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


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.


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


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


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

The new dynamics of financial globalization

Since the global financial crisis began in 2007, gross cross-border capital flows have fallen by 65 percent in absolute terms and by four times relative to world GDP. Half of that decline has come from a sharp contraction in cross-border lending. But financial globalization is still very much alive—and could prove to be more stable and inclusive in the future.

  • Eurozone banks are at the epicenter of the retreat in cross-border lending, with total foreign loans and other claims down by $7.3 trillion, or by 45 percent, since 2007. Nearly half has occurred in intra-Eurozone borrowing, with interbank lending showing the largest decline. Swiss, UK, and some US banks also reduced their foreign business.
  • The retrenchment of global banks reflects several factors:
    • a reappraisal of country risk;
    • the recognition that foreign business was less profitable than domestic business for many banks;
    • national policies that promote domestic lending;
    • and new regulations on capital and liquidity that create disincentives for the added scale and complexity that foreign operations entail.
  • Some banks from developing and other advanced economies—notably China, Canada, and Japan—are expanding abroad, but it remains to be seen whether their new international business is profitable and sustained.
  • Central banks are also playing a larger role in banking and capital markets.
  • Financial globalization is not dead. The global stock of foreign investment relative to GDP has changed little since 2007, and more countries are participating. Our new Financial Connectedness Ranking shows that advanced economies and international financial centers are the most highly integrated into the global system, but China and other developing countries are becoming more connected. Notably, China’s connectedness is growing, with outward stock of bank lending and foreign direct investment (FDI) tripling since 2007.
  • The new era of financial globalization promises more stability. Less volatile FDI and equity flows now command a much higher share of gross capital flows than before the crisis. Imbalances of current, financial, and capital accounts have shrunk, from 2.5 percent of world GDP in 2007 to 1.7 percent in 2016. Developing countries have become net recipients of global capital again.
  • But potential risks remain. Capital flows—particularly foreign lending—remain volatile. Over 60 percent of countries experience a large decline, surge, or reversal in foreign lending each year, creating volatility in exchange rates and economies. Equity-market valuations have reached new heights. Financial contagion remains a risk. The rise of financial centers, particularly those that lack transparency, is worth watching.
  • Looking forward, new digital platforms, blockchain, and machine learning may create new channels for cross-border capital flows and further broaden participation.
    • Banks need to harness the power of digital and respond to financial technology companies or fintechs, adapt business models to new regulation, improve risk management, and review their global strategies.
    • Regulators will need to continue to monitor old risks and find new tools to cope with volatility, while creating a more resilient risk architecture and keeping pace with rapid technological change.

Financial Globalization

Click here to access McKinsey’s detailed study