give �nancial institutions the option to seek patent protection for �nancial

innovations. We develop a dynamic model that incorporates salient aspects of the adoption and

dissemination of �nancial innovations. We �nd, somewhat surprisingly, that patent protection

may be detrimental to long-term pro�ts because of embedded real options for further innovations

and market expansion that are especially important for �nancial �rms. Moreover, a strategy of

patenting and then licensing may not be e¤ective because of expertise-related constraints of the

licensees. Our framework helps understand the success of a wide class of innovations including

swaps, credit derivatives, and pricing algorithms; it also helps �nancial institutions decide whether

it is optimal to exercise the patentability and licensing option.

Keywords: Business Methods; Financial Innovations; Patents; Licenses; Real Options

JEL classi�cation codes: G20, L10, O31

1 Introduction

Until recently, new products and services in the �nancial arena, ranging from back o¢ ce processing

systems to new methods to hedge liabilities, were generally considered not to be eligible for patent

protection, because of the business method exception to patentability (see below). However, a

number of recent court decisions, starting with the celebrated State Street decision,1 allow business

methods to be patentable. These legal decisions have ushered a new patentability paradigm that

poses an immediate decision challenge for �nancial institutions, because they now have the option

to seek patent protection for �nancial innovations. The possibility of patenting also brings with it

the option of licensing.

Financial innovations have occurred at a torrid pace (e.g., Tufano (1989) and Lerner (2002)),

and its economic importance is widely recognized (Merton (1992)). Yet, there are few available

decision frameworks that address the optimal exercise of the patenting and licensing options for

�nancial innovations. Such frameworks are especially needed because of certain unique features of

�nancial innovations.

There are systematic reasons why innovation in �nancial instruments and services may be much

more subject to public exposure than innovation elsewhere. First, there is often non-con�dential

regulatory scrutiny. Second, depending on the form of innovation, a �nancial institution may invite

other institutions to participate in order to reduce its risk exposure. This allows potential imita-

tors to learn about the innovation. Third, to generate increased demand, the end users must be

educated about the product. Again, information is disseminated about the product. Fourth, to

generate market liquidity the innovating institution needs the participation of other institutions.

The importance of developing liquid secondary markets for �nancial innovations distinguishes the �-

nancial services industry from other industries, such as computer software and telecommunications,

where developing a large market base is also critical.

However, there are barriers to entry and imitation in the �nancial industry that provide incen-

tives for innovation even with the endemic threat of exposure and imitation. More so than in most

other industries, specialized human capital and allied organizational assets are central to e¤ective

absorption of certain �nancial innovations � such as the development of a new kind of security or

implementation of especially complex formulas. Moreover, there is substantial heterogeneity among

1State Street Bank & Trust Co. v. Signature Financial Group Inc. 149 F.3d 1368, 1375 (Fed. Cir. 1998). Meurer(2002) provides a discussion of business method patents and related legal issues.

1

the end users of �nancial innovations. Consequently, if the innovating institution has a competitive

advantage with respect to in-house expertise, then it can continue to earn rents from the innova-

tion through �cream-skimming�or market-segmentation, even though the various versions of basic

innovation are o¤ered by imitators.

Indeed, while �nancial innovations share some structural features with innovations in other

industries where network externalities are important (see, e.g., Economides (1996))� again, for

example the computer software industry � �nancial innovations have certain unique characteristics.

In particular, in the �nancial services industry, the innovating institution need not be the exclusive

or even the most dominant vendor in order for the innovation to be pro�table. Rather, the innovator

can allow other �nancial institutions to o¤er various versions of the innovation to share risk, increase

market depth, liquidity and price transparency, while using its human capital and expertise-related

advantages to pro�tably trade with high-valuation end users.

In this paper, we identify and articulate important special features of �nancial innovations and

present a model� with applications� that helps address the basic question: to patent or not to

patent a �nancial innovation; and, if the innovation is patented, whether to license the innovation.

Our main contribution is to show � both theoretically and empirically � that for an important

class of �nancial innovations imitation is not detrimental to the innovating �nancial institution; in

fact, the innovating institution may optimally or strategically forego patent protection. By foregoing

patent protection and targeting the more sophisticated end of the market, innovating institutions

can reconcile the somewhat con�icting imperatives of developing liquid markets and earning rents

from the innovation. Interestingly, this conclusion is robust to the availability of a patent-and-

license option, especially if the licensees degrade the value of the second-generation innovations

for buyers because of expertise- or human-capital-related constraints � a factor that is especially

relevant for �nancial innovations, but is typically not emphasized in the innovations literature.

To �x ideas, we examine some common types of �nancial innovations and consider whether

patent protection may be warranted. If the innovation is strictly for internal use, such as a back

o¢ ce system, then there appears to be little at issue about whether to protect it either as a trade

secret2 or as a patent, apart from legal and administrative costs.

Many forms of innovation provide a direct service to clients that are visible to competitors.

2A trade secret is any information that can be used in the operation of a business or other enterprise and that issu¢ ciently valuable and secret to a¤ord an actual or potential economic advantage to others. See Sections $$39 to$$45 of the Unfair Competition Act.

2

These innovations do not require a secondary market. For example, the innovation could provide

clients with a service to improve the performance of their portfolio, or a method that facilitates

dynamic portfolio benchmarking. Patent protection appears to be generally useful in these cases:

if imitations occur, then the innovator has the option to seek remedy.

However, if the innovation occurs through the introduction of new forms of securities or complex

formulas, then a number of considerations suggest that patent protection may not be appropriate.

On the side of the innovating institution, the risks of underwriting the instrument may be such that

the institution wants to form a syndicate in order to spread the risk and consequently competitors

learn some details about the new security. The innovator has a window of protection before com-

petitors are able to o¤er a similar product. The length of the window depends on the complexity

of the structuring of the security, resolving legal and regulatory issues, the pricing methodology

and hedging considerations. The innovation may have potential appeal to a wide array of end

users, once they learn of its bene�ts. It is therefore in the interest of the innovator to advertise

the product. For example, in the developing credit derivatives market, investment banks produce

detailed information about the di¤erent forms of derivatives, publish papers about the uses of the

derivatives and pricing methodologies in trade journals, and give presentations to potential end

users.

On the demand side, investors may be reluctant to invest in illiquid instruments. While the

innovator may be prepared to make a secondary market, the presence of other market makers

will enhance the liquidity of the market and price transparency. However, price transparency

generally requires standardization of contracts, which will only be achieved by agreement among

the major market makers. All these considerations imply that it is in the interest of the innovator

to disseminate information about the security.

We �rst analyze the types of �nancial innovations that have recently been patented, and second,

identify a certain class of successful innovations, such as the swap and credit derivative markets,

where the absence of patent protection and imitation were crucial to the success of the innovation.

Guided by this analysis, we develop a theoretical model in which we identify su¢ cient conditions

on buyer valuation, imitation response, and the cost structure for patent protection and licensing to

be detrimental to the long-term pro�ts of the innovating institution. This framework emphasizes

the role of real options for further innovations and security market applications in determining

whether patent protection is warranted or not. Finally, we show that our model can be used to

3

aid institutions in answering the fundamental question of whether or not to patent the �nancial

innovation. We apply our framework to shed light on this issue for important �nancial innovations,

such as swaps and pricing algorithms.

To our knowledge, our model is among the �rst to analyze the pro�ts from �nancial innovations

in an industry equilibrium. Our analysis highlights the real options embedded in certain types of

�nancial innovations because of characteristics that are special to the �nancial services industry.

Consequently, our analysis contributes to the broader patenting and licensing literature. While

much of the patenting literature has assumed that patents are always optimal, Horstmann et al.

(1985) provide a model where patenting is not always optimal because it reveals the private in-

formation of the patent holder. However, in our model patenting can be sub-optimal even without

asymmetric information, because the value of the embedded options in a sequence of innovations

is ampli�ed with an educated market that follows a non-protected regime. And while the opti-

mal patent policy in software innovations is also complex due to the presence of externalities from

imitation (e.g., Bessen and Maskin (2001) and Shelanski (2002)), the expertise-related �rst-mover

advantages in the �nancial industry are manifestly unique, for the reasons described above. Simi-

larly, our analysis of the e¤ect of expertise-related constraints of licensees on the optimal licensing

policy contribute to the literature on analyses of licensing of intangible property (e.g., Katz and

Shapiro (1985, 1986a)). Finally, a recent literature theoretically and empirically analyzes the real-

option aspects of innovations (e.g., Bloom and Van Reneen (2000) and Schwartz (2003)), but this

literature does not apply its analysis to the specialized features of �nancial innovations that we

emphasize in this paper.

The remaining paper is organized as follows. In Section 2, we review the business method

patent, the State Street Decision, the use of patents, and the literature pertaining to �nancial

patents. In Section 3, we analyze characteristics of some well known �nancial innovations that have

been developed without patent protection. In Section 4, we present the model and its analysis, and

relate it to the literature on patenting and licensing. In section 5 we apply the model. Section 6,

summarizes the results and conclusions.

2 The Business Method

An application for a patent must be made within one year of commercial activity, even internal

secret commercial activity. The term of a patent is 20 years from �ling date. An issued patent

4

carries a strong presumption of validity: �clear and convincing�evidence needed to over come it.

