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57 Seiten, Note: 1,0
2. Related Literature and Hypothesis Development
2.1 Impact of Competition on Innovation
2.2 Moderating Effect of Age
3. Empirical Setting
3.1 Competition and Innovation in the Insurance Industry
3.2 New Market Entrants: InsurTech Startups
4. Data Sample, Method and Empirical Approach
4.1 Data Collection and Sample
4.2 Dependent Variable: Incumbents’ Innovativeness
4.2.1 Measuring Innovation in Financial Services
4.2.2 Coding Guidelines for Innovation Score
4.3 Independent Variable: Startup Entry
4.4 Control Variables
4.5 Research Design
5. Descriptive Statistics and Regression Model Results
5.1 Descriptive Statistics
5.2 Presentation of Results
5.2.1 Effect of Competition on Innovation
5.2.2 Effect of Age on Competition-Innovation Relationship
5.3 Additional Testing
This paper investigates the relationship between startup entrants and innovation behavior of incumbents. In specific, the insurance industry is empirically analyzed, since many technology driven insurance startups have recently entered this market. After an extensive literature review on the competition-innovation relationship, hypotheses are derived. In detail, it is expected that startup entry has a positive effect on the innovativeness of incumbents, and that this effect will eventually diminish with rising competition, therewith creating an inverted-U relationship. In addition, it is assumed that the positive effect of startup entry will be more impactful for younger incumbents. To evaluate these hypotheses, an innovation score is constructed based on companies’ annual reports. It measures innovation within six broad areas, ranging from organizational changes to new product launches. The population of this study incorporates 10 major insurance companies from Europe and the United States over a period from 2011 to 2015 and 244 InsurTech startups that entered the market in this observation period. In line with prior research, the evidence suggests that startup entrance has a curvilinear effect on incumbents’ innovativeness. Therewith, this study finds that the inverted-U relationship between competition and innovation holds, also when considering startup entry. Lastly, the findings suggest that the positive effect of startup entry is stronger for younger incumbents. In conclusion, an extensive understanding of the given relationship between startup entry and incumbents innovativeness is crucial for practitioners in order to further shift their mindset to a more proactive innovation behavior.
Keywords: Competition, Innovation, Startups, InsurTech
Esta tese investiga a relação entre startup entrants e comportamento de inovação das incumbentes. Especificamente, a indústria de seguros é empiricamente analisada, devido à entrada de várias technology driven insurance startups nos últimos anos . Após uma extensa literature review sobre a relação concorrência-inovação, algumas hipóteses são formuladas. É esperado que a entrada de startups tenha um efeito positivo na inovação das incumbentes e que esse efeito diminua com o aumento da concorrência, criando uma relação inverted-U. É assumido, também, que o efeito positivo da entrada de startups terá maior impacto nas incumbentes mais recentes. Para avaliar estas hipóteses, um score é construído com base nos relatórios anuais das empresas. O score mede a inovação em seis áreas distintas, incluindo mudanças organizacionais. A população deste estudo inclui 10 grandes empresas europeias e americanas no período de observação entre 2011 e 2015, e 244 startups InsurTech que entram no mercado durante o mesmo intervalo. Em linha com investigação anterior, as evidências sugerem que a entrada de startups tem um efeito curvilíneo na inovação das incumbentes. Assim, este estudo mostra que a relação inverted-U entre concorrência e inovação se verifica também quando nos referimos à entrada de startups. Finalmente, os resultados sugerem que o efeito positivo da entrada de startups é mais forte em incumbentes mais recentes. Em suma, compreender a relação entre a entrada de startups e a inovação das incumbentes é crucial para os practitioners, no sentido de mudar o seu mindset no que toca a um comportamento inovador mais proactivo.
I would first like to thank my thesis supervisor Professor Raffaele Conti. The door to Prof. Conti´s office was always open for questions about my research or writing. He allowed this paper to be my own work, but assisted with great guidance when I needed it. Thanks for all the valuable advice and insights given along the way.
Furthermore, I would also like to thank the correction readers, Alexandra Dzimiera and Sarah Gundlach, for their review and support, as well as Lourenço Pinto Leite for helping me translate the abstract into Portuguese.
Finally, I want to express my gratitude to my family and to my girlfriend for providing me with unfailing support and continuous encouragement throughout my years of study and through the process of researching and writing this thesis. This accomplishment would not have been possible without them.
