. so how should the central bank react in this environment? any potential action needs to be viewed in a context where the balance of risks to fulfilling our objective is on the downside. certainly, the time horizon for central banks to normalise inflation cannot be pre - set, by statute, unconditionally. indeed, in a vast part of the world where central banks are assigned numerical objectives for price stability, the stabilisation horizon is not defined in rigid calendar - time form, but is left rather flexible for central banks to determine according to the nature of shocks that cause inflation to deviate from target. at the same time, a central bank cannot allow itself too much discretion over the time horizon when inflation should return to its target. a numerical objective which is rarely realised – looking forward and in retrospect – is no hard objective. our independence rests on the fact that we are accountable, and that means delivering price stability over a horizon that is verifiable by the public. moreover, central banks know that if they lack a verifiable commitment to control inflation symmetrically over a horizon for which the public retains some visibility, this can result in inflation expectations becoming “ unanchored ”. it is in this spirit that a central bank may choose to proactively counter downside risks and thereby underpin the public ’ s faith in the effectiveness of monetary policy. that is why the governing council concluded at its last meeting to thoroughly analyse “ the strength and persistence of the factors that are currently slowing the return of inflation to levels below, but close to, 2 % in the medium term ”, and would re - examine “ the degree of monetary policy accommodation. ” we have to assess whether, taking the risks relating to our mandate into account, the overall picture in the euro area economy is one of sufficient speed and momentum in growth and inflation for the ecb to meet its medium - term mandate. bis central bankers ’ speeches uncertainty about the structure of the economy to deliver our mandate, however, we also need to address the second dimension of uncertainty – uncertainty related to the structure of the economy. more precisely, we need to understand and respond to evolutions in the structure of the economy caused by the crisis. there are two key structural conditions that matter for the central bank to meet its objective. first, the financial transmission channel must remain intact, so that monetary policy is able to maintain sufficient traction over the economy and economic slack remains controllable. second, a

the region. a research by lloyd ’ s has shown that a 1 % rise in insurance penetration translates to a 22 % reduction in taxpayers ’ contribution following a disaster. in order to expand the insurability of catastrophe risks in the region and bridge the protection gap, an innovative public - private partnership ( “ ppp ” ) approach is needed. to do this, the mas is supporting a natural catastrophe data analytics exchange ( nat cat dax ) for asia pacific. led by the ntu institute for catastrophe risk management ( icrm ) in collaboration with a * star and the industry, this common data analytics platform will enable industry to pool insurable claims data. more importantly, this platform will unlock new economic exposure and loss datasets through the use of new technologies such as satellites, remote sensors and drones. with a comprehensive and integrated economic and insurance database, this will form a strong data backbone for the industry to not only underwrite traditional reinsurance better, but also catalyse new product innovation, such as government pools, and alternative risk transfer products, which will push the boundaries of insurability further. today, it gives me great pleasure to announce the formation of the nat cat dax alliance, in collaboration with pioneer industry founding members mitsui sumitomo insurance group, renaissance re, rms and aon. i urge the industry to be a part of this collaborative initiative, as we partner together to increase the availability of quality data, enhance the underwriting process, and spur collective market analytics and innovation. new technology and innovation just as new disruptive technologies like 3d printing, autonomous vehicles, and the internet of things have emerged in various sectors of the economy, such technologies will similarly surface in the insurance industry. this will have an impact on all parts of the insurance value chain – product design, underwriting and distribution. • product design – while there is tremendous scope for enhancements in product design, the advent of new technologies and innovation could even render some existing offerings obsolete. for example, autonomous cars and their safety elements could leave some motor insurance products out - dated, if not irrelevant, over the next couple of decades. • underwriting – with big data and smart analytics, underwriting models will likely evolve to become more predictive and personalised, such as through the use of telematics to price motor premiums according to driving behaviour, or the use of wearables for a customised health protection plan. data analytics is not new to the insurance sector, which has had