The invention must be useful and novel. An invention can not be patented if it would have been

obvious to a person of ordinary skill in the art at the time of the invention3. Note that if a patent

application is �led and if a patent application is made in another country, details of the application

will become public at the end of an 18 months period after �ling, irrespective of whether a patent

will be issued4.

The potential bene�ts from the use of patents are well documented and include:

1. Patents can protect competitive advantage. A patent gives its owner the legal right to exclude

others from utilizing the invention covered by the patent. Hence, the �rm has a competitive

advantage in the area covered by the patent.

2. Patents can generate revenue through licensing. A patent owner can generate revenue by

licensing the use of patented inventions. A �rm may take out patents in areas that it is not

a serious player, simply in order to generate patent revenue.

3. Patents can be used defensively. Patents provide a form of détente in markets where rival

�rms hold patents. Cross licensing agreements can be used to minimize litigation risk.

4. Patents have value. Patents enhance a �rm�s value, because of their ability to (a) protect

market share and (b) generate revenue through licensing.

Some processes have been considered non-patentable. In 1908, in Hotel Checking Co. v. Lor-

raine5, the Second Circuit stated that a method of book keeping designed to prevent fraud by

waiters was ruled not patentable, because it simply described a business method. This decision

established the �business methods exception�and lead lawyers to conclude that business methods

were not patentable subject material. In 1972, in Gottschalk v. Benson the Supreme Court held

that the software for converting a decimal number to a binary representation was not patentable,

because the mathematical formula involved no substantial application except in connection with a

digital computer. In 1978, in Parker v. Flook, the Supreme Court ruled that a computer software

method of updating alarm limits in a chemical re�ning process was not patentable. However, in

3See Patent Act, 35 U.S.C.A. $$1-376.4See Patent Act, 35 U.S.C.A. $$122.5Hotel Security Checking Co. v. Lorraine Co., 160 F. 467 (2nd. Cir. 1908).

5

1981 in Diamond v. Diehr the Supreme Court ruled that a process for curing rubber was patentable,

even though the process used involved existing hardware and the only new component was software

to control the process.

Two important structural changes occurred during this period that a¤ected the patent granting

process6. Up to 1982, patent appeals were held in the appellate courts of the various circuits and,

perhaps not surprisingly, there was wide heterogeneity in the interpretation of patent law. In 1982,

the Federal Court Improvement Act vested almost exclusive patent appellate jurisdiction in a new

court � the U.S. Circuit Court of Appeals for the Federal Circuit (CAFC). According to Lerner

(2003), the CAFC was sta¤ed mostly with judges in the federal systems that had experience as

patent attorneys and were more sympathetic to the patent system. Over the following eight year

period, the CAFC a¢ rmed 90% of patent infringement cases, compared to the prior average of

62% over a three decade period. The second change was in the running of the U.S. Patent and

Trademark O¢ ce from a tax revenue funded agency to a pro�t center that took place during the

1990s. Ja¤e and Lerner (2004) argue that this resulted in a lowering of standards in the patent

awarding process. In many patent, there is a failure of patents to cite published academic work,

rising questions about the originality and novelty of some awarded patent. Patent examinations in

emerging technologies are often performed under severe time pressures by inexperienced examiners.

2.1 The State Street Decision

In March 1993, Signature Financial Group was granted a patent7 that described a computerized

system for managing a mutual fund investment structure. State Street brought an action to invali-

date the patent, arguing that the �nancial service data processing system was merely an algorithm

and a �business method.�In 1998, on appellate review in State Street Bank and Trust v. Signature

Financial Group8, Judge Giles Rich denounced the business method exception. He argued that

unlike the software decision in Gottschalk v. Benson, the Signature invention produced a useful,

concrete and tangible result, so the mathematical algorithm exception does not apply. Further,

with respect to the �business method� exception to statutory subject, Judge Rich puts this �. . .

ill conceived exception to rest.�The Court stated that the case frequently cited as establishing the

business exception to statutory subject matter, Hotel Checking Co. v. Lorraine, did not rely on

6See Lerner (2002) and Ja¤e and Lerner (2004).7See U.S. Pat. No. 5,193,0565.8See 149 F3d 1368, 47 USPQ2D 1596 (FED. Cir 1998), cert dnd, 1. 19 S. Ct.851.

6

the exception to strike the patent. In this case the patent was found invalid for lack of novelty and

the �invention�not because it was improper subject matter for a patent.

This judgment changed the law in two ways. First, if a software invention produced a useful,

concrete and tangible result, then the mathematical algorithm exception does not apply. Second,

it recognizes that business methods are patentable. Note that Judge Rich stressed that business

methods must meet the other legal requirements for patentability: novelty (the method must be

new) and non obviousness (the method must not be obvious to a person knowledgeable in the area).

The State Street decision was a¢ rmed in 1999 in A.T. & T. v. Excel Communications Inc.9. There

the Federal Circuit clari�ed the scope of the mathematical algorithm exception, establishing that

it is what an algorithm does �not how it does � that determines whether the subject matter is

patentable.

Following the State Street decision, the criterion for patentability rests on whether an invention

has a novel and practical application, as measured by the production of useful, concrete or tangible

results. Under this approach is the recognition that abstract ideas are not patentable10.

An abstract idea by itself never satis�es the requirements of eligible subject matter under 35

U.S.C. Section 101. An abstract idea, when practically applied to produce a useful, concrete

and tangible result, satis�es Section 101.

A practical application must be within the useful arts, employing technology if needed to realize

the practical application.

The test for practical application involves a determination of whether there is: (1) speci�c, sub-

stantial and credible utility in the speci�cation; (2) whether the invention produces a �con-

crete�result; and (3) whether the result is tangible, that is more than a merely mathematical

construct or a disembodied data structure, for example.

The extent of protection and whether it will be easy to design around the claims of the patent

depend on the particular invention. The Doctrine of Equivalence provides protection against models

that represent a �minor�extension11. The doctrine of equivalence is involved when a patent claim is

9See 172 F3d 1352, 50 USPQ 2d 1447 (Fed. Cir. 1999), cert dnd 120 S.Ct. 368 and remanded 1999 WL 1050064,52 USPQ2d 1865 (Oct. 1999).10This section draws on the comments of the American Intellectual Property Law Association (2002).11 In Festo Corp. v. Shoketsu Kinzoku Kogyo Kabushiki Co. (SMC), No. 00-1543, 2002 WL 1050479 (U.S. May

28, 2002) the Supreme Court attempted to clarify the applicability of the Doctrine of Equivalence with respect toamendments in any prosecution history estoppel.

7

not literally infringed, but substantially infringed. In most cases the infringing product has similar

but not identical elements as these described in the patent.

2.2 Recent History of Patent Awards

We follow the approach described in Lerner (2001, 2002) and examine patents in �ve subclasses of

classi�cation 705 for the period January 1971 to September 200512. In Table 1 we identify patents

that were listed as having �nance as the main classi�ed. In Part A, we record the history of patents

prior to the State Street decision and in Part B post the decision. It is clear that there has been a

regime shift, with more than double the number of patents awarded post the decision, than during

the 28 years prior to the decision.

In Table 2, we identify the companies that have been the most active in successfully seeking

�nancial patents. We split the companies into non-�nancials (Part A) and �nancials (Part B). The

split is some what arbitrary, as we have put General Electric into non �nancials. Comparing the

two parts, �nancial corporations have secured the most �nancial patents, as is to be expected. This

raises the question of the nature of the �nancial innovations that have been patented.

2.3 The Nature of Financial Patents

In Table 3, we list a number of patents awarded to di¤erent �nancial institutions. Part A, gives

examples of the 705/35 classi�cation. The patents typically describe a method and system to

perform some type of task, such as providing account values in an annuity with life contingencies,

management of an investment fund over a speci�ed horizon, dynamic portfolio bench marking and

a method for hedging one or more liabilities associated with a deferred compensation plan. These

types of patents are all for systems and methodologies that allow the �nancial institution to o¤er

services to clients using the systems/methodologies covered by the patent. As such, the patent

provides either a potential barrier to entry or a licensing opportunity. Other patents cover back

o¢ ce type of applications or methodologies to perform a particular task.

12The subclasses are:705/35: �nance (e.g. Banking, investment and credit).705/36: portfolio selection, planning or analysis.705/37: trading, matching or bidding.705/38: credit risk processing, loan processing.705/4: Insurance �calculation of annuity rates, investment of insurance company assets, the management of

risk through �nancial instruments and related topics.

8

Part B, gives examples of the 705/36 classi�cation. The patents typically describe a method

to perform some type of task, such as a computer implemented method for interacting with the

user of a trading computer, a method to improve the analysis of the performance of mortgage and

closed end loan portfolios, a data processing system and method to track di¤erent types of market

bench marks, and a method for pricing options using importance sampling and strati�cation Monte

Carlo simulation. The �nancial institution will bene�t from the methodology by either employing

it itself, selling the services generated by the product or by licensing its use.

