The exponential digital social world

The exponential digital social world

Tech-savvy start-ups with natively digital business models regard this point in time as the best time in the history of the world to invent something. The world is buzzing with technology-driven opportunities leveraging the solid platform provided over the past 30 years, birthed from

  • the Internet,
  • then mobility,
  • social
  • and now the massive scale of cloud computing and the Internet of Things (IoT).

For the start-up community, this is a

  • platform for invention,
  • coupled with lowered / disrupted barriers,
  • access to venture capital,
  • better risk / benefit ratios
  • and higher returns through organisational agility.

Kevin Kelly, co-founder of Wired magazine believes we are poised to create truly great things and that what’s coming is exponentially different, beyond what we envisage today – ‘Today truly is a wide open frontier. We are all becoming. It is the best time ever in human history to begin’ (June 2016). Throughout history, there have been major economic and societal shifts and the revolutionary nature of these is only apparent retrospectively – at the time the changes were experienced as linear and evolutionary. But now is different. Information access is globalised and is seen as a democratic right for first world citizens and a human right for the less advantaged.

The genesis was the Internet and the scale is now exponential because cloud-based platforms embed connections between data, people and things into the very fabric of business and daily life. Economies are information and services-based and knowledge is a valued currency. This plays out at a global, regional, community and household level. Pro-active leaders of governments, businesses and communities addressing these trends stress the need for innovation and transformative change (vs incremental) to shape future economies and societies across the next few years. In a far reaching example of transformative vision and action, Japan is undertaking ‘Society 5.0’, a full national transformation strategy including policy, national digitisation projects and deep cultural changes. Society 5.0 sits atop a model of five waves of societal evolution to a ‘super smart society’. The ultimate state (5.0) is achieved through applying technological advancements to enrich the opportunities, knowledge and quality of life for people of all ages and abilities.

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The Society 5.0 collaboration goes further than the digitisation of individual businesses and the economy, it includes all levels of the Japanese society, and the transformation of society itself. Society 5.0 is a framework to tackle several macro challenges that are amplified in Japan, such as an ageing population – today, 26.3% of the Japanese population is over 65, for the rest of the world, 20% of people will be over 60 by 2020. Japan is responding through the digitisation of healthcare systems and solutions. The increased mobility and flexibility of work to keep people engaged in meaningful employment, and the digitisation of social infrastructure across communities and into homes. This journey is paved with important technology-enabled advances, such as

  • IoT,
  • robotics,
  • artificial intelligence,
  • virtual and augmented reality,
  • big data analytics
  • and the integration of cyber and physical systems.

Japan’s transformation approach is about more than embracing digital, it navigates the perfect storm of technology change and profound changes in culture, society and business models. Globally, we are all facing four convergent forces that are shaping the fabric of 21st century life.

  • It’s the digital social world – engaging meaningfully with people matters, not merely transacting
  • Generational tipping point – millennials now have the numbers as consumers and workers, their value systems and ways of doing and being are profoundly different
  • Business models – your value chain is no longer linear, you are becoming either an ecosystem platform or a player / supplier into that ecosystem
  • Digital is ubiquitous – like particles in the atmosphere, digital is all around us, connecting people, data and things – it’s the essence of 21st century endeavours

How do leaders of our iconic, successful industrial era businesses view this landscape? Leaders across organisations, governments and communities are alert to the opportunities and threats from an always on economy. Not all leaders are confident they have a cohesive strategy and the right resources to execute a transformative plan for success in this new economy of knowledge, digital systems and the associated intangible assets – the digital social era. RocketSpace, a global ecosystem providing a network of campuses for start-up acceleration, estimate that 10 years from now, in 2027, 75% of today’s S&P 500 will be replaced by digital start-ups (RocketSpace Disruption Brief, March 2017). Even accounting for some potential skew in this estimate, we are in the midst of unprecedented change.

What is change about?

What are the strategic assets and capabilities that an organisation needs to have when bridging from the analogue to the digital world? Key to succeeding in this is taking the culture and business models behind successful start-ups and imbuing them into the mature enterprise. Organisations need to employ outside-in, stakeholder-centric design-thinking and adopt leveraged business models that create

  • scaled resources,
  • agility,
  • diversity of ideas

and headspace to

  • explore,
  • experiment,
  • fail and try again.

The need to protect existing assets and sources of value creation remains important. However, what drives value is changing, so a revaluation of portfolios is needed against a new balance sheet, the digital social balance sheet.

The Dimension Data Digital Social Balance Sheet evolved from analysing transformational activities with our global clients from the S&P500, the government sector, education and public health sectors and not-for-profits. We also learnt from collaborations with tech start-ups and our parent company, Nippon Telegraph and Telephone Group’s (NTT) R&D investment activities, where they create collaborative ecosystems referred to as B2B2X. The balance sheet represents the seven top level strategic capabilities driving business value creation in the digital social era. This holds across all industries, though it may be expressed differently and have different relative emphasis for various sectors – for example, stakeholders may include employees, partners, e-lance collaborators, customers, patients, shareholders or a congregation.

