Risk Assessment Indicators - RAI

Data - ECB

Author

François Geerolf

Last observation: Q2 2026 (N = 94) · juil. 2026 (N = 364)

First observation: sept. 1997 (N = 62) · Q3 1997 (N = 34)

Last data update: 04 sept. 2026, 01:38

Last compile: 04 sept. 2026, 02:44

Structure

Table: Average 2016-2022

Code 
RAI |>
  filter(FREQ == "M") |>
  month_to_date() |>
  filter(date >= as.Date("2016-01-01")) |>
  group_by(DD_ECON_CONCEPT, Dd_econ_concept, REF_AREA, Ref_area) |>
  summarise(OBS_VALUE = mean(OBS_VALUE),
            Nobs = n()) |>
  print_table_conditional()

France

Table

Code 
RAI |>
  filter(FREQ == "M",
         REF_AREA %in% c("FR", "U2")) %>%
  select_if(~ n_distinct(.) > 1) |>
  group_by(DD_ECON_CONCEPT, Ref_area) |>
  filter(TIME_PERIOD == max(TIME_PERIOD)) |>
  select(Ref_area, DD_ECON_CONCEPT, OBS_VALUE) |>
  spread(Ref_area, OBS_VALUE) |>
  arrange(-`France`) |>
  print_table_conditional()
DD_ECON_CONCEPT Euro area (changing composition) France
MMTCH 77.46913 78.7182322
ST1TMF 69.07468 77.3633181
SVLHHNFC 64.78474 46.4084705
IBL1TL 24.63684 36.6164803
LC1DHHS NA 36.1065193
NDEPFUN 14.70316 15.5869736
LEVR 8.31969 7.1485621
GRNLHHNFC NA 6.1830910
CT1DGGV NA 4.3667429
SVLHPHH 16.39929 2.9814300
LMGLNFC NA 1.1056715
LMGBLNFCH NA 0.9927445
LMGLHH NA 0.6716508
LMGOLNFCH NA 0.2537564

SVLHHNFC, LC1DHHS

Code 
RAI |>
  filter(DD_ECON_CONCEPT %in% c("SVLHHNFC", "LC1DHHS"),
         REF_AREA %in% c("FR", "U2")) |>
  month_to_date() %>%
  select_if(~n_distinct(.) > 1) |>
  mutate(Ref_area = ifelse(REF_AREA == "U2", "Europe", Ref_area)) |>
  add_flag_color("Ref_area") |>
  mutate(OBS_VALUE = OBS_VALUE/100) |>
  ggplot() + theme_minimal() + xlab("") + ylab("Share of variable rate") +
  geom_line(aes(x = date, y = OBS_VALUE, color = color, linetype = Dd_econ_concept)) + 
  add_flags(3) + scale_color_identity() +
  scale_x_date(breaks = seq(1960, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.7, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 5),
                     labels = percent_format(accuracy = 1))

CT1DGGV, SVLHPHH

Code 
RAI |>
  filter(DD_ECON_CONCEPT %in% c("CT1DGGV", "SVLHPHH"),
         REF_AREA %in% c("FR", "U2")) |>
  month_to_date() %>%
  select_if(~n_distinct(.) > 1) |>
  mutate(Ref_area = ifelse(REF_AREA == "U2", "Europe", Ref_area)) |>
  add_flag_color("Ref_area") |>
  mutate(OBS_VALUE = OBS_VALUE/100) |>
  ggplot() + theme_minimal() + xlab("") + ylab("Share of variable rate") +
  geom_line(aes(x = date, y = OBS_VALUE, color = color, linetype = Dd_econ_concept)) + 
  add_flags(3) + scale_color_identity() +
  scale_x_date(breaks = seq(1960, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  theme(legend.position = c(0.7, 0.9),
        legend.title = element_blank()) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 5),
                     labels = percent_format(accuracy = 1))