In Part C, the 705/37 classi�cation, the patents cover a diverse range, examples being: a

compute method for optimizing portfolios of multiple participants that facilitate trades as swaps

among multiple parties that keep trades out of the market, a computerized order method and system

for tracking orders implemented on a trading �oor exchange, a system and method for managing a

plurality of stock option accounts each for a plurality of participants, and an investment company

that issues conventional shares and exchange traded shares in the same fund.

In Part D, the 705/38 classi�cation, the patents typically describe a method to perform some

type of task, such as a system that emulates the thought process of a loan o¢ cer in the risk

assessment and completion of a loan package, a system that assists customers in identifying their

credit needs and picking available products, a neural network that imitates a credit manager�s

evaluation and decision process to control loss and guide business expansion, and a method and

system for real time credit approval. Again, the patent is describing some type of back o¢ ce

function that gives the institution a comparative advantage.

In Part E, the 705/4 classi�cation, the patents typically describe a method to perform some

type of task, such as a system and method for providing retail clients with insurance policies

for foreign exchange risk, a system that administers a mortgage and life insurance combination

program, a method for evaluating the insurability of a potential insurable risk, and a data mining

based underwriting pro�tability analysis.

To summarize, we have randomly sampled a number of �nancial patents awarded to �nancial

institutions or �rms that provide �nancial services. The patents fall into the category of a system

and/or method that undertakes a particular task that provides either a direct service to the �nancial

institution or can be transformed to provide a revenue generating service to clients. The patent

acts as a barrier to entry.

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2.4 Licensing13

An institution can always patent an innovation and then license the use of the innovation to other

institutions. Alternatively, for certain types of innovations that lack the uniqueness to qualify for

patent protection, and require the participation of other institutions to help develop a market, the

innovator can register the name of the product as a service mark14 and license its use. In the

case of �nancial innovations, licensing brings its own set of complications arising from pricing and

antitrust laws.

For example, in April 2003, Morgan Stanley and J. P. Morgan (the owners) launched their

jointly owned Trac-X credit default indexes15. By November 2003, it had been licensed to eleven

dealers. Trade information (volume, size) could not be shared for antitrust reasons. This prevented

a per trade or a per notional variable license fee. Determination of a realistic value for a �xed fee is

not easy, given the di¢ culty of quantifying the license value to di¤erent dealers. There is an upper

bound, as the size of any �xed fee would have to be relatively low, given that the barriers to entry

for indexed products is low. A small �xed fee could be charged to help o¤-set some of the legal and

regulatory compliance costs.

The owners did however derived indirect bene�ts. First, the prestige value associated with being

a market innovator. Second, if a licensee wanted to introduce a new structure based on Trac-X,

they had to receive permission from the owners. This meant possibly revealing information about

the new structure and possibly revealing proprietary trading information to the owners. Third,

as both Morgan Stanley and J. P. Morgan had agreed to make markets in the index, they were

able to observe market �ow information. End users in shopping around for quotes, would normally

approach these dealers. Other investment dealers would also approach these dealers for quotes,

when trying to hedge their positions. Fourth, they controlled the selection of the names in the

indexes.

13We gratefully acknowledge discussion with Lisa Watkinson, Lehman Brothers (New York), aboutsome of the issues associated with licensing �nancial products.

14A service mark is similar to a trademark, except that a trademark promotes products while service marks promoteservices. See Lanham Trademark Act 15 U.S.C.A.$$1051-1127.15The case history is reported in Du¢ e (2004) and Chacko, Dessain, Sjoman, Maruani and Hao (2005).

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3 Innovation Characteristics

Senior management must decide on a policy that describes what forms of innovations will be

patented. In Table 3, the patents usually describe some type of method or system that provides

the �nancial institution with a comparative advantage. These can be grouped into three broad

categories: (a) undertaking some form of back o¢ ce function; (b) facilitates a service that can be

o¤ered to clients or an improvement in the technology of an existing service; and (c) a methodology

of performing a particular task.

Innovations that fall into categories (a) and (c) may be di¢ cult for outsiders to directly observe.

However, there is di¤usion of knowledge. In the �nance industry there is mobility of labor and when

workers move, they take their knowledge with them and can employ it in their new employment.

There are also industry conferences and trade magazines, where people describe their work. Con-

sequently, there are a number of di¤erent avenues for the di¤usion of knowledge. Without patent

protection, competitors may quickly reverse engineer the product and o¤er a competing product.16

For innovations that fall into category (b), the innovation facilitates a service that is o¤ered to

clients. Consequently, the institution advertises the service. Rival �rms can attempt to reverse

engineer the innovation that facilitated the service. A patent provides protection to the innovator,

allowing it to earn rent.

In this section, we describe the characteristics of innovations for which patent protection is

unnecessary or undesirable.

3.1 The Form of Innovation

To be concrete, we consider the innovation to be some form of �nancial instrument, that will appeal

to a wide section of end users. We will give examples shortly. In the �rst round of transactions,

the innovator learns how to appropriate price the instrument and how to hedge. In the process,

the institution earns rent that rewards it for its innovation. It also earns itself a reputation as

a market leader. News of the innovation spreads among competitors and imitators start to o¤er

similar products. Consequently, rents dissipate and the innovator ends up earning a fair rate of

return. This is the type of �rst mover advantage argument described by Herrera and Schroth (2003)

(HS). However, the situation in practice is often far more complex, than that described by HS.

16 If an innovation is protected by a trade secret and a third party reverse engineers its innovation, the innovationwill not have protection if the third party was not bounded by the trade secret.

11

For the particular product, the innovator may expect the potential market for end users to be

large and it needs to grow the market. It must educate end users about the nature of the innovation,

explain pricing methodologies, settlement procedures and work to increase the transparency of

the market. For this to happen, it needs the participation of other market makers. Apart from

increasing market depth, the increase in the number of market makers will help in the dissemination

of the information about the product to potential end users. To increase market liquidity, it needs

the standardization of contracts, and the posting of consensus prices visible to end users. Increased

use of the product by end users, may help a market maker to lower its costs of hedging its position, by

taking o¤-setting positions and generating revenue on the �ow. New forms of innovation involving

extensions of the basic product may become possible, once end users become familiar with the

basic product. Indeed, end users may be the driving forces behind future innovations by suggesting

extensions. The rents will accrue to the innovating market leaders.

3.2 Examples

We give three examples of successful innovations that were made without patent protection.

3.2.1 The Swap Market

The �rst interest rate swap contract was made in the early 1980s17. The swap contract allowed

one end user to trade �xed rate coupon payments over a de�ned horizon for a series of �oating

rate payments over the same period with another end user. A �nancial institution (the innovator)

acted as a broker and charged a spread for the services provided. The end users were only exposed

to the counterparty risk of the �nancial institution. The tenor of the contracts were initially

relatively short. The market quickly grew, as end users learnt of the bene�ts of the contract, and

the spreads attracted more market makers. The increased competition put pressure on the spreads.

This simulated further improvements. First, to increase revenue, institutions started to warehouse

swaps, that is they took the opposite side and then hedged. Second, maturities of the contracts

increased, putting pressure on the risk management systems of the �nancial institutions. Third,

contracts became standardized, with the development of an ISDA contract. This standardization

facilitated the posting of consensus swap rates on a �xed range of speci�ed maturities, increasing

17Note that this example occurs before the State Street decision, while the second example occurs after thatdecision.

12

the transparency of the market.

The success of the interest rate spurred new innovations in several di¤erent directions. The idea

evolved to foreign exchange contracts, with the introduction of foreign exchange swaps. Options

on swaps (swaptions) started to trade.

The initial market leaders in the swap market and the resulting derivative products earned rent

without patent protection or licensing.

3.2.2 Credit Derivative Markets

The introduction of credit derivatives started in the late 1990s. In a credit default swap, one

party, the protection buyer, makes periodic contingent premium payments to a second party, the

protection seller. If a de�ned credit event occurs, the protection seller makes a payment to the

protection buyer to compensate for the loss on some de�ned reference entity. The growth of

the market has been very rapid, though liquidity on individual contracts remains an issue. The

success of the market has prompted a number of innovations. First, synthetic collateralized debt

obligations, where the collateral portfolio is a portfolio of credit default swaps. To help improve the

transparency of the market, credit indices were introduced in 2003, and prices quoted on di¤erent

tranches on the index. Second, the trading of bespoke individual tranches is now possible, due

to improvements in technology by some of the leading investment banks. Third, options are now

traded on credit default swaps. In all cases, the innovating institutions have been able to earn rents

on their innovations.

3.2.3 Pricing Algorithms

If a �nancial institution invents a pricing algorithm, the decision to patent depends on its area of

application and the identity of the users of the algorithm. Clients of the institution usually want

price transparency. Two dimensions of transparency are knowing how to price an instrument and

guidance on appropriate hedging. If the algorithm can be readily calibrated, so that it is easily

usable by end users, it is in the institution�s advantage to make it available so that it can be used

for pricing or hedging. The Lehman risk model, described by Naldi, Chu and Wang (2002), is

an example. The model is a 32-factor model that analyzes the risk of a �xed income portfolio

relative to the Lehman index. Examples of models that have become industry standards are the

13

Black-Scholes option pricing model developed by Black and Scholes (1973)18; the reduced form

model for pricing credit derivatives developed by Jarrow and Turnbull (1995); and the application

of the normal copula to model default dependence, described by Li (2000). In the �rst two cases

the developers were academics. In the last case, David Li is a banker, who worked at the Canadian

Imperial Bank of Commerce (CIBC) at the time he published his paper. There is no patent either

to CIBC or to Li covering the application.