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Across each capability we have defined five levels of maturity and this extends the balance sheet into the Dimension Data Digital Enterprise Capability Maturity Model. This is an holistic, globally standardised framework. From this innovative tool, organisations can

  • assess themselves today,
  • specify their target state,
  • conduct competitive benchmarking,
  • and map out a clear pathway of transitions for their business and stakeholders.

The framework can also be applied to construct your digital balance sheet reporting – values and measures can be monitored against organisational objectives.

Where does your organisation sit? Thinking about your best and worst experiences with a business or government organisation this year, what is revealed about their capabilities? Across each of the pillars of this model, technology is a foundation and an enabler of progressive maturity. For example, effective data architecture and data management platforming underpins the information value capability of responsiveness. A meaningful capability will be enabled by the virtual integration of hybrid data sources (internal systems, external systems, machines, sensors, social) for enhanced perception, discovery, insight and action by both knowledge workers and AI agents. Uber is a leading innovator in this, and is also applying deep learning, to predict demand and direct supply, not just in time, but just before time. In this, they are exploring beyond today’s proven and mainstream capabilities to generate unique business value.

Below is a high level assessment of three leading digitals at this point in their business evolution – Uber, Alibaba and the Estonian government. We infer their capabilities from our research of their organisational journeys and milestones, using published material such as articles and case studies, as well as our personal experiences engaging with their platforms. Note that each of these businesses’ capabilities are roughly in alignment across the seven pillars – this is key to sustainable value creation. For example, an updated online presence aimed at improving user experience delivers limited value if not integrated in real time across all channels, with information leveraged to learn and deepen engagement and processes designed around user context, able to adapt to fulfil the point in time need.

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Innovation horizons

In the model below, key technology trends are shown. We have set out a view of their progression to exponential breakthrough (x axis) and the points at which these technologies will reach the peak of the adoption curve, flipping from early to late adopters (y axis). Relating this to the Digital Enterprise Capability Maturity Model, level 1 and 2 capabilities derive from what are now mature foundations (past). Level 3 aligns with what is different and has already achieved the exponential breakthrough point. Progressing to level 4 requires a preparedness to innovate and experiment with what is different and beyond. Level 5 entails an appetite to be a first mover, experimenting with technologies that will not be commercial for five to ten years, but potentially provide significant first mover advantage. This is where innovators such as Elon Musk’s horizons are set with Tesla and SpaceX.

An example of all of this coming together at level 3 of digital capability maturity and the different horizon – involving cloud, mobility, big data, analytics, IoT and cybersecurity – to enable a business to transform, is Amoury Sport Organisation (A.S.O.) and their running of the Tour de France. The Tour was conceived in 1903 as an event to promote and sell A.S.O.’s publications and is today the most watched annual sporting event in the world. Spectators, athletes and coaches are hungry for details and insights into the race and the athletes. Starting from the 2015 Tour, A.S.O. has leapt forward as a digital business. Data collected from sensors connected to the cyclist’s bike is aggregated on a secure, cloud-based, big data platform, analysed in real time and turned into entertaining insights and valuable performance statistics for followers and stakeholders of the Tour. This has opened up new avenues of monetisation for A.S.O. Dimension Data is the technology services partner enabling this IoT-based business platform.

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If your organisation is not yet on the technology transformation path, consider starting now. For business to prosper from the digital economy, you must be platformed to enable success – ready and capable to seamlessly connect humans, machines and data and to assure secure ecosystem flows. The settings of our homes, cars, schools and learning institutions, health and fitness establishments, offices, cities, retail outlets, factories, defence forces, emergency services, logistics providers and other services are all becoming forever different in this digital atmosphere.

Where is your innovation horizon set? The majority of our co-innovation agendas with our clients are focused on the beyond horizons. In relation to this, we see four pairs of interlinked technologies being most impactful

  • artificial intelligence and robotics;
  • virtual/ augmented reality and the human machine interface;
  • nano-technology and 3D/4D printing,
  • and cybersecurity and the blockchain.

Artificial intelligence and robotics

Artificial intelligence (AI) is both a science and set of technologies inspired by the way humans sense, perceive, learn, reason, and act.

We are rapidly consuming AI and embedding it into our daily living, taking it for granted. Think about how we rely upon GPS and location services, use Google for knowledge, expect Facebook to identify and tag faces, ask Amazon to recommend a good read and Spotify to generate a personalised music list, not so long ago, these technologies were awe-inspiring.

