How to ensure that macroprudential policy can help in this context? If we release, we may contribute to the inflation dynamics through the usual credit channel. If we tighten, we can contribute to triggering financial risks. Complementarity with monetary policy remains, but prudence is of the essence, and this could be the time for some macroprudential pause. II. The case of the real-estate sector: how macroprudential tools help mitigate growing risks In France, our macroprudential body is the High Council for Financial Stability (HCSF): it’s chaired by the Finance Minister, but I as Governor have the sole power to propose macroprudential measures to the Council. It’s a subtle institutional balance… but it works. In recent years, we have used actively the countercyclical capital buffer (CCyB): removing it in March 2020, reintroducing it at 0.5 % in April this year, and planning to raise it at 1% next December. As  Page 8 sur 11 the CCyB is always difficult to explain to public opinion, we also decided to rebrand it “credit protection reserve”. Let me now focus on a practical case, on a sector that has often proved critical to financial stability, namely the real estate sector. It is politically most sensitive for citizens. Severe financial crises have often been related to housing boomand-bust cycles: the great financial crisis was a stark example of this. Lessons have been learned and a wide range of macroprudential tools have been implemented since then to mitigate vulnerabilities arising in the residential real estate sector,iii including in France and Ireland.

This builds up a knowledge profile of the area, and enables underwriting and pricing of risks. Insurers and governments are also able to detect droughts and floods, and their potential impact on harvests early, enabling a quicker response. And in the event of a disaster, the before and after images allow insurers to perform loss assessment and support quicker release of claims to the affected farmers. No need to send loss surveyors to inspect damages in-person, which can be costly and time consuming. Big data analytics is at the core of Singapore’s own Natural Catastrophe Data Analytics Exchange (Nat Cat DAX). Nat Cat DAX is led by ICRM, in partnership with MAS and the industry. It will aggregate a variety of data sources including economic loss and exposure data as well as drone and satellite data to create a comprehensive database of Asia Pacific natural catastrophe risk. The consortium has commenced industry data collection efforts in Taiwan and Jakarta, and is also using satellite imagery to extract information on building features. I understand a more detailed update of its preliminary findings will be shared later in this conference. Product innovation Second, product innovation. We are seeing new forms of insurance products and solutions, such as index-based and parametric insurance. Unlike traditional insurance which indemnifies actual losses, parametric insurance solutions make pay-outs based on catastrophe events hitting certain pre-defined parameters such as hurricane wind speed or earthquake magnitude. This removes the need for loss adjusters to survey the extent of losses.