area of insurance should be supported by independent and reliable statistics. 4 the central bank was tasked with this job and we have worked to address this data gap in the motor insurance market through the establishment of the national claims information database ( ncid ). today ’ s report on the ncid will increase transparency in the sector. the report will assist the cost of insurance working group, government, oireachtas and wider stakeholders in their consideration of the relevant issues. the motor insurance report has a range of new information in relation to claims ; premiums ; comparison of settlement channels and a breakdown of insurers ’ income and expenditure for private motor insurance ( central bank, 2019 ) the overall trend is consistent with the long term insurance underwriting cycle, with peaks and troughs in premiums, reserves and profitability. cycles typically last six to nine years. the report is rich in data but one key comparison will undoubtedly draw attention. between 2009 and 2018, the average cost of claims per policy decreased by 2. 5 % from €437 in 2009 to €426 in 2018. in contrast, between 2009 and 2018, the average premium per policy increased by 42 % from €495 in 2009 to €705 in 2018. now, i ’ m not saying this is a black - and - white case. data cannot be considered in isolation – it has to be considered both in the round and in the contextual circumstances, such as the underwriting cycles mentioned previously. for instance, while it is correct to say from the data that the average cost of claims per policy has fallen, it is also true to say that the average cost of each claim has steadily increased over the same period. in all, the average cost of claims is up by 64 % per cent over the period. within that there has been a compositional shift to a greater proportion of higher value injury claims. the average cost of an injury claim has been increasing steadily over the entire period and is now over 50 % higher than a decade ago, currently at just over €47, 000. looking at the loss ratio for insurance firms, there was a prolonged period of losses peaking in 2014. this has since been coming down. firms are more profitable, in line with peaks and troughs in the cycle. like i said, our task was to gather the data and publish it, and it will be for others to analyse and contextualise some of the patterns we are seeing above. but i can say with confidence

er hub better data, to inform better policy - deputy governor sharon donnery 16 december 2019 speech opening remarks at the sixth conference on household finance and consumption good morning, and welcome to the sixth conference on household finance and consumption1. i would like to thank both my colleagues in the central bank of ireland and the ecb for all their hard work in organising what promises to be a fascinating network event. looking at the programme, and the range of topics ; from inflation, housing, credit, and business cycles, to inequality, demographic change, and of course, monetary policy, you ’ re in for a stimulating couple of days. what i see as a common thread across this diverse range of issues is ultimately, how better data informs better policy. like many policy institutions, a decade ago, the crisis, prompted us to reflect on the type of data we collect, how it is analysed, and, crucially, how the analysis feeds through to policy decisions. the work that you, the network, are doing and what we will discuss today, is critical to how we make policy, how we decide, and how what we do affects society. but it ’ s important we don ’ t just think about the gaps in data that emerged in the past. we also need to develop data in areas that have grown and changed recently, such as non - bank, or market based finance. finally, today, i wish to note how data can enhance debates and policy discussion where before it had been unavailable. for example, today the central bank of ireland is launching a report on the national claims information database ( ncid ), a report that will add important numbers and facts to a widely debated topic here in ireland. understanding household balance sheets through data, the irish household finance and consumption survey ( 2013 ), provided really important insights in to household finances in the wake of the crisis. we know that high - leverage households were twice as likely to face credit constraints, even after controlling for different income shocks faced by households ( leblanc & lydon 2019 ). the cross - country evidence paints a similar picture – amongst euro area households in 2013 / 14, irish households were the most indebted and the most likely to be credit constrained – almost one - in - five households at the time ( ibid ). heavily indebted households reduce their spending by significantly more in response to a given income shock. this partly explains why ireland experienced one of the largest drops in consumer spending during the