Now, and into the next 15 years, there is an AI revolution underway, a constellation of different technologies coming together to propel AI forward as a central force in society. Our relationships with machines will become more nuanced and personalised. There’s a lot to contemplate here. We really are at a juncture where discussion is needed at all levels about the ways that we will and won’t deploy AI to promote democracy and prosperity and equitably share the wealth created from it.

The areas in which this will have the fastest impact are transportation, traditional employment and workplaces, the home, healthcare, education, public safety and security and entertainment. Let’s look at examples from some of these settings:

Transportation – Autonomous vehicles encapsulate IoT, all forms of machine learning, computer vision and also robotics. This will soon break through the exponential point, once the physical hardware systems are robust enough.

Healthcare – there is significant potential for use of AI in pure and applied research and healthcare service delivery, as well as aged and disability related services. The collection of data from clinical equipment e.g. MRI scanners and surgical robots, clinical electronic health records, facility-based room sensors, personal monitoring devices, and mobile apps is allowing for more complete digital health records to be compiled. Analysis of these records will evolve clinical understandings. For example, NTT Data provides a Unified Clinical Archive Service for radiologists, providing machine learning interpretation of MRI brain imagery. The service provides digital translations of MRI brain scans and contains complete data sets of normal brain functions (gathered from John Hopkins University in the US). Radiologists are able to quantitatively evaluate their patient results with the normal population to improve diagnostics. Each new dataset adds to the ecosystem of knowledge.

Education – AI promises to enhance education at all levels, particularly in providing personalisation at scale for all learners. Interactive machine tutors are now being matched to students. Learning analytics can detect how a student is feeling, how they will perform and what the best likely interventions to improve learning outcomes are. Online learning has also enabled great teachers to boost their class numbers to worldwide audiences, while at the same time, student’s individual learning needs can be augmented through analysis of their response to the global mentor. Postgraduate and professional learning is set to become more modular and flexible, with AI used to assess current skills and work related projects and match learning modules of most immediate career value – an assemble your own degree approach. Virtual reality along with AI, is also changing learning content and pathways to mastery, and so will be highly impactful. AI will never replace good teaching, and so the meaningful integration of AI with face-to-face teaching will be key.

Public safety and securityCybersecurity is a key area for applied AI. Machine learning from AI against the datasets from ubiquitously placed cameras and drones for surveillance is a key area. In areas of tax, financial services, insurance and international policing, algorithms are improving the conduct of fraud investigations. A significant driver for advances in deep learning, particularly in video and audio processing has come off the back of anti-terrorist analytics. All of these things are now coming together in emergency response planning and orchestration and in the emerging field of predictive policing.

Virtual reality/augmented reality and the human machine interface

The lines between the physical and digital worlds are merging, along the ‘virtuality’ continuum of augmented and virtual reality. Augmented reality (AR) technologies overlay digital information on the ‘real world’, the digital information is delivered via a mechanism, such as a heads-up display, smart glass wall or wrist display. Virtual reality (VR) immerses a person in an artificial environment where they interact with data, their visual senses (and others) controlled by the VR system. Augmented virtuality blends AR and VR. As virtuality becomes part of our daily lives, the way we will interact with each other, learn, work, and transact are being re-shaped.

At the 2017 NTT R&D Fair in Tokyo, the use of VR in sports coaching and the spectator experience was showcased, with participants able to experience playing against elite tennis and baseball players and riding in the Tour de France. A VR spectator experience also enabled the direct experience the rider’s view and the sensation of the rider’s heart rate and fatigue levels. These applications of VR and AI are being rapidly incorporated into sports analytics and coaching.

Other enterprise VR use cases include

  • teaching peacekeeping skills to troops in conflict zones,
  • the creation of travel adventures,
  • immersion in snowy climate terrain to reduce pain for burn victims,
  • teaching autistic teenagers to drive,
  • and 3D visualisations of organs prior to conducting surgery.

It isn’t hard to imagine the impact on educational and therapeutic services, government service delivery, a shopping experience, on social and cultural immersion for remote communities and on future business process design and product engineering.

Your transformation journey

Every business is becoming a digital business. Some businesses are being caught off guard by the pace and nature of change. They are finding themselves reactive, pulled into the digital social world by the forces of disruption and the new rules of engagement set by clients, consumers, partners, workers and competitors. Getting on the front foot is important in order to control your destiny and assure future success. The disruptive forces upon us present opportunities to create a new future and value for your organisation and stakeholders. There are also risks, but the risk management approach of doing nothing is not viable in these times.

Perhaps your boardroom and executive discussions need to step back from thinking about the evolution of the current business and think in an unconstrained ‘the art of possible’ manner as to the impact of the global digital disruption and sources of value creation into the future. What are the opportunities, threats and risks that these provide? What is in the best interests of the shareholders? How will you retain and improve your sector competitiveness and use digital to diversify?