SVLHPHH - Share of floating rates, Households

Table: Last Time

Code 
RAI |>
  filter(DD_ECON_CONCEPT == "SVLHPHH") |>
  filter(TIME_PERIOD == max(TIME_PERIOD)) |>
  select_if(~n_distinct(.) > 1) |>
  select(REF_AREA, Ref_area, OBS_VALUE, OBS_VALUE) |>
  mutate(OBS_VALUE = round(OBS_VALUE, 1)) |>
  mutate(Flag = gsub(" ", "-", str_to_lower(gsub(" ", "-", Ref_area))),
         Flag = paste0('<img src="../../icon/flag/vsmall/', Flag, '.png" alt="Flag">')) |>
  select(Flag, everything()) |>
  arrange(OBS_VALUE) %>%
  {if (is_html_output()) datatable(., filter = 'top', rownames = F, escape = F) else .}

Table: Many dates

Code 
RAI |>
  filter(DD_ECON_CONCEPT == "SVLHPHH",
         TIME_PERIOD %in% c(last_time, "2020-01", "2015-01", "2010-01", "2005-01")) |>
  select_if(~n_distinct(.) > 1) |>
  select(REF_AREA, Ref_area, TIME_PERIOD, OBS_VALUE) |>
  mutate(OBS_VALUE = round(OBS_VALUE, 1)) |>
  spread(TIME_PERIOD, OBS_VALUE) |>
  print_table_conditional()
REF_AREA Ref_area 2005-01 2010-01 2015-01 2020-01 2026-07
AT Austria 65.7 76.2 87.3 40.6 19.3
BE Belgium 58.2 58.4 2.4 4.5 5.6
BG Bulgaria NA 96.2 84.0 97.3 99.8
CY Cyprus NA 61.7 95.1 90.7 12.1
CZ Czech Republic NA NA 7.2 2.1 4.5
DE Germany 19.1 21.6 13.2 11.6 12.1
DK Denmark 70.1 49.2 NA NA 51.2
EE Estonia 99.3 56.7 85.4 NA 97.5
ES Spain 93.1 90.1 66.6 32.1 7.8
FI Finland 97.8 97.5 96.8 97.6 94.3
FR France 36.5 12.8 3.8 1.9 3.0
GR Greece 84.4 72.2 93.1 70.2 26.8
HR Croatia NA NA 84.9 20.5 2.7
HU Hungary 58.1 84.4 44.1 2.1 7.9
IE Ireland 93.6 84.1 66.0 25.8 6.0
IT Italy 87.3 81.3 71.7 18.0 29.0
LT Lithuania 97.9 84.7 89.8 97.8 96.2
LU Luxembourg 88.5 NA 63.9 30.1 NA
LV Latvia 72.3 84.4 NA 94.3 93.8
MT Malta NA 88.0 77.9 47.4 NA
NL Netherlands 43.2 24.9 19.9 17.4 21.7
PL Poland 90.9 100.0 99.9 100.0 26.1
PT Portugal 97.8 99.5 93.0 86.7 14.1
RO Romania NA NA 89.9 73.6 19.6
SE Sweden NA 85.6 85.5 64.2 92.1
SI Slovenia 99.1 98.1 93.4 55.5 2.2
SK Slovakia 62.4 36.0 6.4 1.1 1.9
U2 Euro area (changing composition) 54.7 42.6 21.6 15.8 16.4

Netherlands, Germany, Belgium, France, Europe

Code 
RAI |>
  filter(DD_ECON_CONCEPT == "SVLHPHH",
         REF_AREA %in% c("NL", "DE", "BE", "FR",  "U2")) |>
  month_to_date() %>%
  select_if(~n_distinct(.) > 1) |>
  mutate(Ref_area = ifelse(REF_AREA == "U2", "Europe", Ref_area)) |>
  add_flag_color("Ref_area") |>
  mutate(OBS_VALUE = OBS_VALUE/100) |>
  ggplot() + theme_minimal() + xlab("") + ylab("Share of variable rate, households (%)") +
  geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  add_flags(5) + scale_color_identity() +
  scale_x_date(breaks = seq(1960, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 5),
                     labels = percent_format(accuracy = 1))