Figure I: InsurTech Funding Volume and Deals (2011-2015)
Table I: InsurTech Segmentation
Table II: Innovation Areas of Insurance Companies
Table III: Descriptive Statistics of Data Sample
Table IV: Effect of Competition on Innovation
Table V: Moderating Effect of Age on Competition-Innovation Relationship
Table VI: Effect on differentiated Innovation Score Levers
Table VII: Lagged Regression Model
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The field of innovation is important for both practitioners and scholars. The Organisation for Economic Co-Operation and Development (OECD, 2007, p. 5) states that “innovation performance is a crucial determinant of competitiveness”. More recently, also the Boston Consulting Group´s (BCG, 2015) annual global survey of the state of innovation supports the importance of innovation, as 79 percent of the respondents’ ranked innovation as a top-three priority for their company.
Especially in industries with (rising) competition, innovation is considered a crucial activity in order to distinguish oneself from competition (e.g. Aghion et al., 2001). Still, evidence found in literature is contradictory as not all economic theories follow this positive competition-innovation relationship. For example, Schumpeter (1942) as well as Dixit and Stiglitz (1977) and Salop (1977) with their theories of industrial organization (IO) suggest that with rising competition, innovation should decline. Aghion et al. (2005) reconcile the opposing conceptions with their theoretical model explaining an inverted-U relationship between competition and innovation. Following their line of argumentation, two effects occur: First, when competition is rising an escape competition effect (positive effect of competition on innovation) motivates firms to innovate – as long as they can retrieve greater profits. Thereafter, the Schumpeterian effect (negative effect) dominates, when there is little incentive to innovate, because the potential rents attained by innovation diminish due to fierce competition.
Previous studies investigated the relationship between competition and innovation in different industry settings with established competition and most often focus exclusively on product innovation (e.g. Aghion et al., 2005; Bos et al., 2013; Hashmi, 2013). However, in an era of entrepreneurship as nowadays, also new market entrants could possibly impact established industry players. Consequently, it is of particular interest whether a similar innovation behavior is put forward by incumbents when they experience competition from startups entering the market. In summary, the aim of this thesis is to examine the impact of startup entrants on the innovativeness of incumbents. Therefore, I construct two hypotheses to test my assumptions. First, I hypothesize that the relationship between startup entry and incumbents innovativeness is curvilinear. Secondly, it is expected that the positive effect of entry will be stronger for younger incumbents.
The empirical setting is the insurance industry, as with the recent upraise of FinTechs – representing financial technology startups – a new layer of competition was introduced to the financial services sector. These predominantly young companies operate at the intersection of financial services and technology, offering existing financial services at lower cost and introducing new tech-driven solutions (PwC, 2016). More specifically, within the insurance industry a subset of specialized and technology-driven startups, called InsurTechs, are increasing competition (Institute of International Finance, 2016).
In order to test my hypotheses, I follow a method developed by Arnaboldi and Rossignoli (2015) to measure innovation in financial services based on annual reports, as traditional indicators like research and development (R&D) spending and patents are unlikely to be satisfactory for financial institutes given their rarity in reporting (Beck et al., 2016; Bos et al., 2013; Lerner, 2006). Consequently, an innovation score for the selected data sample of 10 major insurance companies across an observation period from 2011 to 2015 is created. The obtained information is merged with corresponding firm financials and data of 244 InsurTechs to perform an econometrical analysis.
The results generally support my hypotheses. In line with the existing literature on competition and innovation (Aghion et al. 2005; Bos et al., 2013), this paper finds evidence for an inverted-U relationship between new entrants and innovation. Thus, the entrance of startups positively affects incumbents’ innovation behavior – however only up to a certain level of competition, whereupon it diminishes. Concluding, it is in general beneficial for incumbents to be exposed to competition from new market entrants to foster innovation. These findings hold across different regressions. Finally, my results show that the positive effect of startup entry is stronger for younger incumbents.
The remainder of this thesis is structured as follows: Chapter 2 presents relevant academic research on the impact of competition on innovation. Based on this literature review two hypotheses are formulated. Chapter 3 introduces the empirical setting. Chapter 4 illustrates the data and explains the coding guidelines to evaluate companies’ innovativeness. The results are presented and discussed in chapter 5. Chapter 6 concludes this paper.
Since the aim of this paper is to investigate the influence of startup entrants on the innovativeness of incumbents, this section sets out the theoretical foundation on the effect of competition on innovation to derive my hypotheses. Further, also the incumbents’ age is taken into consideration as it might have a moderating effect on the competition-innovation relationship.