Not all algorithms will provide bene�ts to clients of the institution. Some algorithms help

the institution in execution and provide a competitive advantage. For these algorithms, patent

protection may be bene�cial.

3.2.4 Comparison with Innovation in Other Industries

The examples given above indicate that the success of �nancial innovation depends on a number

of steps. First, is generating a market for the product. Second, developing the liquidity and

transparency of the market. Third, developing derivative innovations.

There are, somewhat super�cial, similarities between certain aspects of successful �nancial

innovations and innovations in �network markets�� where users purchase products compatible

with those brought by other � such as the computer software industry (see, e.g., Besen and

Farrell (1994)). In such markets, coexistence of incompatible products is unstable, and dominant

technology standards emerge rapidly (Besen and Johnson (1986)). Because expectations about the

ultimate size of the network are crucial, market demand can be self-reinforcing for a technology

that is expected to be the standard � and hence end up with largest network. There is, thus, a

�winner-take-all�aspect to network markets, and the dominant standard can be extremely di¢ cult

to dislodge, inspite of the presence of competitors that are superior from a strictly technological

perspective (e.g., David (1985) and Ferguson and Morris (1993)).

Consequently, installing a large user base visibly and early is important for successful innova-

tions in network markets. Innovators therefore use a variety of strategies to maximize their use

base early on. Examples of such strategies include penetration pricing (Katz and Shapiro (1986b));

liberal grants of manufacturing licenses to potential rivals and commitments for joint development

of derivative innovations (Bensen and Farrell (1994)); actively attracting producers of complemen-

tary products, such as applications for software platforms; and, strategic �pre-announcements�of

18One of the authors asked the late Fischer Black why he had not patented the Black-Scholes model. He replied:�If I had, no one would have used it.�

14

products to disrupt the installation of user base for rivals (Farrell and Saloner (1986)).

However, pro�t-generation in successful innovations in network markets and �nancial innova-

tions arguably di¤er in at least one important aspect. Successful innovations in network markets

generate pro�ts by becoming dominant standards and increasing the size of the user base. In such

�winner-take-all�markets, axiomatically, there is little scope for the simultaneous existence of di¤er-

ent versions of the basic technology provided by di¤erent vendors. By contrast, successful �nancial

innovations are often characterized by various derivative innovations (of the basic innovations) be-

ing simultaneously o¤ered by di¤erent �nancial institutions. The innovating institution typically

earns pro�ts not by grabbing the entire market, but by expropriating the most pro�table trading

segments through a �rst-mover advantage based on expertise.19

�Cream-skimming� by the innovating institution in the derivative innovations market, after

initially developing the liquidity and transparency of the market by inviting the participation of

other institutions, is thus a relatively unique aspect of an important class of �nancial innovations.

Importantly, this aspect of �nancial innovations poses a dilemma for the innovating institution:

whether to patent (and possibly license) the innovation or to forego patent protection. In the next

section, we present a model that analyzes this decision problem in an industry equilibrium.

4 A Real Options Model of Financial Innovations

The model has three dates. At the start (t = 0), the �nancial institution (denoted I) expends

an amount C0 to develop a new form of a derivative. The derivative can be purchased from the

institution and is e¤ective for one-time period. That is, if investors wish to obtain recurring bene�ts

from the derivative, they must re-purchase in every time period. The institution has a client base or

initial market ofM0 investors, each of whom obtain a a basic value of � from using the derivative at

each date, and this parameter is common knowledge. We assume that I is the high-quality provider

and the leader in the market because of its proprietary intellectual capital and its pool of specialized

human capital. Therefore, in addition to the derivative, I can provide additional services regarding

the derivative that add value to the buyers: for example, from expertise in the structuring of the

19Herrera and Schroth (2003) argue that �nancial �rms that innovate possibly enjoy a sustainable �rst moveradvantage. They learn how to structure a particular type of deal. Repeated deals provide the innovator with moreexperience on the structuring of deals. While the term sheet for the deal may be public knowledge, the actualstructuring details are private. Consequently, the innovator can earn rents for a period before imitators learn how tostructure similar deals eroding spreads.

15

derivative; the resolution of legal and regulatory issues; providing ancillary technology to compute

the required cash �ows to di¤erent stake holders, and the development of the necessary pricing and

hedging methodologies. These additional services are valued at �. Thus, if the derivative premium

is �, then the net bene�t to the investor is, �+ � � �.

To develop the market beyond the initial client base, the �nancial institution needs to advertise

the derivative to potential end users. But, in this process, imitators learn about the derivative and

compete with the institution at (t = 1). These imitators also advertise to their end users. We will

assume that there are N imitators and each imitator has Z end users, who obtain the basic value �

per period from using the derivative. The imitators, however, are not in a position to provide any

additional services to the end users. Hence, the net bene�t to the customers of investors is, � � �.

The provision of specialized services is costly; for example, for �nancial instruments, the bulk

of the delivery costs are specialized labor wage costs. Because such highly quali�ed labor is in

short-supply, we assume that the unit costs are convex in the market size: thus, if the market size

is M; then the unit costs are, 12c¯M2; for some given parameter c

¯> 0: The imitators at (t = 1),

on the other hand, act competitively and face a common constant unit cost function, �cM; where

�c < �:

4.1 The Patenting Decision

The innovating institution, I, can forestall imitation by patenting the derivative valuation process.

If the institution does patent the new derivative, then the market size for the derivative at date

t = 1 is limited by the institution�s own advertising and client reach, namely M0. We denote the

patenting decision through the binary variable P 2 f0; 1g, where P = 0 indicates that the �rm

obtains a patent, while P = 1 denotes the alternative.

The institution I expects that the innovation will lead to further innovations. It anticipates

that in the process of communicating with end users and observing their value generation from the

derivative, it will learn about (a) how to improve the market for the derivative and (b) the potential

demand for new forms of innovations related to the derivative. E¤ectively, the institution has real

options for further innovation.

The end user may view the future innovation either as a complement or a substitute. For

example, if the initial innovation is a credit default swap and the future innovation is an option on

the credit default swap, the end user might invest in both. Alternatively, if viewed as a substitute,

16

the end user switches from investing in the credit default swap to investing in options on the swap.

Another example of a substitute would be a collateralized debt obligation and the future innovation

being a synthetic collateral debt obligation on a credit index, the later having more transparent

pricing. In this paper, we treat the future innovation as a substitute, though the analysis readily

extends to the case of a complement.

We model these real options by assuming that at date t = 1, I makes an investment C2 in a

future innovation that will materialize at date t = 2, with a probability q, 0 < q < 1 The new

innovation increases the buyer valuation to � > �+�: Because I is the originator of this innovation,

it has a monopoly over its delivery at date t = 2; taking as given the total market size for the initial

innovation (or derivative) at the end of the previous period (date t = 1). The unit cost function for

this innovation for I is 12c0M2. Note that in general the cost of further innovation,C2, will depend

on the initial patenting decision. If the market has su¢ ciently developed in size and knowledge,

then costs may be lower. The size of the market will tend to be larger in the absence of patenting.20

Under certain situations, I; as a monopolist, may wish to restrict the market it serves. In this

case, the residual market can still buy the original derivative in the market place. However, we

assume that by date t = 2; the market for the original derivative is competitive, and all producers

face common constant unit costs of production and delivery of, c¯: We therefore incorporate the

idea, well documented by the empirical literature, that the original innovation eventually becomes

a commodity over time as the expertise and specialized inputs required for its production and

delivery become publicly known and freely available, respectively� see Tufano (1989). Indeed, we

also assume that the opportunity to earn rents from this class of derivatives itself expires at the

end of date t = 2, although we can easily allow a competitive market in the product class to remain

over the horizon, without materially a¤ecting our results:21

Finally, all players are risk-neutral. The time-interval between adjacent dates is � and the

instantaneous risk-neutral discount rate is r:

4.1.1 Analysis

20Similarly, we would expect Bayesian updating to occur for the probability of a successful innovation, q, given thatat date (t = 1), I can observe the state of market development. For the present, we ignore the Bayesian updating.21More realistic touches, such as allowing the buyer value from using the original derivative to atrophy over time

(because of possible obsolescence) can be easily incorporated at the cost of additional notation, but without materiallya¤ecting our results.