Is a new industry play now possible? Is your transformed digital business creating the ecosystem (acting as a platform business) or operating within another? How will it drive the business outcomes and value you expect and some that you haven’t envisaged at this point?

The digital balance sheet and seven pillars of digital enterprise capability could be used as the paving blocks for your pathway from analogue to digital. The framework can also guide and measure your progressive journey.

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Our experiences with our clients globally show us that the transformation journey is most effective when executed across three horizons of change. Effective three step horizon planning follows a pattern for course charting, with a general flow of:

  1. Establish – laying out the digital fabric to create the core building blocks for the business and executing the must do/no regret changes that will uplift and even out capability maturity to a minimum of level 2.
  2. Extend – creating an agile, cross-functional and collaborative capability across the business and executing a range of innovation experiments that create options, in parallel with the key transformative moves.
  3. Enhance – embedding the digital social balance sheet into ‘business as usual’, and particularly imbuing innovation to continuously monitor, renew and grow the organisation’s assets.

In this, there are complexities and nuances of the change, including:

  • Re-balancing of the risk vs opportunity appetite from the board
  • Acceptable ROI models
  • The ability of the organisation to absorb change
  • Dependencies across and within the balance sheet pillars
  • Maintaining transitional balance across the pillars
  • Managing finite resources – achieving operational cost savings to enable the innovation investment required to achieve the target state

The horizon plans also need to have flex – so that pace and fidelity can be dialled up or down to respond to ongoing disruption and the dynamic operational context of your organisation.

Don’t turn away from analogue wisdom, this is an advantage. Born-digital enterprises don’t have established physical channels and presence, have not experienced economic cycles and lack longitudinal wisdom. By valuing analogue experience and also embracing the essence of outside-in thinking and the new digital social business models, the executive can confidently execute.

A key learning is that the journey is also the destination – by

  • mobilising cross functional teams,
  • drawing on diverse skills and perspectives,

empowered to act using quality information that is meaningful to them – this uplifts your organisational capabilities and in itself will become one of your most valuable assets.

Click here to access Dimension Data’s detailed study

Can Data and Technology Support the Insurance Industry to Regain Lost Relevance?

Since the start of the Third Industrial Revolution in the 1980s, the world has changed in many different ways:

  • rapid introduction and adoption of technological innovation (global internet; social networks; mobile technologies; evolving payment solutions; data availability);
  • new economic realities (volatile and shorter economic cycles; interconnected financial climate; under utilisation of assets);
  • structural shifts in society’s values (desire for community; generational altruism; active citizenship);
  • and demographic readjustment (increasing population; urbanization; longer life expectancy; millennials in the work force).

While these changes have been happening, the Insurance industry has seemingly preferred to operate in a closed environment oblivious to much of the impact these changes could bring:

  • Resistance to change,
  • Failure to meet changing customer demands
  • Decrease in the importance of attritional risks

has led the Insurance industry to reduce its relevance.

However

  • the availability of data,
  • the introduction of new capital providers,
  • the impact of new business models emerging from the sharing economy
  • and the challenge of InsurTechs

are affecting the industry complacency. Collectively, these factors are creating the perfect storm for the incumbents allowing them to re-evaluate their preference for maintaining the status quo. There is an ever increasing expectation from the industry to be more innovative and deliver a vastly improved customer experience.

As data and emerging technology are accelerating the need for change, they are also opening doors. The industry is at cross roads where it can either choose to regain relevance by adapting to the new world order or it can continue to decline. Should it choose the latter, it could expose the US$ 5 trillion market to approaches from large technology firms and manufacturers who have the access to customers, transformational capabilities and more than enough capital to fill the void left by the traditional players.

Insurance industry is slow to evolve

The Insurance industry has historically lacked an appetite to evolve and has shown reluctance in adopting industry-wide changes. A number of key elements, have created high barriers to entry. New entrants have found it difficult to challenge the status quo and lack appetite to win market share from incumbents with significantly large balance sheets. Such high barriers have kept the impact of disruption to minimal, allowing the industry to stay complacent even when most other industries have undergone significant structural shifts. In many ways ‘Darwin’ has not been at work.

  • A complex value chain

The Insurance industry started with a simple value chain involving four roles – the insured, a broker who advices the insured, an underwriter who prices the risk and an investor who provides the capital to secure the risk. Over centuries, the chain has expanded to include multiple other roles essential in helping the spreading of large risks across a broad investor community, as shown below.

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These new parties have benefitted the chain by providing expertise, access to customers, secure handling of transactions, arbitration in case of disputes and spreading of risk coverage across multiple partners. However, this has also resulted in added complexities and inefficiencies as each risk now undergoes multiple handovers.