The impact of (more intense) competition on innovation and growth has been analyzed for decades, but remains puzzling (Aghion et al., 2005). The seminal work by Schumpeter (1942) argues that product market competition (PMC) discourages innovation, because of decreasing monopoly returns. Aghion and Howitt (1989) reinforce this logic: as the flow of rents for an incumbent is reduced when there is more PMC, its incentive to innovate should decrease alike. Similar conclusions are reached by Salop (1977) and Dixit and Stiglitz (1977) in their research on IO models of product differentiation and monopolistic competition. In the same way, R&D incentives are likely to be negatively influenced through weaker patent protection opportunities and easier imitation, as these levers shorten the expected duration of returns obtained from a certain innovation (Davidson & Segerstrom, 1998).
These models all predict that an incumbent monopolist is unlikely to innovate at all, as it already obtains monopoly rents due to its market power (Aghion & Howitt, 1989). Aghion et al. (2001) state that in Schumpeterian models innovation is rather realized by outsider firms who do not earn rents without innovating. However, in real economy most innovation activity is put forward within competitive industries and within incumbent companies that are already earning rents; thus PMC or an increase in PMC can stimulate innovation activities to increase profits (Aghion et al., 2001). The motivation to innovate in this setting is grounded in the intention to escape competition with neck-and-neck rivals, as pointed out by scholars such as Mookherjee and Ray (1991). These findings reconcile the Schumpeterian paradigm and suggest a positive impact of competition on innovation and firm growth. This positive relationship is further supported by the research of Nickell (1996) and Blundell et al. (1999), who revealed a positive linear influence of competition on innovation. Likewise, Theeke (2016) recently found that also the innovation breadth1 increases with rising market pressure (inter-firm as well as intra-firm competition).
Based on findings in the previous literature Aghion, et al. (2005) suggest a new theoretical model explaining an inverted-U relationship between competition and innovation. In addition, this inverted-U pattern was already recognized by Scherer (1967). The dynamics of the inverted-U shape can be explained as follows (Aghion et al., 2005): in the absence of product market competition, neck-and-neck firms have hardly any incentive to innovate, as they are already earning high rents. When competition is rising, there is an incentive for firms to innovate, as the rents for a leader are higher than for the other market participants. Like this, an industry spends the bulk of the time in an environment, which is characterized by the escape competition effect, with firms innovating in order to obtain the higher rents in a leader position. When competition reaches a sufficient level, Aghion et al. (2005) describe that the Schumpeterian effect or rent dissipation effect dominates thereafter. At the tipping point, competition is that high, that the laggard firms have comparably little incentive to innovate, because the potential rents attained by innovation are diminished by the fierce competition. Thus, the market remains in a state where leaders do not innovate as the Schumpeterian effect influences the laggard (Aghion et al., 2005).
More recently, Bos et al. (2013) analyzed the relationship of competition and innovation in the setting of financial services. Consistent with Aghion et al. (2005), they find that the theory of an inverted-U pattern also applies to the financial services industry. Once again, they point to the escape competition effect (positive effect of competition on innovation) and the Schumpeterian effect (negative effect). With regards to the competitive landscape in financial services they further depict that improvements in information processing capabilities of banks through advancements in information technology could tend to decrease competition because of favorable information asymmetries for certain institutions (Bos et al., 2013). Conversely, with an increased information dissemination due to information technology innovations, the competitive pressure could also increase as proprietary knowledge is more widely spread and accessible (Bos et al., 2013).
In this context, my work complements the existing research by considering startup entrants as new industry competitors. Based on the literature, I formulate my first hypothesis:
Hypothesis 1: Startup entry has a positive effect on the innovativeness of incumbents, which will diminish with rising competition, creating an inverted-U relationship (curvilinear).
In an environment with increasing competition not all companies react in the same way. Some firms are more likely to respond to competition than others. Thus, literature has been reviewed to evaluate the firm´s age as a possible moderating effect on the competition-innovation relationship. Here, the continuous moderating effect could possibly change the direction or strength of the actual relationship and thus needs to be taken into consideration (Hair et al., 2016).