17

We solve the model through backward induction, starting at date t = 2: Let, MT1 denote the total

number of investors purchasing the initial innovation at the end of date t = 1: Clearly,MT1 depends

on whether I patented the innovation at date t = 0 or not. That is,

MT1 =

8<: M0; if P = 0

M1 �M0 +NZ; if P = 1(1)

We �rst consider the case of no patenting at the initial date: P = 1. If I successfully develops

the innovation, then it faces a market where the buyers�reservation utility is determined by their

ability to purchase the initial innovation at the price c¯. Let �� � � + �: Buyers will only purchase

the new innovation at a price �2, if (���2) � (���c¯) The constrained pro�t maximization problem

facing I, conditional on having a successful innovation at date t = 2, is to choose a derivative

premium �2 and market size Q2 to:

Maxf�2;Q2g

��2Q2 �

1

2c0Q22

�; s:t:; (i) �2 � �� (�� � c¯); (ii) Q2 �M1 (2)

In (2), we recognize the upper limit on the price due to the reservation utility of the buyers. As

this pricing constraint will be binding in any optimal strategy for I; we straight forwardly compute

the optimal price of the new innovation and its market share as:

Q�2(P = 1) = Min

�M1;

�� (�� � c¯)

c0

���2 = �� (�� � c

¯) (3)

This policy yields the pro�ts,

��2(P = 1) = Q�2(P = 1)

��� (�� � c

¯)� c

0Q�2(P = 1)

2

�(4)

Note that these pro�ts are positive because, by assumption, � > ��: Thus, I will invest in developing

the new innovation if and only if

C2(P = 1) � exp(�r�)[q��2(P = 1)] (5)

We turn next to the case where I has taken out a patent at date t = 0: P = 0: In this case, I

maintains a monopoly over the market,M0. Of course, I may still wish to segment this market into

18

buyers who receive the second-generation innovation, at a premium of �2, and buyers who receive

the original innovation, at a premium of �2. Buyers of the latest innovation therefore will purchase

as long as (�� � �2) � � � �2: Hence, conditional on successfully developing a second-generation

innovation, the optimization problem of I is now to,

Maxf�2;Q2g

�[�2Q2 �

1

2c0Q22] + [(�2 � c¯)Max(0;M0 �Q2)]

�; s.t., �2 � �� (�� � �2) (6)

The objective function (6) shows how the market gets endogenously segmented between the

�rst and second generation innovations. Analysis of the maximization problem yields the optimal

pricing and market segmentation policies:

Q�2(P = 0) = Min

�M0;

�� (�� � c¯)

c0

���2 = �; ��2 = �� (7)

These policies yield the pro�ts:

��2(P = 0) = Q�2(P = 0)

��� c

0Q�2(P = 0)

2

�+ (�� � c

¯)Max(0;M0 �Q�2(P = 0)) (8)

Thus, I will invest in developing the new innovation if and only if

C2(P = 0) � exp(�r�)[q��2(P = 0)] (9)

We can delineate two sets of conditions for whether it is optimal to patent or not. It then follows

from (1), (4) and (8) that,

Proposition 1 Suppose that M1 >��(���c

¯)

c0 : Then, ��2(P = 1) > ��2(P = 0) if M0 is su¢ ciently

small relative to ��(���c¯)

c0 :

Proposition 1 con�rms the intuition that if imitators bring in a su¢ ciently large number of

buyers into the market at date t = 1; then the pro�ts from a successful new-generation innovation

are higher for I if it does not patent the initial innovation. This result also indicates that, for a

su¢ ciently large ZN , allowing imitation is more likely to be optimal for I if the second-generation

innovation signi�cantly improves buyer value compared to the unit cost, that is, (� � ��)=c0 is

high and/or if there is a signi�cant cost reduction between the two innovations, that is, c¯/c0 is

19

high. However, if (� � ��)=c0 is low and/or if there is a signi�cant cost increases between the two

innovations, that is, c¯/c0 is low, then we have the reverse case:

Corollary 1 If M0 >��(���c

¯)

c0 , then ��2(P = 0) > ��2(P = 1):

We turn next to analysis at date t = 1: We �rst consider the case of no patenting. Because I is

the market leader, it chooses a premium and market size, with the imitators serving the remaining

market at the break-even price of �c. An end user will buy from I only if �1 � �c � �; where �1

is the premium charged by I: Hence, I�s constrained pro�t maximization problem is to choose a

derivative premium �1 and market size Q1:

Maxf�1;Q1g

��1Q1 �

1

2c¯Q21

�; (10)

s.t., (i) �1 � �+ �c; (ii) Q1 �M1 (11)

The reservation utility constraint in (11) will be binding in the optimal policy. Hence, the solution

to (10)-(11) is,

Q�1(P = 1) = Min

�M1;

�+ �c

c¯

���1(P = 1) = �+ �c (12)

The pro�ts with the optimal policy, ��1(P = 1); are given by

��1(P = 1) = Q�1(P = 1)

��+ �c� c¯Q

�1(P = 1)

2

�(13)

If a patent has been taken out at date t = 0, that is, P = 0; then at date t = 1; I has a monopoly

over the provision of the initial innovation. Thus, I will charge the premium �1, subject to the

constraint that �1 � �� and serve its pro�t maximizing market:

Maxf�1;Q1g

��1Q1 �

1

2c¯Q21

�; s.t.�(i) �1 � ��; (ii) Q1 �M1 (14)

The optimal policies are therefore,

Q�1(P = 0) = Min

�M0;

��

c¯

���1(P = 0) = �� (15)

20

The pro�ts from the price-quantity strategy speci�ed in (15), denoted by ��1(P = 0) :

��1(P = 0) = Q�1(P = 0)

��� � c¯Q

�1(P = 0)

2

�(16)

Now, we can directly compare I�s pro�ts at date t = 1, based on the patent decision at the

previous date. Intuitively, this comparison trades-o¤ the higher pro�t margin and lower market size

with patent protection against the lower margin and higher market size without patent protection.

Patenting strictly dominates the alternative at date t = 1 if M0 is at least as large as the optimal

monopoly market size for I. This is stated formally in the following proposition:

Proposition 2 If M0 � ��c¯; then ��1(P = 0) > �

�1(P = 1):

Note that Proposition 2 holds is independent of ZN: That is, if I�s initial end user base is

not too small, then patenting strictly dominates the alternative from the viewpoint of date t = 1;

irrespective of the market extension provided by imitators. On the other hand, the logic of

Proposition 2 can be reversed if M0 is su¢ ciently small relative to ZN: That is,

Proposition 3 If M0 is su¢ ciently small relative to ZN; then ��1(P = 1) > ��1(P = 0):

Propositions 2 and 3 clarify the essential con�ict between patenting and allowing imitation:

patenting increases pro�ts on the initial innovation, but may restrict pro�ts� relative to an open

imitation environment� from the second-generation or subsequent innovation.

Indeed, Proposition 3 implies that if the innovating institution�s initial market size, M0; is

su¢ ciently small, then it is bene�cial not to patent in order to increase the value of the real option

of the subsequent innovation. That is, irrespective of the size of ZN; ifM0 is su¢ ciently small, then

it is likely that the optimal policy is to forego patenting. Usually, if there is a �break through,�

one expects innovations creating large buyer value per unit cost, i.e., a large (��=c), to be more

patentable. The following Corollary shows that this is not always the case.

Corollary 2 There exists some 0< M¯ 0< ��c¯such that ��1(P = 1) > �

�1(P = 0) whenever M0 <

M¯ 0:

This result is somewhat counter-intuitive because it implies that, for a given M0, patenting is

less likely to be optimal if the initial innovation creates large buyer value per unit cost of delivery.

Usually, one expects innovations creating greater buyer value (per unit cost) (��=c¯)to be more

21

patentable. However, this intuition overlooks the fact that high-value initial innovations increase the

innovator�s short-run pro�ts without a patent, while also (at least weakly) increasing the innovator�s

pro�ts from subsequent innovations. Another way of stating this point is that it may be sub-optimal

to patent signi�cant �break throughs,� especially if these break throughs can give rise to further

innovations. Some types of �nancial innovations fall into this category. If patented, so that there

are no other suppliers, the market is too small. To be viable, the market needs other suppliers and

this can be achieved by not patenting.

We now analyze the determinants of the optimal patenting decision in further detail by com-

paring the present value of pro�ts, from the view point of date t = 0. First, with patenting22

��0(P = 0) = exp(�r�)���1(P = 0) + [exp(�r�)q��2(P = 0)� C2(P = 0)]+

�(17)

It will be optimal to patent if

��0(P = 0) > C0 + CP

where CP are the legal and preparation costs associated with patenting. Without patenting we

have

��0(P = 1) = exp(�r�)���1(P = 1) + [exp(�r�)q��2(P = 1)� C2(P = 1)]+

�(18)

We clarify the circumstances under which the institution bene�ts from patenting versus not patent-

ing in a number of results. The �rst representation quanti�es the intuition that if the initial market

size, i.e., M0 is large relative to the value increment arising from the second-generation innovation,

then it will be optimal for I to patent at date t = 0:

Proposition 4 Suppose that M0 �Max���(���c

¯)

c0 ; ��c¯

�: Then, ��0(P = 0) > �

�0(P = 1):

We note that the condition of Proposition 4 is more likely to be met if, ceteris paribus, the

di¤erence ����, that is, the buyer value increment between the initial and the subsequent innovation,

is not too high. And, for a �xed ����, the su¢ cient condition of Proposition 4 is also more likely to

be satis�ed if c¯/c0, that is, the ratio of the delivery costs of the initial and the subsequent innovations

is not too large. Put di¤erently, if there is a substantial production cost reduction between the two

innovations, then patenting is more likely to be optimal. This is because with a very low production

22The term [X]+ = max(0; X):

22

cost at date t = 2; the advantages of having a large market size due to an open imitation regime

are ampli�ed.

