process by which authorities' exclusion of entity types that they assess as not engaging in any of the defined economic functions has been subject to collective review by peer jurisdiction The exercise took a conservative approach of including entity types into the narrow measure for all jurisdictions if the activities associated with non-bank credit intermediation could give rise to shadow banking risks at least in some jurisdictions. This year's report also seeks to explain where jurisdiction-specific exclusions from the narrow measure have occurred, and classification (see Annex 1). To foster aligned approaches, the activity-based narrow measure remains a work in progress and is expected to deeper understanding of the shadow banking system e consistency in the assessments and improve over time with increased data availability, mor Building on the economic functions classification, Section 3 of this report introduces risk analyses as a further enhancement to the annual monitoring report. It describes ways in which particular entity types may engage in leverage, liquidity and maturity transformation, and imperfect credit risk transfer in each economic function. Moreover, aggregate risk metrics across particular entity types in different economic functions are presented, illustrating how levels of risk-taking, as reported by each jurisdiction, range widely. While data gaps hamper a more thorough quantitative assessment of shadow banking risks, a review of jurisdictions assessment of risks based on available data and supervisory judgment suggests relatively higher attention to liquidity and maturity transformation risks at the current conjuncture. With respect to these risks, FSB members noted current concerns about rising risks stemming the overestimation by investors of the degree of liquidity in fixed income markets as well as the growth of assets under management in funds that offer on-demand redemptions but invest in less liquid assets. In light of these concerns, it is important to ensure that any financial stability risks are properly understood Section 4 of the report provides an enhanced macro-mapping of the broad measure of non- bank financial intermediation. Monitoring the broad measure remains important to cast the net wide to capture emerging adaptations and innovations from which shadow banking risks may This year, the monitoring scope has been increased through the inclusion of insurers and ion funds in the broad mUNFI measure 3 in order to enable the introduction of the shadow banking measure based on economic functions. Size and growth trends of insurance companies, pension funds and OFIs are presented. The section also compares various factors including growth of banking and non-banking sectors to gdP to better understand relationships between economic and financial system developments Chinese authorities did ation of certain entity types as shadow banking. Thus, China's entity types are not reflected in this years econo ions. The report shows a narrow measure of Chinas shadow banking sector based on ofis that ar intermediation, consistent with the methodology that was utilised to derive the narrow measure in last years shadow banking monitoring report. Due to data limitations, some of the exhibits and results presented in Section 3 on shadow banking risks and interconnectedness, and Section 5 on credit and lending patterns, in particular, come from a subsample of jurisdictions and may therefore not be extrapolated to describe the entire sample of participating jurisdictions. These data trends should not be interpreted as definitive indicators of the degree of financial stability risks posed by these activities. More specifically, any conclusion from the data related to the subsample may not apply to all of the jurisdictions that ttp//www.fsborg/2015/03/fsb-plenary-meets-in-frankfurt-germa Although not part of MUNFl, data on insurance companies and pension funds has already been collected in last year monitoring exercise to capture some key insights into the broader composition of the financial system4 process by which authorities’ exclusion of entity types that they assess as not engaging in any of the defined economic functions has been subject to collective review by peer jurisdictions. The exercise took a conservative approach of including entity types into the narrow measure for all jurisdictions if the activities associated with non-bank credit intermediation could give rise to shadow banking risks at least in some jurisdictions. This year’s report also seeks to explain where jurisdiction-specific exclusions from the narrow measure have occurred, and the rationale for such differences in classification (see Annex 1). To foster aligned approaches, the activity-based narrow measure remains a work in progress and is expected to improve over time with increased data availability, more consistency in the assessments and a deeper understanding of the shadow banking system.10 Building on the economic functions classification, Section 3 of this report introduces risk analyses as a further enhancement to the annual monitoring report.11 It describes ways in which particular entity types may engage in leverage, liquidity and maturity transformation, and imperfect credit risk transfer in each economic function. Moreover, aggregate risk metrics across particular entity types in different economic functions are presented, illustrating how levels of risk-taking, as reported by each jurisdiction, range widely. While data gaps hamper a more thorough quantitative assessment of shadow banking risks, a review of jurisdictions’ assessment of risks based on available data and supervisory judgment suggests relatively higher attention to liquidity and maturity transformation risks at the current conjuncture. With respect to these risks, FSB members noted current concerns about rising risks stemming from the overestimation by investors of the degree of liquidity in fixed income markets as well as the growth of assets under management in funds that offer on-demand redemptions but invest in less liquid assets.12 In light of these concerns, it is important to ensure that any financial stability risks are properly understood. Section 4 of the report provides an enhanced macro-mapping of the broad measure of non￾bank financial intermediation. Monitoring the broad measure remains important to cast the net wide to capture emerging adaptations and innovations from which shadow banking risks may arise. This year, the monitoring scope has been increased through the inclusion of insurers and pension funds in the broad MUNFI measure, 13 in order to enable the introduction of the shadow banking measure based on economic functions. Size and growth trends of insurance companies, pension funds and OFIs are presented. The section also compares various factors including growth of banking and non-banking sectors to GDP to better understand relationships between economic and financial system developments. 10 Chinese authorities did not agree with the classification of certain entity types as shadow banking. Thus, China’s entity types are not reflected in this year’s economic functions. The report shows a narrow measure of China’s shadow banking sector based on OFIs that are involved in credit intermediation, consistent with the methodology that was utilised to derive the narrow measure in last year’s shadow banking monitoring report. 11 Due to data limitations, some of the exhibits and results presented in Section 3 on shadow banking risks and interconnectedness, and Section 5 on credit and lending patterns, in particular, come from a subsample of jurisdictions and may therefore not be extrapolated to describe the entire sample of participating jurisdictions. These data trends should not be interpreted as definitive indicators of the degree of financial stability risks posed by these activities. More specifically, any conclusion from the data related to the subsample may not apply to all of the jurisdictions that participated in this report. 12 See the FSB Plenary press release: http://www.fsb.org/2015/03/fsb-plenary-meets-in-frankfurt-germany/. 13 Although not part of MUNFI, data on insurance companies and pension funds has already been collected in last year’s monitoring exercise to capture some key insights into the broader composition of the financial system