Scholars usually find that younger firms seem better suited to detect new market and technological opportunities as they benefit from an impartial perspective (Coad et al., 2016). More importantly, thanks to their greater flexibility they can more likely capitalize on radical innovations, compared to older companies which are more tied to incremental innovation activities (Segarra & Teruel, 2014). Likewise, Sapienza et al. (2006) find that younger companies tend to adopt more novel approaches. Further, Sørensen and Stuart (2000) indicate that older firms, because of their greater inflexibility, are less likely to incorporate new technology advancements, thus being disadvantaged compared to the new competition. Here, the relative flexibility of younger companies enables a more rapid learning approach, which is necessary to survive in competitive environments and react to new market entrants (Autio et al., 2000). As companies grow older, Autio et al. (2000) propose that learning impediments will hamper the likelihood to respond successfully to changing environments. Here, established companies rather rely on their routines which ensures a constant and efficient output, but limits the organizational adaptability (Ahuja & Morris Lampert, 2001). Bierly and Chakrabarti (1996) support this line of reasoning, stating that organizational rigidity limits the flexibility of learning. At the same time, the ability to change of older companies itself can be limited by inertia (Coad et al., 2016; Sørensen and Stuart, 2000), which might be relevant to react to competition. In summary, this discussion demonstrates the tradeoff between efficiency (routine, repetitive tasks) and flexibility (non routine, innovative tasks) in organizational theory (Adler et al., 1999), considering changing industry environments and new competition.
In conclusion, younger incumbent firms seem more likely to still inherit a greater flexibility in comparison to their older peers, which makes them more responsive to changing competitive environments and thus to pursue innovation. Following, I formulate my second hypothesis:
Hypothesis 2: The positive effect of startup entry will be stronger for younger incumbents.
I will test my previously crafted hypotheses on the competition-innovation relationship in the insurance industry. This setting is of particular interest due to the recent upraise of technology driven insurance startups. In the following, I will introduce this research setting while highlighting industry characteristics and recent trends. Thereafter, InsurTech startups are characterized.
The global insurance industry accounts for four trillion US Dollars in total premium per year (Liam & Sen, 2016). Unlike many other industries, such as music and publishing, the insurance industry has been unaffected by the ongoing technological change for a long time. Thus, the business models have largely remained the same for the past 30 years (Liam & Sen, 2016). Even though the industry is mature, Liam and Sen (2016) state that it still inherits growth opportunities as e.g. in the United Kingdom (UK) where only 12 percent of people have an income protection insurance. At the same time insurance companies have grown more international over the past 50 years, making competition fiercer, as McKinsey & Company (2014) report for property-casualty carriers. On the other side, life insurance companies are also losing some revenue to alternative savings vehicles in the low interest-rate environment (McKinsey & Company, 2014).
Further, as more recently, new entrants try to disrupt the banking sector, also the insurance industry has gained more attention from entrepreneurs willing to found insurance related startups (Institute of International Finance, 2016). In line with the technological evolvement also customer expectations are changing and companies have to innovate (more) to stay competitive, as the shifting awareness of adopters could have long-reaching implications (Lerner & Tufano, 2011). By nature, this innovation impact can be radical, revolutionary or incremental (Gardner, 2009). In addition, the innovations can be categorized as: new products (e.g. cyber insurance), new services (e.g. digital agency), new “production” processes (e.g. electronic record keeping for securities) or new organizational forms (e.g. internet-only insurers) (Frame & White, 2004)2. This division is sustained by Lerner and Tufano (2011) for the financial services industry, who are also emphasizing the creation and popularization of new financial technologies and markets, besides the creation of new financial instruments, as elements of innovation. In general, scholars as Miller (1986) and Merton (1992) depict innovation of new products as facilitator for economic growth.
Accordingly, FinTechs could play a major role as catalyst for innovation in the financial service industry with the introduction of new technologies such as Robo-Advice3 or the creation of new markets, such as Peer-to-Peer (P2P) Insurance4, just to name a few. Here, these technology-based businesses can act as enabler or disruptor for the incumbents likewise (Pollari, 2016). Apart from that, insurance companies are also end users of innovation that has been produced by other industries, such as software. A recent example can be given by AXA5 who has partnered with Google Nest, a smart thermostat and smoke detector, for its home insurance segment to capitalize on the Nest product features (Sia Partners, 2016). However, it should be generally noted, that successful innovations in the financial services area are likely to be immediately replicated by peers (Laster & Raturi, 2002) – even if mechanisms to prevent imitation have been emphasized (Alnuaimi & George, 2016). The reason behind is, that protection via patent, copyright or informal protection like secrecy is hard to be enforced (Lerner, 2006).
