Innovation in Financial Institutions Insurance
When I first started in financial institutions’ insurance (at a large broking house a couple of decades plus ago), I was guided to past bankers blanket bond and professional indemnity policy wordings, some of which were thirty years old even back then. I was surrounded by a mixture of wise older heads and younger enthusiastic and ambitious protagonists like myself, keen to impress.
Realising that I lacked many of the social skills of the better brokers, I determined (perhaps already with one eye on an underwriting career later) to become immersed in the technical side of our business. I studied those insurance wordings to the point whereby I could recite large portions of many, many policy forms, in much the same way that I had committed Homer’s Odyssey to memory as a fifteen year old - in Ancient Greek. I have long forgotten my Homer, but still take a certain pride in correcting young underwriters when they get their KFA ‘81 muddled up with their RAGJ/ALS ‘83. I am obsessed. Every young underwriter who endures the pleasure of working with me to this day is forced to study 30 and 40 and 50 year old wordings before I let them loose with any underwriting authority; and I test them; and they fail, all of them. It’s just degrees of failure. Just as I failed - as my old mentor used to say to me, in order to be any good to your clients now and in the future you need to understand the past. You can’t be too knowledgeable; you can never know enough.
There is a valid perception that insurance is an industry which exists with two eyes looking in the rear view mirror. We use past data to model future losses. That’s great when we can apply the law of large numbers, like motor or household insurance, but not so easy the more one moves towards the more specialist commercial insurances. Attempting to predict trends in, say, the personal liability of directors of private companies in, say, Indonesia, relative to companies publicly listed on an exchange in USA is rather tricky. We have to attempt this with a lack of absolute data, a lack of relative data, developing and different legal systems, economic environments, political interference and uncertainty, trends in criminality (in its broadest interpretation), etc. Solely relying upon past data would be naive and foolish in the circumstances.
The banking industry has moved on, and the rest of the financial services industry is following suit.
There is a realisation that past data is only useful if it can be modelled into potential future outcomes. The data has to be real and it has to be plentiful in order to provide credibility to the forward looking calculations, with its inherent subjective assessments.
Banks and other financial institutions are now required to model their operational risks under Basel III to one in one thousand confidence levels. They have to take their own past operational loss data, combined with the anonymised data they obtain about their peers’ operational losses, and model these to predict future operational losses (“in order to plan for the future, one needs to understand the past”). Aside from sound risk management, this now can form the basis of their existing Pillar One and Pillar Two capital requirements. Under the Advanced Measurement Approach, banks are able potentially to offset up to 20% of their operational risk capital requirement through the use of appropriate insurance.
Even insurance companies are now having to take note. Solvency II is finally upon us with a much delayed start date of January 2016. Similar methodology to Basel III will apply in respect of the modelling of operational risk data and capital requirements.
In the meantime, many of the professional lines insurance products offered to financial institutions, with some exceptions, remain mired in the 1970s and 1980s. When presenting our suite of policy forms to a room full of several hundred insurance brokers in 2012, I asked how many of them used the internet for banking or management of their investment portfolios. All but one of the brokers raised their hands (there’s always one, isn’t there!); when I asked how many of them were doing the same a decade previously, only one person kept their hand raised. Our policies recognised many of the newer risks faced by the modern financial institution (or regulated IT company, as may be more accurate description) with extensive revision of those out-of-date coverages to reflect modern banking practices and financial services.
At XL Catlin, now that our financial institution clients are facing all sorts of regulatory and legislative pressure because capital, more than ever, is both scarce and valuable, we have had to consider how we can make insurance more relevant as a source of capital for our clients, whether that’s regulatory or economic capital. So we have found an innovative insurance solution for their operational risks, ensuring relevance for their capital requirements. For instance, at a corporate level insurance can now be used as a source of cost-effective capital (especially for Pillar II), or to enhance profitability within divisions or products by mitigating the operational risk capital impact.
We do this by using our clients’ data to model their potential operational risks, just as they do. Understanding the past, but using it to inform us about the future.
“By hook or by crook this peril too shall be something that we remember” Homer, The Odyssey
Want to know more? You can reach Gerard on: firstname.lastname@example.org