While a longer value chain offers opportunities to new entrants to attack at multiple points, the added complexities and the importance of scale reduces opportunities to cause real disruption.

  • Stringent regulations

Insurance is one of the highest regulated industries in the world. And since the global financial crisis of last decade, when governments across the globe bailed out several financial service providers including insurers, the focus on capital adequacy and customer safety has increased manifold.

While a proactive regulatory regime ensures a healthy operating standard with potential measures in place to avoid another financial meltdown, multiple surveys have highlighted the implications of increased regulatory burden, leading to increased costs and limited product innovation.

  • Scale and volatility of losses

The true value of any insurance product is realised when the customer receives payments for incurred losses. This means that insurers must maintain enough reserves at any time to meet these claims.

Over the years volatility in high severity losses have made it difficult for insurers to accurately predict the required capital levels.

In addition, regulators now require insurers to be adequately capitalised with enough buffer to sustain extreme losses for even the lowest probability of occurrence (for example 1-in-100 years event or 1-in-200 years event). This puts additional pressure on the insurers to maintain bulky balance sheets.

On the other hand, a large capital base gives established insurers advantage of scale and limits growth opportunities for smaller industry players/new entrants.

  • Need for proprietary and historical data

Accurate pricing of the risk is key to survival in the industry. The insurers (specifically underwriters supported by actuaries) rely excessively on experience and statistical analysis to determine the premiums that they would be willing to take to cover the risk.

Access to correct and historical data is of chief importance and has been a key differentiating factor amongst insurers. Since the dawn of Third Industrial Revolution in the 1980s, insurers have been involved in a race to acquire, store and develop proprietary databases that allow them to price risks better than the competitors.

The collection of these extensive databases by incumbent insurers have given them immense benefits over new entrants that do not typically have similar datasets. Additionally, the incumbents have continued to add on to these databases through an unchallenged continuation of underwriting– which has further widened the gap for new entrants.

Struggling to meet customer needs

Despite years of existence, the Insurance industry has failed to keep up with the demand for risk coverage. For example the economic value of losses from all natural disasters has consistently been more than the insured value of losses by an average multiple of 3x-4x.

The gap is not limited to natural disasters. As highlighted by Aon’s Global Risk Management Survey 2019, multiple top risks sighted by customers are either uninsurable or partially insurable leading to significant supply gap.

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Six of the top 10 risks, including Damage to reputation/brand and Cyber, require better data and analytical insights to achieve fully effective risk transfer. However, current capabilities are primarily applied to drive better pricing and claims certainty across existing risk pools, and have not yet reached their full potential for emerging risks.

This inability to meet customer need has been driven by both an expensive model (for most risks only 60% of premiums paid are actually returned to the insured) and a lack of innovation. Historically, the need for long data trends meant insurance products always trailed emerging risks.

Status Quo is being challenged

While the industry has been losing relevance, it is now facing new challenges which are creating pressure for change. While these challenges are impacting the incumbents they also provide the potential for insurance to regain its key role in supporting innovation. Creating opportunity for lower costs and new innovations.

The insurance customer landscape has changed considerably: traditional property and casualty losses are no longer the only main risks that corporations are focused on mitigating. The importance of intellectual property and brand/reputation in value creation is leading to a realignment in the customer risk profile.

Value in the corporate world is no longer driven by physical/ tangible assets. As technology has advanced, it has led to the growth of intangibles assets in the form of intellectual property. The graph below shows that 84% of market capitalization in 2018 was driven by intangible assets. While the five largest corporations in 1975 were manufacturing companies (IBM; Exxon Mobil; P&G; GE; 3M), that has completely changed in 2018 as the first five positions were occupied by Tech companies (Apple; Alphabet; Microsoft; Amazon; Facebook). Yet, organizations are only able to secure coverage to insure a relatively small portion of their intangible assets (15%) compared to insurance coverage for legacy tangible assets (59%).

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This shift represents both a challenge and an opportunity for the Insurance industry. The ability to provide coverage for intangible assets would enable insurance to regain relevance and support innovation and investment. Until it can, its importance is likely to remain muted.

InsurTech

The Insurance industry has had traditionally manual processes, and has been a paper driven industry with huge inefficiencies. While customers´ needs are evolving at an unprecedented quick pace, the incumbents´ large legacy systems and naturally conservative approach, make them slow to reach the market with new products and an improved customer experience.

InsurTechs are companies that use technology to make the traditional insurance value chain more efficient. They are beginning to reshape the Insurance industry by targeting particular value pools or services in the sector, rather than seek to provide end-to-end solutions.