France, Spain, Portugal, latvia, Lithuania, Estonia

Code 
RAI |>
  filter(DD_ECON_CONCEPT == "SVLHPHH",
         REF_AREA %in% c("FR", "ES", "PT", "EE", "LT", "U2")) |>
  month_to_date() %>%
  select_if(~n_distinct(.) > 1) |>
  mutate(Ref_area = ifelse(REF_AREA == "U2", "Europe", Ref_area)) |>
  add_flag_color("Ref_area") |>
  mutate(OBS_VALUE = OBS_VALUE/100) |>
  ggplot() + theme_minimal() + xlab("") + ylab("Share of variable rate, households (%)") +
  geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  add_flags(6) + scale_color_identity() +
  scale_x_date(breaks = seq(1960, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 5),
                     labels = percent_format(accuracy = 1))

France, Spain, Portugal

Code 
RAI |>
  filter(DD_ECON_CONCEPT == "SVLHPHH",
         REF_AREA %in% c("FR", "ES", "PT")) |>
  month_to_date() %>%
  select_if(~n_distinct(.) > 1) |>
  add_flag_color("Ref_area") |>
  mutate(OBS_VALUE = OBS_VALUE/100) |>
  ggplot() + theme_minimal() + xlab("") + ylab("Share of variable rate, households (%)") +
  geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  add_flags(3) + scale_color_identity() +
  scale_x_date(breaks = seq(1960, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 5),
                     labels = percent_format(accuracy = 1))

Italy, Sweden, Poland

Code 
RAI |>
  filter(DD_ECON_CONCEPT == "SVLHPHH",
         REF_AREA %in% c("PL", "IT", "SE")) |>
  month_to_date() %>%
  select_if(~n_distinct(.) > 1) |>
  add_flag_color("Ref_area") |>
  mutate(OBS_VALUE = OBS_VALUE/100) |>
  ggplot() + theme_minimal() + xlab("") + ylab("Share of variable rate, households (%)") +
  geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  add_flags(3) + scale_color_identity() +
  scale_x_date(breaks = seq(1960, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 5),
                     labels = percent_format(accuracy = 1))

Netherlands, Germany, Belgium

Code 
RAI |>
  filter(DD_ECON_CONCEPT == "SVLHPHH",
         REF_AREA %in% c("NL", "DE", "BE")) |>
  month_to_date() %>%
  select_if(~n_distinct(.) > 1) |>
  add_flag_color("Ref_area") |>
  mutate(OBS_VALUE = OBS_VALUE/100) |>
  ggplot() + theme_minimal() + xlab("") + ylab("Share of variable rate, households (%)") +
  geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  add_flags(3) + scale_color_identity() +
  scale_x_date(breaks = seq(1960, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 5),
                     labels = percent_format(accuracy = 1))