In general, the claims of the beneficial impact of financial innovation must be seen with caution. One reason is the past financial crisis, where companies’ innovations, such as new products, were sold on false pretenses (Lerner & Tufano, 2011). Accordingly, innovation in financial services can be understood as a “double-edged sword” (Beck et al., 2016): In the traditional innovation-growth view, innovations help to improve quality and variety of services. By contrast, the innovation fragility view sees financial innovations as a major cause of the last financial crisis, through innovations that are not properly used.
Thus, the critical examination of the competition-innovation relationship in the insurance industry under consideration of startups as new market entrants is of particular relevance. To better understand the potential impact of InsurTechs on the innovativeness of incumbents in the insurance market, the next chapter introduces the InsurTech environment.
As previously mentioned, “InsurTech can be described as an insurance company, intermediary or insurance value chain segment specialist that utilizes technology to either compete or provide valued added benefits to the insurance industry” (Sia Partners, 2016, p. 2). Scott-Briggs (2016) emphasizes the focus and importance of the technological capabilities and customer centric approach of InsurTechs. It is a fast growing subsector of FinTech, an area that, in general, includes all technology-driven startups in the financial services sector (Scott-Briggs, 2016). Since 2012 the segment is gaining increasing traction with startups emerging as EY (2016) reports for the German insurance market.
Further, the viability of InsurTechs is described by the global funding volume and deal activity shown in figure I, as reported by CB Insights (2016)6. In 2015, the segment did account for $2.65 billion that where globally invested; an increase of 300 percent in terms of funding in comparison to the previous year.
Figure I: InsurTech Funding Volume and Deals (2011-2015) (Source: CB Insights 2016)
Abbildung in dieser Leseprobe nicht enthalten
While the United States (US) remain pioneers in InsurTech, its momentum is emerging on global scale, as in countries like the UK or Germany (Oliver Wyman & Policen Direkt, 2016). Further, the deal flow is moving from a focus on health insurance startups (70 percent in 2014) to the life and commercial insurance industry, representing 49 percent in US InsurTech Deals in 2015 (CB Insights, 2016). For 2016, an increase to 173 deals was reported (CB Insights, 2017). In conclusion, it can be said that InsurTechs are one of the rising stars in the FinTech area (EY, 2016).
The predominant drivers for the recent success of InsurTech are the developments in technology altering the nature of risk, therewith enabling new services, products and delivery channels. Second, the changing customer demands paired with the generally low customer engagement of the industry is in favor for the digital startups (Institute of International Finance, 2016). In summary, InsurTech arises from a combination of supply- and demand-driven financial innovations (García-Quevedo, Pellegrino, & Vivarelli, 2014). Besides innovations in data and mobile, the insurance industry is affected by technological developments in advanced sensors (Institute of International Finance, 2016). Startups with interdisciplinary backgrounds are likely to take advantage on incumbents in these areas, as they are more experienced in using and producing new technologies (Bottazzi, 2001). In addition to the relatively slow tech adoption in the insurance segment, it traditionally inherits low customer touch, which could be troubling in times of focused user experiences showcased by other industries (Institute of International Finance, 2016). Especially younger customers, called “millennials” or “digital natives” expect simplicity, speed and transparency of a service as well as a personalized experience, to name just a few attributes (Institute of International Finance, 2016; Tällt Ventures, 2016). Customers’ familiarity with technology emphasizes the need for an omni-channel communication and sales world – which amongst others – InsurTechs are able to fulfill, e.g. with insurance products embedded in third party online shops, as Simplesurnace7 is offering (Johansson & Vogelgesang, 2015). Similar customer-centric approaches are key successors in the changing insurance environment (Towers Watson, 2015). Likewise, Lerner and Tufano (2011) point out that innovation is driven by the dynamics of how products are accessed and used over time, reinforcing the importance of customer expectations.
To better understand the various application areas of InsurTech, I cluster them in the following. The variety of InsurTechs has been organized in several ways by practitioners (e.g. EY, 2016; Institute of International Finance, 2016; Tällt Ventures, 2016). I follow a segmentation in product, sales and operations by Oliver Wyman and Policien Direkt (2016) due to the straightforward trichotomy, which is easy to follow while drawing a light on the diverse areas of innovation in financial services. Each segment incorporates different subclasses as indicated by table I. Moving forward, I refer to some of the categories in more detail to show recent innovations.