InsurTechs have seen more than US$ 11 billion of funding since 2015, and the volume in 2018 is expected to reach US$ 3,8 billion (FT PARTNERS). While Insurtechs were originally viewed as a disruptive force competing with traditional insurers to gain market share, there is a growing collaboration and partnership with the incumbent players. Most of them are launched to help solve legacy insurer problems across the organization, from general inefficiency in operations to enhancing underwriting, distribution, and claims functions, especially in consumer facing insurance. More recently they are also moving into the commercial segment focusing on loss prevention and efficiency. (CATLIN, T. et al. 2017). Incumbent insurers have managed to leverage InsurTechs to speed up innovation (DELOITTE, 2018: 11). From a funding perspective most of the US$ 2.6 billion that went into the InsurTechs in the first nine months of 2018 came from incumbent Insurers. (MOODY`S, 2018: 6).

The accelerated use of technology and digital capabilities again represents both a challenge for the industry but also an opportunity to innovate and develop more efficient products and services.

Data and technology with potential to transform

Traditionally, the Insurance industry has used proprietary historic data to match the demand from risk owners with the supply from capital providers. Focusing on relative simplistic regression analysis as the main approach.

While robust, this approach is reliant on a long data history and limits insurers ability to move into new areas. Increasingly the transformative power of data and technology is changing this relationship, as shown in the graph below. While underwriting data used to be in the hands of the incumbents only, emerging technologies, new analytical techniques and huge increases in sensors are enabling usage of new forms of data that are much more freely accessible. In addition, these technologies are supporting instant delivery of in-depth analytics that can potentially lead to significant efficiency gains and new types of products.

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  • Artificial Intelligence

Artificial Intelligence – Robotic Process Automation (RPA) and Cognitive Intelligence (CI) – is know as any system that can perceive the world around it, analyse and understand the information it receives, take actions based on that understanding and improve its own performance by learning from what happended.

Artificial Intelligence not only gives the opportunity to reduce costs (process automation; reduction of cycle times; free up of thousands of people hours) but improves accuracy that results in better data quality. For insurers this offers significant potential to both enable new ways of interpreting data and understanding risks. As well as reducing the costs of many critical processes such as claims assessment.

This dual impact of better understanding and lower costs is highly valuable. Insurers’ spend on cognitive/artificial intelligence technologies is expected to rise 48% globally on an annual basis over five years, reaching US$ 1.4 billion by 2021. (DELOITTE, 2017: 15).

  • Internet of Things

The Internet of Things refers to the digitization of objects around us. It works by embedding advanced hardware (e.g. sensors, cameras and meters) into everyday objects and even people themselves, linking those objects further to online networks. (MOODY`S, 2018: 11).

For example, connected devices in the homes such as water leakage detectors, smoke alarms, C02 readers and sophisticated home security systems will support prevention and reduction in losses from water damage, fire and burglary, respectively.

The Internet of Things has the potential to significantly change the way that risks are underwritten. The ability to have access to data in ‘real time’ will provide greater precision in the pricing of risk and also help insurers to respond better to the evolving customer needs. Consider the example of home insurance; customers will be forced to resconsider the decision to buy home insurance as packaged currently when their house is already monitored 24/7 for break-ins and the sensors are constantly monitoring the appliances to prevent fires. The insurers could utilise the same data to develop customised insurance policies depending on usage and scope of sensors.

The Internet of Things applies equally to wearable devices with embedded sensors for tracking vital statistics to improve the health, safety and productivity of individuals at work. It is predicted that the connected health market will be worth US$ 61 billion by 2026.

The Internet of Things offers the Insurance industry an opportunity to reinvent itself and to move from simply insuring against risk to helping customers protect the properties / health. This integration of insurance with products through live sensor data can revolutionise how insurance is embedded into our every day lives.

  • Blockchain

All disruptive technologies have a “tipping point” – the exact moment when it moves from early adopters to widespread acceptance. Just as it was for Google in the late 1990s and smartphones in the 2000s, could we be approaching the tipping point for the next big disruptive technology – blockchain?

Essentially, blockchain is a shared digital ledger technology that allows a continuously growing number of transactions to be recorded and verified electronically over a network of computers. It holds an immutable record of data, stored locally by each party to remove the barrier of trust. Through smart contacts, blockchain can enable automation of tasks for more efficient processing. It made its debut in 2009 as the system used to track dealing in the first cryptocurrency, Bitcoin, and, since then, organisations around the world have spotted blockchain’s potential to transform operations.

Most industries are currently experimenting with blockchain to identify and prove successful use cases to embrace the technology in business as usual. IDC, a leading market intelligence firm, expects the spend on blockchain to increase from US$ 1.8 billion in 2018 to US$ 11.7 billion in 2022 at a growth rate of 60%.

With all the aforementioned benefits, blockchain also has potential to impact the Insurance industry. It can help Insurers reduce operational and administrative costs through automated verification of policyholders, auditable registration of claims and data from third parties, underwriting of small contracts and automation of claims procedures. Equally, it can help reduce the fraud which would contribute to reduce total cost.