SVLHHNFC - Share of floating rates, Households, and Corporations

Table

Code 
RAI |>
  filter(DD_ECON_CONCEPT == "SVLHHNFC",
         TIME_PERIOD %in% c(last_time, "2020-01", "2015-01", "2010-01", "2005-01")) |>
  select_if(~n_distinct(.) > 1) |>
  select(REF_AREA, Ref_area, TIME_PERIOD, OBS_VALUE) |>
  mutate(OBS_VALUE = round(OBS_VALUE, 1)) |>
  spread(TIME_PERIOD, OBS_VALUE) |>
  print_table_conditional()
REF_AREA Ref_area 2005-01 2010-01 2015-01 2020-01 2026-07
AT Austria 91.7 92.3 89.7 70.1 68.1
BE Belgium 90.7 90.4 76.4 73.3 74.1
BG Bulgaria NA 98.7 95.8 95.8 97.4
CY Cyprus NA 85.4 96.1 94.2 56.1
CZ Czech Republic 80.8 76.5 51.7 48.7 46.3
DE Germany 61.5 72.6 59.4 61.3 63.2
DK Denmark 76.4 64.5 43.6 50.2 69.7
EE Estonia 92.0 71.1 80.4 83.6 96.4
ES Spain 91.5 91.4 88.1 70.8 75.1
FI Finland 94.3 NA NA 94.8 NA
FR France 64.8 45.3 39.8 32.3 46.4
GR Greece 82.9 86.1 97.7 91.6 82.9
HR Croatia NA NA 88.8 57.8 45.6
HU Hungary 95.3 94.5 75.0 52.4 23.7
IE Ireland 83.0 87.3 82.3 67.3 60.8
IT Italy 90.4 93.9 92.4 73.4 75.1
LT Lithuania 93.6 88.3 93.9 89.1 85.8
LU Luxembourg 98.4 99.1 95.0 91.3 87.5
LV Latvia 72.6 82.3 80.1 95.3 NA
MT Malta NA 98.7 89.4 59.6 79.5
NL Netherlands 71.1 73.5 57.2 45.0 59.4
PL Poland 94.5 93.6 86.6 90.2 59.3
PT Portugal 95.7 95.9 90.9 74.8 48.6
RO Romania NA 96.6 85.9 67.3 60.4
SE Sweden NA 89.2 90.6 78.7 93.0
SI Slovenia 89.5 93.5 91.5 78.9 52.4
SK Slovakia 83.2 78.9 66.7 23.4 28.6
U2 Euro area (changing composition) 79.2 81.5 69.9 60.5 64.8

France, Spain, Portugal

Code 
RAI |>
  filter(DD_ECON_CONCEPT == "SVLHHNFC",
         REF_AREA %in% c("FR", "ES", "PT")) |>
  month_to_date() %>%
  select_if(~n_distinct(.) > 1) |>
  add_flag_color("Ref_area") |>
  mutate(OBS_VALUE = OBS_VALUE/100) |>
  ggplot() + theme_minimal() + xlab("") + ylab("Share of variable rate, households and firms (%)") +
  geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  add_flags(3) + scale_color_identity() +
  scale_x_date(breaks = seq(1960, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 5),
                     labels = percent_format(accuracy = 1))

Italy, Sweden, Poland

Code 
RAI |>
  filter(DD_ECON_CONCEPT == "SVLHHNFC",
         REF_AREA %in% c("PL", "IT", "SE")) |>
  month_to_date() %>%
  select_if(~n_distinct(.) > 1) |>
  add_flag_color("Ref_area") |>
  mutate(OBS_VALUE = OBS_VALUE/100) |>
  ggplot() + theme_minimal() + xlab("") + ylab("Share of variable rate, households and firms (%)") +
  geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  add_flags(3) + scale_color_identity() +
  scale_x_date(breaks = seq(1960, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 5),
                     labels = percent_format(accuracy = 1))

Netherlands, Germany, Belgium

Code 
RAI |>
  filter(DD_ECON_CONCEPT == "SVLHHNFC",
         REF_AREA %in% c("NL", "DE", "BE")) |>
  month_to_date() %>%
  select_if(~n_distinct(.) > 1) |>
  add_flag_color("Ref_area") |>
  mutate(OBS_VALUE = OBS_VALUE/100) |>
  ggplot() + theme_minimal() + xlab("") + ylab("Share of variable rate, households and firms (%)") +
  geom_line(aes(x = date, y = OBS_VALUE, color = color)) + 
  add_flags(3) + scale_color_identity() +
  scale_x_date(breaks = seq(1960, 2100, 2) |> paste0("-01-01") |> as.Date(),
               labels = date_format("%Y")) +
  scale_y_continuous(breaks = 0.01*seq(-10, 100, 5),
                     labels = percent_format(accuracy = 1))