The tenor of the foregoing argument suggests that it would be optimal not to patent if there is

a substantial buyer value-increment or a substantial production cost reduction between the initial

and the subsequent innovation. Our next result clari�es that this intuition is correct provided that

the market extension due to an open imitation regime is su¢ ciently large.

Proposition 5 Suppose that ZN is a large number. Then there exist � and � such that

��0(P = 1) > ��0(P = 0) if �� �� > � or c¯ / c

0 > �:

This result and Proposition 2 imply that while it might be optimal to patent the initial inno-

vation, when we consider subsequent innovations, it is optimal not to patent.

4.2 The Role of Licensing

So far, we have not allowed the innovating institution (I) to patent and then share the innovation

through licensing. Licensing can potentially resolve the con�ict between increasing the market

size for the sequential innovation and capturing rents from it. We now examine the e¤ect on the

patenting decision when I can ex ante license the sequential innovation to the potential imitators

through �xed fees.

While, in practice, licensing can occur through both �xed fees and per unit licensing fees

that depend on output (see, e.g., Katz and Shapiro (1985)), the latter appear to be particularly

unsuitable in the �nancial world, because of prohibitive costs of monitoring output and antitrust

laws. Indeed, since the use of �nancial instruments and algorithms often occurs as part of complex

bilateral (provider-client) relationships that involve a variety of activities, it may be especially

problematic to write easily veri�able contracts based on output. Thus, we focus on �xed fee

licensing arrangements. Furthermore, we focus attention on the licensing of the second-generation

innovation, because I can not broaden the market for the higher-value second-generation innovation

without licensing its use.

Thus, if I patents at the initial date (i.e., P = 0) and the second-generation innovation is

realized at date t = 2, then I can license it to each of the N imitators, at the �xed fee of :

But although the licensees can o¤er the second-generation innovation, they still can not match

the quality of support and related services o¤ered by I: For parsimony, we model this asymmetry

23

through the assumption that for the same cost function (i.e., c(Q) = 12c0Q2), the licensees provide

a lower value to buyers from the second-generation innovation, namely, �� � > ��.

Clearly, the upper bound on the �xed fee is the incremental pro�t, at date t = 2, to each

licensee from the license� relative to o¤ering the �rst-generation innovation at the unit cost, c¯.

Note that any end user will purchase the second-generation innovation at price p2 from a licensee

only if �� �� p2 � (��� c¯): Thus, each licensee will segment its market, Z; into two components: a

segment S2 that receives the second-generation innovation at the price, p2 = �� � � (�� � c¯); and,

the remaining segment, Z � S2, that receives the �rst-generation innovation.

We let, �`�2 (P = 0); denote the pro�ts (of I) from patenting the sequence of innovations and

licensing the second-generation innovation at date t = 2. Now, S2 > 0 only if the pro�ts from

o¤ering the second-generation innovation exceed those from o¤ering the �rst-generation technology.

Intuition suggests that the pro�ts from the second-generation innovation will be increasing in the

incremental buyer utility provided by this innovation, relative to the �rst- generation product. That

is, the additional pro�ts from the second-generation innovation are positively associated with the

di¤erence, �� �� (��� c¯). The following result con�rms this intuition and shows that the licensing

of the second-generation innovation will not be feasible unless the incremental buyer value from

the new innovation is su¢ ciently large.

Proposition 6 If �� � > 3(�� � c¯), then,

S�2 =Min

�Z;�� � � (�� � c

¯)

c0

�(19)

Thus, under the parameterization at hand, the value provided by the licensees in providing the

second-generation innovation must be at least three times the net utility buyers can receive from

purchasing the �rst-generation derivatives at the competitive price of c¯:

Proposition 6 also allows us to compute the incremental pro�t to the licensees from the second-

generation innovation. Of course, this increment represents the maximum fee that I can charge for

the licensee, which we denote by � �. While the actual fee will lie between zero and � �, depending

on the relative bargaining strengths, we can certainly compute � �:

Proposition 7 If �� � > 3(�� � c¯), then, the upper bound on the license fee is:

� � =

8<:����(���c

¯)(����3(���c

¯))

2c0 if S�2 =����(���c

¯)

c0

Z[�� � � 2(�� � c¯)� Z

2c0 ] if S�2 = Z(20)

24

Of course, the requirement of a substantial buyer-value enhancement in the second-generation

innovation, i.e., � � � > 3(�� � c¯); is not a su¢ cient condition for the strategy of patenting and

licensing to dominate the no-patenting strategy. This is because if I does not patent (i.e., P = 1)

and induces the imitators to create a larger market, it can attempt to serve that market with

the second-generation innovation itself� as we have seen above� without sharing that market with

the licensees. Clearly, �`�2 (P = 0) � ��2(P = 0)+� �. Comparing this with the pro�ts from not

patenting (and hence also not licensing), i.e., ��2(P = 1); we get,

Proposition 8 ��2(P = 1) > �`�2 (P = 0) if the ratio M1=M0 and � are su¢ ciently large.

Of course, Proposition 8 is trivially true if � > � � 3(�� � c¯) and M1=M0 is su¢ ciently large.

In this case, non-patenting dominates patenting (see Proposition 1) and licensing is not feasible.

Interestingly, however, eschewing the patent may still dominate the patenting and licensing strategy

if � is su¢ ciently close to ��3(���c¯), because then � � is small. The economic interest of this result

is that using a licensing strategy to expand the market size for a sequence of innovations may not be

optimal if the licensees can not provide high-quality support and other services that enhance buyer-

value. In such a situation, the incremental value provided by the licensees through the advanced

innovations is small, and hence the licensing revenues available to the original innovator are also

small; if the innovator is also the high-quality service provider in the industry, then it may be

optimal for it keep the technology open, and serve the expanded market size (due to imitators)

with the next generations innovations itself at a higher price.

4.3 Relation to the Literature

Our model and the results we have developed above have a variety of links with the innovation

literature, some of which deserve explication. An important aspect of our analysis is that patenting

is not always optimal with �nancial innovations, and we clarify the conditions under which patenting

would or would not be optimal. Empirically, using a sample of non-�nancial innovations, Pakes and

Griliches (1980) �nd that there is considerable inter-industry heterogeneity in patenting policies

that can not be explained by variations in R&D. While there has been a paucity of empirical

work on �nancial patents, recent work by Lerner (2002, 2006) indicates that the determinants of

�nancial patents are complex and patenting patterns are only imperfectly correlated with innovation

patterns.

25

However, much of the earlier theoretical work on patents implies that patenting is always opti-

mal. In a notable exception to this rule, Horstmann et al. (1985) develop an asymmetric information

model in which the innovating �rm may optimally patent only a fraction of innovations, i.e., the

equilibrium propensity to patent lies between zero and one. But while the motivation for eschew-

ing patenting in their model is to reduce the transmission of the innovator�s private information

to competitors, in our model patenting may be sub-optimal even without information asymmetry.

Similarly, Bessen and Maskin (2000) argue that if innovations are complementary, then they can

increase industry pro�ts, and hence patenting may be sub-optimal. However, we consider a se-

quence of complementary innovations made by the high-quality provider, who may also license; we

therefore �nd that the optimal patenting and licensing policy is more complex.

Theoretical work on the determinants of �nancial patenting is relatively rare. Herrera and

Schroth (2002) present a model �nancial patents that emphasizes the �rst-mover aspects of �nancial

innovations in derivatives. Our model incorporates the �rst mover argument of Herrera and Schroth,

as a special case. While the institution may have a �rst mover advantage, the economic rents may

not be su¢ cient to justify the innovation in the absence of a patent. However, patenting may

not be optimal if the real bene�ts generated from subsequent innovations, depend on the size and

state of the market. The sequential nature of certain types of �nancial innovations is an issue not

addressed by Herrera and Schroth. The possible bene�ts to the institution are two fold: (a) the

rent generated by the initial innovation and (b) the options for further innovation, as it learns more

about the market for the initial innovation.

Gallini (1984) and Gallini and Winter (1985) consider the sharing of innovations in a search-

theoretic R & D model, and �nd that licensing always occurs in equilibrium. In a duopolistic

setting, Katz and Shapiro (1985) consider licensing of a cost-reducing innovation that is owned by

one of the producers, while Katz and Shapiro (1986) examines licensing by an upstream research

lab to a downstream oligopoly of identical producers. And Green and Scotchmer (1995) consider

the role of licensing in a model of sequential innovations when di¤erent �rms contribute to the

innovation sequence. Our analysis di¤ers from the existing licensing literature in considering the

role of licensing in expanding the market for a sequence of innovations, where the sole innovator is

also the high-quality service provider in the industry.

In our model, the innovation sequence improves the basic product (in terms of buyer value),

and hence is similar to the �quality ladder�formulation (see, e.g., Scotchmer (2004)). However, in

26

a pure quality ladder, each point in the sequence increases the product quality by a �xed amount,

while this is not the case in our model. More importantly, our model allows heterogeneous buyer

valuation of the innovation sequence, based on di¤erences in quality of supporting services, unlike

the quality ladder model where the quality superiority of the innovations is �xed for the industry

(e.g., O�Donoghue et al. (1998)).