Table I: InsurTech Segmentation (Source: adapted from Oliver Wyman & Policen Direkt, 2016)
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As shown, InsurTechs can differ from traditional insurance companies while introducing innovative products to the market. One example is the Internet of Things (IoT), a network of devices, which is monitoring, collecting and sharing stacks of data through the internet (Ng & Wakenshaw, 2017). These “smart” devices can range from home security systems over wearable health technologies to automobiles. These applications enable a more efficient risk modeling or product pricing on the basis of ongoing data reporting’s (Institute of International Finance, 2016; Lam & Sen, 2016). Another illustrative example are online P2P platforms in insurance, which enable a new ways of addressing customers and effectively servicing them, even though not fundamentally changing the core of insurance (Institute of International Finance, 2016). These P2P insurance startups either act as brokers or carriers. While a brokers’8 goal is to lower the insurance cost for their customers by pooling the policyholders together and leveraging their buying power, a P2P insurance carrier9 performs actual underwriting and sells own insurance policies direct-to-consumer. Guevara, an UK based car insurance network and Friendsurance, an actor in the German property insurance space, are two prominent use cases for P2P brokers. On average, they save their customers 50 respectively 33 percent premium per year, due to their innovative business model (Institute of International Finance, 2016). The first company in the P2P carrier space is the US-based Lemonade founded in 2015 and active in property and casualty insurance.
With respect to sales innovations “Next Generation Brokers” such as Clark, Knip or GetSafe are on the rise. These online/mobile-brokers attract customers due to their convenient and transparent handling as well as the value created that results from the identification of insurance gaps or duplicates and corresponding individual product offerings (Oliver Wyman & Policen Direkt, 2016). A recent evolvement in this segment is also the use of chatbots for real-time customer communication purposes as showcased by Spixii´s intelligent algorithm (Oliver Wyman & Policen Direkt, 2016). Lastly, also the cluster of operations experiences innovative solutions e.g. driven by big data. Here, product development could be improved with knowledge retrieved from the data analysis of customers´ online patterns. Likewise, big data could enable real-time underwritings and fraud pattern recognitions, which would increase the overall efficiency and reliability of the processes, just to give a glimpse of the possibilities (EY, 2016).
To subsume, business models of InsurTechs are predominantly centered around three entry points of incumbents´ businesses: (1) The replacement of infrastructure, (2) monetization of data and (3) disintermediation of value chain activities (EY, 2016). However, one should note that not only InsurTechs are capitalizing on these segments, but also incumbents are increasing their engagement.
Currently, practitioners´ assessment on whether InsurTechs will disrupt the industry or rather function as an enabler for insurers to become more customer-centric and agile diverges (Pollari, 2016). Disruptors are those InsurTechs that focus on core insurance functionalities such as policy and claims management or underwriting, with the goal of replacing incumbents (EY, 2016). On the contrary, PwC and Startupbootcamp10 (2016) state that the majority of new entrants are an enabling factor rather than a disruptive threat. In this perspective, the startups complement incumbents´ offerings in various ways e.g. while improving customer connectivity.
Either way, InsurTechs cultivate innovation in financial services with the introduction of new concepts in the insurance market. These are likely to lift the industry standards on a next level, because also the incumbents need to learn about the (digital) opportunities and should engage in the establishment of associated capabilities to stay competitive (EY, 2016). The question remains: How will this impact the innovativeness of incumbents?
Next, I present the research method applied in order to test my hypotheses later. I begin with a description of my data sample. Then I explain the methodology used to measure innovation in the context of financial services, to obtain my dependent variable. Finally, I refer to my independent variable of interest as well as some common determinants of innovation, which will be used as control variables in my research model which is designed thereafter.
I consider a list of the world´s top insurance companies ranked by total assets in 201511 (70 insurers) to select my sample (RelBank, 2015). From this list, I single out a subset of the ten largest insurance companies in Europe and the US12 and further exclude possible firm conglomerates13. Thus, my data sample includes the following constituents: AIG (US), Allianz (Germany), Assicurazioni Generali (Italy), Aviva (UK), AXA (France), Legal & General (UK), MetLife (US), Munich Re (Germany), Prudential (UK) and Prudential Financial (US).
In a first step, I attempt to assess their innovativeness between the years of 2011 to 2015, as described later. The sample period starting in 2011 is grounded in the time when InsurTechs increasingly gained recognition (EY, 2016) and last to the year for which annual reports were available (2015) when conducting the research. These information, as well as firm financials are based on secondary data available at Thomson Reuters. I include data for variables such as size, age, leverage and profitability of each company in the dataset. The gross domestic product (GDP) was obtained by World Bank. No missing values were recognized, leading to an outright dataset.
