Tag Archives: transparency

Artificial Insurance

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.

Inhibiting Derivatives

The array and complexity of new financial regulation in response to the financial crisis can have unforeseen impacts. A reduction in the liquidity of the bond markets today compared to before the crisis is commonly explained as a result of increased regulation of the banking sector.

A report by International Organization of Securities Commissions (IOSCO) in 2013 highlighted the impact of the regulatory push, following a G20 direction in 2009, for the OTC derivatives markets to be cleared through central counterparties (CCPs), thereby creating a potential for systemic counterparty risk (as per this post). The idea was to provide a centralised clearing point per asset class with the goal of increasing transparency and providing regulators with consistent data across borders to monitor.

The reality today is somewhat different that the theory. Many competing repositories have sprung up with the commercial intend of leveraging the valuable data. David Wright, the Secretary General of IOSCO, recently stated “we’ve got 25 of these beasts today and they don’t talk to each other, so a basic fundamental trawl of transparency is actually missing”. Regulators are stressing the need for further reform so that data can be aggregated to improve monitoring and, in February, issued requirements on CCPs to disclose information on topics such as the size of their credit risk, liquidity risk, collateral, margins, business risk, custody, and investment risks

Benoît Cœuré, a member of the Executive Board of the ECB, said in a speech this month that “the gross notional outstanding amount of centrally cleared positions was estimated at $169 trillion for OTC interest rate derivatives, and at $14 trillion for credit derivatives. The sheer magnitude of these figures (around ten times the GDP of the United States or European Union) gives us an idea of the severity of the potential consequences from a stress event at a major global CCP”.

Cœuré outlined a number of options for strengthening the financial resilience of CCPs including increased regulatory capital, initial margin haircutting, setting up cross-CCP resolution funds or a central resolution fund. Any such measures would have to be consistently applied across jurisdictions to ensure fairness and designed so as not to provide a disincentive to using CCPs.

In March, the Bank of International Settlements (BIS) and IOSCO announced a delay until September 2016 for the introduction of margin requirements for non-centrally cleared derivatives (above certain thresholds and subject to exemptions). The proposed margin requirements are split between initial and variable, with the initial margin phased in from September 2016 to September 2020 and the variation margin phased in from September 2016 to March 2017.

The amount of initial margin reflects the size of the potential future exposure calculated “to reflect an extreme but plausible estimate of an increase in the value of the instrument that is consistent with a one-tailed 99 per cent confidence interval over a 10-day horizon, based on historical data that incorporates a period of significant financial stress”. The required amount of initial margin is calculated by reference to either a quantitative portfolio margin model or a standardised margin schedule (as per the schedule below). The requirements also prohibit the re-hypothecation of initial margin required to be collected and posted under the rules.

click to enlargeInitial Margin for Derivatives

The amount of variation margin reflects the size of this current exposure dependent on the mark-to-market value of the derivatives at any point in time. As such, the volatility of this requirement may be significant in stressed cases, particularly for illiquid derivatives.

The proposals, as set out by the BIS and IOSCO, are ambitious and it will be interesting to see how they are enforced across jurisdictions and the impact they will have on market behaviour, both within and outside CCPs. I suspect there will be a few twists in this tale yet, particularly in relation to unintended consequences of trying to tame the derivative monster.