In an industry where ‘trust’ is critical, the ability to have guaranteed contracts, with claims certainty will help the take-up of insurance in new areas. BCG estimates that blockchain could drastically improve the end-to-end processing of a motor insurance policy and any claims arising thereof as shown in the graph below.

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Conclusion

The relevance of insurance, which has declined over the last few decades, after peaking in the early 1980s, is set to increase again:

  • Big shifts in insurance needs, both in the commercial and consumer segments,
  • New sources of cheap capital,
  • Prevelance of cheap and accessible data and the technology to automate and analyse

will transform the Insurance industry.

Not only is this important for insurers, it is also important for all of us. Insurance is the grease behind investment and innovation. The long term decline in the Insurance´s industry ability to reduce risk could be a significant impediment on future growth.

However we believe that the reversal of this trend will mean that insurance can once again grow in its importance of protecting our key investments and activities.

Click here to access Aon’s White Paper

 

Les besoins verticaux définissent la marche à suivre pour les transformations de produits numériques et les stratégies

Les initiatives de transformation numérique se déroulent différemment selon les secteurs verticaux et les entreprises, en fonction des besoins métiers en jeu. Lorsque les entreprises subissent des transformations numériques, elles se concentrent souvent sur

  • les processus informatiques,
  • les ventes et le marketing

avant le développement des produits. Cependant, ce rapport expliquera aux DSI et aux directeurs de la technologie comment les entreprises de différents secteurs verticaux utilisent l’organisation produits comme catalyseur de leur transformation numérique, et comment cette décision améliore leurs relations avec les clients.

Principales conclusions

Les sociétés de produits physiques se concentrent sur l’IoT

Pour les organisations produits physiques, l’étape évidente vers une entreprise numérique consiste souvent à connecter des produits et des actifs. Il s’agit d’une tâche complexe qui nécessite

  • une infrastructure technologique intégrée,
  • une grande compétence dans la connectivité et l’Internet des objets (IoT),
  • ainsi qu’une logique claire sur la façon dont les produits connectés répondront aux besoins de leurs clients.

Les sociétés de services construisent des plates-formes numériques orientées client

Les entreprises du secteur des services basculeront vers le commerce numérique grâce à des plateformes numériques axées sur la clientèle. Ces projets doivent être

  • faciles à utiliser,
  • évolutifs
  • et intégrés aux partenaires de l’écosystème

afin de créer de la valeur pour les clients.

Diapositive1

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Technology Driven Value Generation in Insurance

The evolution of financial technology (FinTech) is reshaping the broader financial services industry. Technology is now disrupting the traditionally more conservative insurance industry, as the rise of InsurTech revolutionises how we think about insurance distribution.

Moreover, insurance companies are improving their operating models, upgrading their propositions, and developing innovative new products to reshape the insurance industry as a whole.

Five key technologies are driving the change today:

  1. Cloud computing
  2. The Internet of Things (including telematics)
  3. Big data
  4. Artificial intelligence
  5. Blockchain

This report examines these technologies’ potential to create value in the insurance industry. It also examines how technology providers could create new income streams and take advantage of economies of scale by offering their technological backbones to participants in the insurance industry and beyond.

Cloud computing refers to storing, managing, and processing data via a network of remote servers, instead of locally on a server or personal computer. Key enablers of cloud computing include the availability of high-capacity networks and service-oriented architecture. The three core characteristics of a cloud service are:

  • Virtualisation: The service is based on hardware that has been virtualised
  • Scalability: The service can scale on demand, with additional capacity brought online within minutes
  • Demand-driven: The client pays for the services as and when they are needed

cloud

Telematics is the most common form of the broader Internet of Things (IoT). The IoT refers to the combination of physical devices, vehicles, buildings and other items embedded with electronics, software, sensors, actuators, and network connectivity that enable these physical objects to collect and exchange data.

The IoT has evolved from the convergence of

  • wireless technologies,
  • micro-electromechanical systems,
  • and the Internet.

This convergence has helped remove the walls between operational technology and information technology, allowing unstructured, machine-generated data to be analysed for insights that will drive improvements.