5 Applications of the Model

The model developed in the last section can be expressed in the form

��0(P ) = PV0(P ) + PV0[option(P )] (21)

where for a given patenting policy denoted by the symbol P , the term PV0(P ) represents the

present value of the initial innovation and PV0[option(P )] the present value of options associated

with subsequent innovations that depend on the initial innovation. The model provides a framework

to assist executives in determining whether or not to patent an innovation. We now apply this model

to the examples considered in Section 3.2.

5.1 Case Study One: Swap Innovations

Consider the case of interest rate swaps. In the 1980�s, if the innovating institution had patented the

idea of an interest rate swap, preventing other institutions from competing23, then it must estimate

the present value of the cash �ows from marketing swaps to end users: (PV0(P = 0)). Central to

the analysis is an estimate of the size of the market (M0), the growth in the market24, the cost of

servicing each transaction (c¯) and the value added (��). The cost of the innovation (C0), depends

on the costs associated with designing the contract, addressing legal issues associated with the

exchange of cash �ows in the presence of counterparty risk, addressing regulatory issues, designing

the back o¢ ce, designing hedging strategies and having the sta¤ to run a swaps desk.

If the institution does not patent, then information about the swap contract and the potential

pro�ts will be disseminated, attracting other institutions (N) to enter the market, each able to

23The institution could have allowed other institutions to o¤er swaps under licensing agreements. This wouldhowever have hindered the development of the market. The pricing of the licensing agreement would also be an issue- see the discussion in Section 2.4.24 In the model developed in the last section, we did not address this issue in order to avoid complication.

27

reach a client base (Z). The operating cost per contract are (�c) and the value added (�). The

institution I is assumed to have an advantage in execution, at least over some initial period and

the value added to end users is (�� = � + �; � > 0). The size of the potential market has now

expanded to (M1 = M0 +NZ). The institution must estimate the present value of the cash �ows

in this more competitive environment. This is denoted by PV0(P = 1).

In the Herrera and Schroth (2002) analysis, it is argued that it is possible for PV0(P = 1) >

PV0(P = 0), implying that I may not require patent protection to recoup the costs of innovation.

For �nancial innovation involving �nancial instruments, the situation is usually more complicated.

It is possible for PV0(P = 1) < PV0(P = 0), yet it is still optimal for I not to seek patent

protection. The di¤erence arises from the present value of subsequent innovations motivated by

the initial innovation.

Here future innovations may take many forms. One example is instead of exchanging �xed

for �oating payments, exchange �oating for �oating payments referenced to two di¤erent interest

rates25. Another example would be to trade options on swaps. The success of future innovations

depends on the acceptance of the initial innovation. End users must be aware of the bene�ts of

using swaps. The size of the market a¤ects the liquidity of the market. If I had patented the

innovation, it reaches a market of size M0. This may a¤ect the costs of introducing new forms of

swaps, as it needs to educate end users about the merits of swaps, the liquidity of the swap market

may be quite limited, restricting its development. It also must address the legal and regulatory

issues that arise from the new forms of innovation.

If I had not patented the innovation, the size of the swap market will be enhanced and with

more end users there will be more knowledge about the product. Institutions in the swap market

will also learn from each other about the pricing and hedging of swaps26. Consequently, the costs

of introducing a new form of swap should be lower compared to the patent case: C2(P = 0) >

C2(P = 1). The institution I must estimate the present value of the option to undertake further

innovation: PV0[option(P )]. Therefore I is now in a position to calculate the net present value of

initial innovation plus the option for further innovation.

Note that in our model we assumed that I is the innovator for subsequent innovations. This is

not necessary. Usually there are a small number of leading institutions that act as market leaders,

25For example, exchange LIBOR payments for Federal Fund payments.26 In investment banking there is high mobility of labor, so knowledge is readily di¤used. There are also industry

publications and conferences resulting in the dissemination of knowledge.

28

each being able to capture some rent over some �nite period. The analysis can incorporate this

possibility. The analysis readily extends to cover the case of multiple innovations.

The analysis for credit default swaps is similar, so we omit the details.

5.2 Pricing Algorithms

This example is quite di¤erent in nature from the previous example. The algorithm could be for

pricing of options using simulation27 or it could be a risk model. For example, the RiskMetrics

algorithm �rst developed by J. P. Morgan for risk management or the risk model developed by

Lehman Brother for analyzing the risk characteristics of �xed income portfolios -see Naldi, Chu

and Wang (2002). To analyze this type of innovation, the �rst step is to identify the objectives of

the innovation project. If the pricing algorithm is developed to be part of a package of algorithms,

it is hoped that it increases the value added, (�), to end users. If the pricing algorithm is developed

to speed up pricing for, say, risk management, it helps to lower the cost per unit (c¯). In both

cases the option for further development may be non-existent. Patenting in either case provides a

barrier preventing competitors copying the innovation. The economic analysis is straight forward

in theory, if not in practice.

For the case of the algorithm being a risk model, we �rst consider the J. P. Morgan case.

Here the initial motivation for the innovation is dictated by the need to meet Basel I regulatory

requirements. It could either purchase the necessary software or develop in-house. The advantage

of a leading institution developing in-house is the �exibility it allows to incorporate new structures

into a risk management system28. Viewed in isolation, J. P. Morgan would have bene�tted from

obtaining a patent, as other institutions would be forced to bear the full costs of development:

PV0(P = 1) < PV0(P = 0). However, they did not apply for a patent (this was after the State

Street Decision), instead they followed a policy of full disclosure and became a market leader.

The option for further innovation in this case is to capitalize on the development of the software

by transferring it over to a separate risk management entity. This stand alone entity generates

revenue by providing risk management consulting to other institutions and corporations. By making

the development open and becoming an industry standard enhances the value of the option. In

this case PV0[option(P = 1)] > PV0[option(P = 0)].

27Patent 6,381,586, granted to International Business Machines, prices options using importance and strati�edsampling Monte Carlo simulation.28Software vendors can be quite tardy in responding to clients requests.

29

For the case of the algorithm being a risk model for �xed income securities, it is developed

as an aid to clients who manage their �xed income portfolios relative to one of the institution�s

bond indices. The bene�t to the institution is that it lowers the costs to their clients in managing

their portfolios and it is hoped that they will continue to use the institution for trading. To be

acceptable to clients, the model must be transparent, so details are public knowledge. A patent

may prevent competitors from developing similar models. Absent a patent, the institution still

has an advantage, because it has monopolistic access to the bond index data. The options for

further innovation might entail extending to risk model to the many di¤erent indices that are used

in practice.29

To undertake a formal analysis, the institution must quantify the bene�ts of the innovation, the

value of subsequent innovations and the e¤ects of patenting on these values. While this is extremely

di¢ cult, the analysis represented by expression (21) at least provides a framework.

6 Summary and Conclusions

Following the State Street Decision recognizing that business methods can be patented, there has

been a rapid growth in the �ling of patents for �nancial innovations. Moreover, the fact that

business methods can now be patented presents �nancial institutions with an option to obtain

patent protection for di¤erent types of �nancial innovations. However, the literature is only just

beginning to explore whether patent protection for �nancial innovations is warranted; this is an

important issue because �nancial innovations di¤er from innovations in other areas due to certain

market and regulation related aspects that are unique to the �nancial industry. In particular, public

exposure of innovations, ease of imitation, importance of educating end users, and leveraging on

the participation of other market makers to reduce the costs of adoption are some of the features

that are especially important in the industry.

We undertake a systematic review of the major characteristics of recent �nancial innovations.

We �nd that certain types of �nancial innovations have been successful because they were not

protected by patents and imitation was allowed. We identify the characteristics of such innovations

through a simple but illuminating model. Our analysis highlights the real options for subsequent

innovations and market expansion that are embedded in certain types of �nancial innovations as

the primary determinant of whether patent protection is warranted; furthermore, we also examine

29Many of these indices are designed to meet particular needs of a client.

30

the role of licensing in �nancial innovations. We then apply this model to a number of case studies

to show that it provides a framework to address the di¤erent characteristics of �nancial innovations

in order to reach a decision about the appropriate patenting decision.

To our knowledge, our paper is among the �rst analyses to systematically examine the determi-

nants of long-term pro�ts from �nancial innovation. This analysis is not only central to the optimal

patenting decision, but is also of independent interest as a model that characterizes �nancial inno-

vations in an industry equilibrium. Thus, our framework can be extended in a variety of directions

to examine the sources of competitive advantage in this important industry.

31

Appendix

Proof of Proposition 1 Put � � ��(���c)c0 : We want to �nd a set of additional conditions under

which L � ��2(P = 1) � ��2(P = 0) > 0: Let, � �h(�� � c)� c0M0

2

iM0: Then, under the conditions

annunciated in the Proposition, we can write

L =c0�2

2� c0�M0 � �

=c0

2[(� �M0)

2 �M20 � 2�=c0]

Let us �nd the critical value of � for which L = 0.

� �M0 = (+=�)(M20 + 2�=c

0)1=2

Now

M20 + 2(�=c

0) = M20 +

2

c0

�(�� � c)� c

0M0

2

�M0

=2

c0(�� � c)M0

Hence if,

� �M0 > [2

c0(�� � c)M0]

1=2; (22)

then L > 0: Thus, if M0 is su¢ ciently small then (22) will be satis�ed.