In parallel, I construct a separate data base including 244 InsurTechs (Appendix VI), who entered the insurance sector in the observation period all over the world. Like EY (2016), I consider the following selection criteria: recently founded by independent partners (not as direct or indirect spin-off), active insurance related offering and market entry before 2016. I populated this list of startups compiling different sources, as there is no comprehensive data base on InsurTech startups existent yet. Subsequently, several expert publications such as the FinTech100 (H2 Ventures & KPMG, 2016), the Insurance Distribution Report (Tällt Ventures, 2016), zeb.Innovationsradar (zeb, 2016) and the InsurTech Radar by Policien and Oliver Wyman (2016) where combined with an extensive data export on insurance related startups from crunchbase14. The data was validated across the different sources and checked for duplicates. Finally, I merged both data stacks to create a comprehensive data sample expedient for my research purpose.
A major challenge that confronts research is the complexity of measuring financial innovation, which is predominantly caused by the paucity of data (Frame & White, 2004; Lerner, 2006). Whilst studies of innovation in manufacturing traditionally use R&D spending and patents as an indicator for innovation, these measures are unlikely to be satisfactory for financial institutes, given their rarity in reporting (Beck et al., 2016; Bos et al., 2013; Lerner, 2006). In addition, also patents are used infrequently for financial innovations (Lerner, 2002) or are not even available as in the European Union (Beck et al., 2016). In consequence, the majority of existing studies draw attention to specific innovations such as new organizational forms (e.g. DeYoung, 2005; DeYoung et al., 2007) or new forms of financial securities (Grinblatt & Longstaff, 2000; Henderson & Pearson, 2011). However, Lerner and Tufano (2011) point out that alternatives like the listings of new securities also remain troubling as much of the innovation in financial services is outside the publicly traded securities, and that “novel” securities are often only minor variants of existing securities (Tufano, 2003). Lerner (2006) is trying to address this gap by measuring financial innovation based on news items in the Wall Street Journal. Still, it may be, that some innovations are not pictured in newspaper because of a missing direct impact and thus interest to the reader.
By contrast, Bos et al. (2013) developed another model indicating a technology gap to measure innovation whilst examining the capability to abate cost through innovation. Recently, Arnaboldi and Rossignoli (2015) developed an alternative measure for financial innovation based on annual reports. I will follow their methodology as the annual report represents the main official document of a company disclosed to the general public. Therefore, it offers a reasonable basis to analyze and the accuracy of information provided is ensured by the authorities, who have changed accounting rules in favor of investors (Lehnert, 2014). In the following, the methodology will be explained.
1 Innovation breadth represents the elements used to develop an innovation. Expanding the breadth of elements could further successful innovation activities of a company.
2 A similar declaration of innovation types is also provided in the Oslo Manual (OECD, 2005).
3 Creation and management of investment portfolios using automation and digital techniques (Accenture, 2015).
4 A group of like-minded individuals (peers) pool their premiums together to insure against a risk. This risk sharing network enables insurance firms to pool capital more cost-effectively and policyholders to save significantly by keeping claims low (Institute of International Finance, 2016).
5 AXA Group is a worldwide leader in financial protection and was the largest insurance group 2015 (AXA, 2015).
6 CB Insights is a venture capital and angel investment database predicting technology trends.
7 Simplesurance is a Berlin based e-commerce provider for product insurances using proprietary software.
8 Here the premium is split to a mutual pool, covering minor losses and a standard insurance. If only few claims are filed, remaining funds are returned; other the traditional insurance covers.
9 Here the capital reserves are also funded by investors, who split the remaining balance of the premium pool after all claims have been processed.
10 Startupbootcamp InsurTech is a leading accelerator with focus on financial innovation based in London.
11 The Top 10 includes two US, three UK companies and companies from France, Germany, Japan and China.
12 Amongst other, this is based on the regional InsurTech cluster as displayed in Appendix I.
13 Berkshire Hathaway was excluded from the selection as it is a conglomerate of more than 80 different companies.
14 Crunchbase is a leading database of innovative Web2.0 companies, personalities and investors.
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Masterarbeit, 78 Seiten
Doktorarbeit / Dissertation, 111 Seiten
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