People of my generation, like those before us no doubt, like to moan on about the quality of modern music. When I look back at the diversity of the music from the 1980’s that I grew up listening to, I cannot but help feel that this generation is missing out.
As it happens, the 2018 Global Music Report from IFPI indicated that the multi-year decline in global music revenues has bottomed out. The 2017 industry revenues grew by 8% over 2016, with streaming revenues up 41%. This represents three consecutive years of growth after many years of decline. The music sector is one of the earliest examples of the awesome creative destructive ability of the digital revolution, as the graph below shows.
click to enlarge
The physical, digital and streaming revenues are obvious (e.g. CDs & vinyl, downloads & streaming). Performance rights includes the revenues generated by the use of recorded music by broadcasters and public venues. Synchronisation revenues include the revenues from the use of music in advertising, film, games and television programmes.
As a regular theme of this blog is the impact of the digital revolution under way on so many industries and the need for sectors to adapt through digital transformation of their business models, the graph above is both thought provoking and scary.
Listening to the investment pitch by Spotify this week over the future of the sector, I can’t but help think that the democratisation and disintermediation promised by the internet age has resulted, for the music sector at least, in dominant players dictating homogeneous tastes and culture. The death of individualism seems to be the result, at least until this or future generations get fed up with it.
Posted in General
Tagged 2020 projections, advertising, creative destructive, death of individualism, democratisation, digital revolution, digital transformation, disintermediation, diversity, film, games, Generational Music, Global Music Report, homogeneous culture, IFPI, modern music, music digital revenues, music industry revenues, music sector, performance rights, RIAA, Spotify, streaming revenue, synchronisation revenues, television, vinyl records
The digital transformation of existing business models is a theme of our age. Robotic process automation (RPA) is one of the many acronyms to have found its way into the terminology of businesses today. I highlighted the potential for telecoms to digitalise their business models in this post. Klaus Schwab of the World Economic Forum in his book “Fourth Industrial Revolution” refers to the current era as one whereby “new technologies that are fusing the physical, digital and biological worlds, impacting all disciplines, economies and industries, and even challenging ideas about what it means to be human”.
The financial services business is one that is regularly touted as been rife for transformation with fintech being the much-hyped buzz word. I last posted here and here on fintech and insurtech, the use of technology innovations designed to squeeze out savings and efficiency from existing insurance business models.
Artificial intelligence (AI) is used as an umbrella term for everything from process automation, to robotics and to machine learning. As referred to in this post on equity markets, the Financial Stability Board (FSB) released a report called “Artificial Intelligence and Machine Learning in Financial Services” in November 2017. In relation to insurance, the FSB report highlights that “some insurance companies are actively using machine learning to improve the pricing or marketing of insurance products by incorporating real-time, highly granular data, such as online shopping behaviour or telemetrics (sensors in connected devices, such as car odometers)”. Other areas highlighted include machine learning techniques in claims processing and the preventative benefits of remote sensors connected through the internet of things. Consultants are falling over themselves to get on the bandwagon as reports from the likes of Deloitte, EY, PwC, Capgemini, and Accenture illustrate.
One of the better recent reports on the topic is this one from the reinsurer SCOR. CEO Denis Kessler states that “information is becoming a commodity, and AI will enable us to process all of it” and that “AI and data will take us into a world of ex-ante predictability and ex-post monitoring, which will change the way risks are observed, carried, realized and settled”. Kessler believes that AI will impact the insurance sector in 3 ways:
- Reducing information asymmetry and bringing comprehensive and dynamic observability in the insurance transaction,
- Improving efficiencies and insurance product innovation, and
- Creating new “intrinsic“ AI risks.
I found one article in the SCOR report by Nicolas Miailhe of the Future Society at the Harvard Kennedy School particularly interesting. Whilst talking about the overall AI market, Miailhe states that “the general consensus remains that the market is on the brink of a revolution, which will be characterized by an asymmetric global oligopoly” and the “market is qualified as oligopolistic because of the association between the scale effects and network effects which drive concentration”. When referring to an oligopoly, Miailhe highlights two global blocks – GAFA (Google/Apple/Facebook/Amazon) and BATX (Baidu/Alibaba/Tencent/Xiaomi). In the insurance context, Miailhe states that “more often than not, this will mean that the insured must relinquish control, and at times, the ownership of data” and that “the delivery of these new services will intrude heavily on privacy”.
At a more mundane level, Miailhe highlights the difficulty for stakeholders such as auditors and regulators to understand the business models of the future which “delegate the risk-profiling process to computer systems that run software based on “black box” algorithms”. Miailhe also cautions that bias can infiltrate algorithms as “algorithms are written by people, and machine-learning algorithms adjust what they do according to people’s behaviour”.
In a statement that seems particularly relevant today in terms of the current issue around Facebook and data privacy, Miailhe warns that “the issues of auditability, certification and tension between transparency and competitive dynamics are becoming apparent and will play a key role in facilitating or hindering the dissemination of AI systems”.
Now, that’s not something you’ll hear from the usual cheer leaders.
Posted in Insurance Market
Tagged Accenture, AI, AI systems, algorithm bias, Alibaba, Amazon, Apple, Artificial Insurance, artificial intelligence, asymmetric global oligopoly, auditability, Baidu, Capgemini, claims processing, competitive dynamics, Deloitte, Denis Kessler, digital transformation, ex-ante predictability, ex-post monitoring, EY, Facebook, Financial Stability Board, fintech, Fourth Industrial Revolution, Future Society, Google, granular data, Harvard Kennedy School, improving efficiencies, information asymmetry, information commodity, insurance Innovation, insurance sector, InsurTech, internet of things, Klaus Schwab, machine learning, machine learning algorithms, machine learning techniques, new AI risks, Nicolas Miailhe, product innovation, PwC, robotic process automation, robotics, SCOR, telemetrics, Tencent, transparency, Xiaomi