Proof of Corollary 1 In this parametric range, we have internal solutions to the pro�t maximizing

output condition in both cases: P = 0 or P = 1: This implies that

��2(P = 0) =1

2c0[�� (�� � c

¯)]2 + (�� � c

¯)M0

��2(P = 1) =1

2c0[�� (�� � c

¯)]2 (23)

Given that �� �c¯, then the result follows.

Proof of Proposition 2 Given the conditions of the Proposition, then as � > �c, if follows that

M1 � (�+ �c)=�c. This implies an interior solution, so that ��1(P = 1) = (�+ �c)2=�c. Hence

32

��1(P = 0)���1(P = 1) � [(�� + �)2 � (�+ �c)2]=�c > 0:

Proof of Proposition 3 For M0 = ", where " is a small number, it follows from (16) that

��1(P = 0) � ��". Meanwhile, for ZN � �+�cc¯, it follows from (13) that, ��1(P = 1) = (�+c)2

2c¯: Hence,

��1(P = 1)���1(P = 0) if we choose " �(�+c)2

2c¯�� :

Proof of Corollary 2 Follows immediately from Proposition 3 if we set M¯ 0

= (�+c)2

2c¯�� :

Proof of Proposition 4 The proof follows from Corollary 1 and Proposition 2.

Proof of Proposition 5 The proof follows from Proposition 3 and Corollary 2.

Proof of Proposition 6 Pick any licensee. Since p2 = �� �� (��� c¯), the optimal market size for

the second-generation market size is,

MaxfS2g

�[�� � � (�� � c

¯)]S2 �

1

2c0S22

�; s:t:; S2 � Z: (24)

The solution to this optimization exercise is given by Equation (19) in the Proposition. However, the licensee

has the choice to simply service his or her entire market with the �rst-generation innovation at a pro�t-margin

of (�� � c). Hence, we have to compare the pro�ts from o¤ering the second-generation innovation with that

from o¤ering only the �rst-generation innovation. Suppose, �rst, that, S�2 =����(���c

¯)

c0 : In this case, we

can readily compute,

�`�2 (P = 0) =[�� � � (�� � c

¯)]2

2c0+ (�� � c

¯)(Z � �� � � (�� � c¯)

c0) (25)

Straightforward computations then show that �`�2 (P = 0) > (�� � c¯)Z if �� � > 3(�� � c¯). Suppose,

next, that S�2 = Z: Then,

�`�2 (P = 0) = Z

��� � � (�� � c

¯)� c

0Z

2

�(26)

33

Hence,

�`�2 (P = 0)� (�� � c¯)Z = (Z=2)

�2(�� �)� 4(�� � c

¯)� c0Z

�= Z

��� � � 3(�� � c

¯) + (�� � � (�� � c

¯)� c

0Z

2)

�(27)

The second term in the R.H.S. of Equation (27) is positive because, by assumption, [����(���c¯)]

2c0 > Z:

Hence, �`�2 (P = 0) > (�� � c¯)Z; if �� � > 3(�� � c¯):

Proof of Proposition 7 The proof follows from Equations(25) and (27).

Proof of Proposition 8 From Proposition 1, we know that ��2(P = 1) > ��2(P = 0) if the ratio

M1=M0 is su¢ ciently large. Meanwhile, �`�2 (P = 0) # ��2(P = 0) as � becomes large (cf. Proposition

6).

34

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37

Table 1

Part A

Pre the State Street DecisionYear Total 705/35 36 37 38 705/4

1971 2 0 0 2 0 0

1972 2 0 0 0 1 1

1973 1 0 1 0 0 0

1974 0 0 0 0 0 0

1975 0 0 0 0 0 0

1976 1 0 1 0 0 0

1977 0 0 0 0 0 0

1978 0 0 0 0 0 0

1979 0 0 0 0 0 0

1980 2 0 0 0 2 0

1981 0 0 0 0 0 0

1982 2 0 2 0 0 0

1983 2 0 1 1 0 0

1984 0 0 0 0 0 0

1985 0 0 0 0 0 0

1986 3 0 3 0 0 0

1987 5 0 1 2 1 1

1988 13 3 3 2 4 1

1989 5 1 1 0 1 2

1990 8 0 2 4 1 1

1991 7 0 2 3 2 0

1992 11 3 4 3 0 1

1993 24 3 9 6 5 1

1994 9 1 0 5 1 2

1995 3 0 0 0 0 3

1996 10 0 1 4 1 4

1997 25 4 3 5 7 6

1998 67 16 17 13 8 13

Total 202 31 51 50 34 36

Part B

Post the State Street Decision

Year Total 705/35 36 37 38 705/4

1999 104 25 23 17 19 20

2000 134 38 29 33 16 18

2001 78 16 17 25 11 9

2002 72 15 18 22 7 10

2003 73 16 11 24 10 12

2004 26 2 5 11 2 6

Total 487 112 103 132 65 75

Table 2

Patents Awards: by Major Companies

(Excluding Financial Institutions)

1971 to 2004Company Major Finance Minor Finance Total

IBM 10 22 32

Hitachi 3 16 19

Reuters 13 0 13

Fujitsu 6 9 15

NCR 3 9 12

GE 7 1 8

Optimark 7 0 7

Casio 3 2 5

SUN 1 4 5

Xerox 2 3 5Main Finance: major classi�cation 705:/35/36/37/38/4

Minor Finance: minor classi�cation 705:/35/36/37/38/4

Table 3

Summary of Patent Awards

Patents Awards: to Financial Institutions

1971 to 2004Company Major Finance Minor Finance Total

Citigroup 15 11 26

Merrill Lynch 20 1 21

Walker Asset 3 3 6

Cantor Fitzgerald 4 0 4

Goldman Sachs 4 0 4

Thomson 2 2 4

American Express 2 1 3

College Saving Bank 3 0 3

Financial Engines 5 0 5

Foreign Exchange Transaction Services 3 0 3

Golden 1 Credit Union 3 0 3

Morgan Stanley 3 0 3

Capital One 2 0 2

Huntington Bancshares 2 1 3

Bank of America 1 0 1

Wells Fargo 1 0 0Main Finance: major classi�cation 705:/35/36/37/38/4

Minor Finance: minor classi�cation 705:/35/36/37/38/4

Table 4Types of Patents Held By Financial Institutions

Part A 705/35PatentNum-ber

Assignee Description

6,611,815 Lincoln National Life Insur-ance Co.

A data processing method for admin-istering an annuity product having aguarantee of lifetime payments.

6,799,167 Decision Analytics A bench mark portfolio is providedto be customizable to an investmentportfolio where the customization isdynamic.

6,766,303 Goldman Sachs & Co. A method for hedging a deferred com-pensation liability.

6,336,102 Wells Fargo InstitutionalTrust Company

Method and system for managementof an investment fund over a speci�edlife for that fund.

Part B 705/36

6,625,583 Goldman, Sachs, & Co. A computer implemented method forinteracting with a user of a tradingcomputer.

6,249,775 Chase Manhattan Bank, NewYork, NY

A method designed to improve analy-sis of past and future performance ofloan portfolios.

6,381,586 International Business Ma-chines Corporation

Pricing of options using importancesampling and strati�cation/QuasiMonte Carlo

6,092,056 Morgan Stanley dean Witter,New York, NY,

A data processing system and methodfor implementing and control of a �-nancial instrument which is listed fora period of time. The instrumentis based on an underlying basket ofstocks optimally selected to track anestablished capital market.

Part C 705/37

6,393,409 Morgan Stanley Dean Witter& Co.

Computer method and apparatus foroptimizing portfolios of multiple par-ticipants.

6,505,175 Goldman, Sachs & Co. A computerized order centric methodand system for tracking orders imple-mented on a trading �oor exchange.

6,269,346 Merrill Lynch A system and method for managing aplurality of stock option accounts eachfor a plurality of participants.

6,879,964 Vanguard Group, Inc. Investment company that issues aclass of conventional shares and a classof exchange traded shares in the samefund.

Part D 705/386,112,190 Citibank, N. A., New York,

NYA method and system for assimilatingdata, applying mechanisms, and emu-lating the though process of a credito¢ ce for commercial credit analysis

5,765,144 Merrill Lynch & Co., Inc A system for interactively interview-ing and educating a customer regard-ing their credit needs and the availableproducts.

5,696,907 General Electric Co. A method and system for performingrisk and credit analysis of �nancial ser-vice applications with a neural net-work.

6,405,181 NextCard, Inc. A system and method for providingreal time approval of credit over a net-work

Part E 705/45,884,274 Walker Asset Management Lt.

Partnership.A system and method for providinga foreign exchange insurance policythat determines a premium based ona number of risk factors.

5,819,230 HomeVest Financial Group,Inc.

A method and system for tracking andfunding asset purchase and insurancepolicy.

4,975,840 Lincoln National Risk Man-agement,Inc.

A method and apparatus for evaluat-ing a potential insurable risk.

5,970,464 International Business Ma-chines Corporation.

A computer implemented method ofunderwriting pro�tability analysis anddelivers the analytic process to a widecross section of insurance decisionmakers.