IoT

Big data refers to data sets that are so large or complex that traditional data processing application software is insufficient to deal with them. A definition refers to the “five V” key challenges for big data in insurance:

  • Volume: As sensors cost less, the amount of information gathered will soon be measured
    in exabytes
  • Velocity: The speed at which data is collected, analysed, and presented to users
  • Variety: Data can take many forms, such as structured, unstructured, text or multimedia. It can come from internal and external systems and sources, including a variety
    of devices
  • Value: Information provided by data about aspects of the insurance business, such as customers and risks
  • Veracity: Insurance companies ensure the accuracy of their plethora of data

Modern analytical methods are required to process these sets of information. The term “big data has evolved to describe the quantity of information analysed to create better outcomes, business improvements, and opportunities that leverage all available data. As a result, big data is not limited to the challenges thrown up by the five Vs. Today there are two key aspects to big data:

  1. Data: This is more-widely available than ever because of the use of apps, social media, and the Internet of Things
  2. Analytics: Advanced analytic tools mean there are fewer restrictions to working with big data

BigData

The understanding of Artificial Intelligence AI has evolved over time. In the beginning, AI was perceived as machines mimicking the cognitive functions that humans associate with other human minds, such as learning and problem solving. Today, we rather refer to the ability of machines to mimic human activity in a broad range of circumstances. In a nutshell, artificial intelligence is the broader concept of machines being able to carry out tasks in a way that we would consider smart or human.

Therefore, AI combines the reasoning already provided by big data capabilities such as machine learning with two additional capabilities:

  1. Imitation of human cognitive functions beyond simple reasoning, such as natural language processing and emotion sensing
  2. Orchestration of these cognitive components with data and reasoning

A third layer is pre-packaging generic orchestration capabilities for specific applications. The most prominent such application today are bots. At a minimum, bots orchestrate natural language processing, linguistic technology, and machine learning to create systems which mimic interactions with human beings in certain domains. This is done in such a way that the customer does not realise that the counterpart is not human.

Blockchain is a distributed ledger technology used to store static records and dynamic transaction data distributed across a network of synchronised, replicated databases. It establishes trust between parties without the use of a central intermediary, removing frictional costs and inefficiency.

From a technical perspective, blockchain is a distributed database that maintains a continuously growing list of ordered records called blocks. Each block contains a timestamp and a link to a previous block. Blockchains have been designed to make it inherently difficult to modify their data: Once recorded, the data in a block cannot be altered retroactively. In addition to recording transactions, blockchains can also contain a coded set of instructions that will self-execute under a pre-specified set of conditions. These automated workflows, known as smart contracts, create trust between a set of parties, as they rely on pre-agreed data sources and and require not third-party to execute them.

Blockchain technology in its purest form has four key characteristics:

  1. Decentralisation: No single individual participant can control the ledger. The ledger
    lives on all computers in the network
  2. Transparency: Information can be viewed by all participants on the network, not just
    those involved in the transaction
  3. Immutability: Modifying a past record would require simultaneously modifying every
    other block in the chain, making the ledger virtually incorruptible
  4. Singularity: The blockchain provides a single version of a state of affairs, which is
    updated simultaneously across the network

Blockchain

Oliver Wyman, ZhongAn Insurance and ZhongAn Technology – a wholly owned subsidiary of ZhongAn insurance and China’s first online-only insurer – are jointly publishing this report to analyse the insurance technology market and answer the following questions:

  • Which technologies are shaping the future of the insurance industry? (Chapter 2)
  • What are the applications of these technologies in the insurance industry? (Chapter 3)
  • What is the potential value these applications could generate? (Chapter 3)
  • How can an insurer with strong technology capabilities monetise its technologies?
    (Chapter 4)
  • Who is benefiting from the value generated by these applications? (Chapter 5)

 

Click here to access Oliver Wyman’s detailed report

Insurance Global Trends in 2017

A brief summary of the key regional trends :

  • Analytics, Customer Centricity and Digital Innovation achieve similar scores across all our regions.
    • Customer-Centricity trails marginally in North America.
    • Noteworthy is the perfect score of 60 attained for Digital Innovation in Asia-Pacific, which indicates that this was the number-one priority here in all four measures underlying the priority score (money, time, staffing and training).
  • Underwriting and Risk Management both score considerably higher in North America than they do elsewhere – as we saw in the first priorities table, Underwriting is 3rd in the list of priorities in North America, despite not getting above 7th place in any other regions, and its Risk Management score is more than 80% higher than the runner-up’s (Europe).
  • There is a step-up in focus on Claims in Europe and North America compared to Asia-Pacific.
  • With Distribution Diversification, we have the exact inverse scenario, with Asia-Pacific leading the pack, possibly a reflection of the emerging markets within it necessitating high-scale low-cost distribution, which traditional models cannot provide.
  • Fraud is also a marginally higher priority in Asia-Pacific.
  • Europe and Asia-Pacific lead North America with their focus on Internet of Things.
  • Cybersecurity and Mobile achieve similar (lowish) scores for all regions; Product Development is relatively high across the board.
  • Regulation is the biggest deal in Europe, where respondents quoted in particular Solvency II and the Insurance Distribution Directive (IDD) as being causes for concern.

InsuranceNexus

Click here to access Insurance Nexus detailed survey analysis