Financing Scenarios

Scenario datasets provide dated sets of future assumptions. They are not observed future rates, guaranteed offers or forecasts with assigned probabilities. Use them to explore conditional outcomes rather than to claim what will happen.

All use daily snapshot filters (YYYY-MM-DD). Future projection points are selected separately with horizon_from_month and horizon_to_month, integers 0-120 inclusive. If omitted, the full supported range is requested.

Scenario Choices

`scenario`	Interpretation
`market_base`	Reference path based on the accepted market and financing inputs. Not a guaranteed outcome or probability-weighted expectation.
`higher_for_longer`	A hypothetical path with more persistent elevated rates.
`rapid_cuts`	A hypothetical faster-easing path.
`refinancing_stress`	A hypothetical stressed refinancing environment.

The chosen dataset and returned observations determine the actual assumptions. Scenario labels do not imply a universal fixed shock to every instrument. No custom shock input, probability, arbitrary LTV or borrower-specific margin is accepted.

SONIA Forward Rate Path

Dataset: sonia_forward_path. Required: dataset. Optional: horizon bounds. Metric: rate_pct, unit percent, basis scenario.

http

GET /v1/rates/series?dataset=sonia_forward_path&horizon_from_month=0&horizon_to_month=24

This exposes curve-implied one-month forward-rate assumptions for future intervals. It is distinct from the instantaneous OIS forward curve and from the realised overnight SONIA series.

There is no scenario override on this dataset: it uses its accepted reference path. Each horizon identifies an interval start. Use returned projection start/end dates when labelling a chart. The interval beginning at month 120 can end at month 121.

Bank Rate Scenarios

Dataset: bank_rate_scenarios. Required: dataset. Optional: scenario (default market_base), horizon bounds. Metric: rate_pct, unit percent, basis scenario.

http

GET /v1/rates/series?dataset=bank_rate_scenarios&scenario=higher_for_longer&horizon_to_month=60

Modelled policy-rate assumptions for analysis. These are not predictions of individual Monetary Policy Committee decisions or a probability distribution. Do not infer a forecast probability from a rate path crossing a threshold.

Buy-to-Let Refinancing Rate Scenarios

Dataset: btl_refinancing_scenarios. Required: dataset. Optional: scenario (default market_base), term_years (2 or 5), horizon bounds. Metric: rate_pct, unit percent, basis scenario.

http

GET /v1/rates/series?dataset=btl_refinancing_scenarios&scenario=market_base&term_years=5&horizon_from_month=12&horizon_to_month=60

Indicative future fixed-rate refinancing assumptions combining market-curve and mortgage-benchmark evidence. Both supported terms use 75% LTV; ltv_pct: 75 appears as response metadata, not a freely adjustable input. Omitting the term returns both supported terms.

The result is not an all-in financing cost, personalised offer, credit decision or guarantee of availability. Fees and borrower-specific terms are not comprehensively modelled. Keep underlying mortgage observation dates when displaying a daily scenario snapshot.

Mortgage Reversion Rate Scenarios

Dataset: mortgage_reversion_scenarios. Required: dataset. Optional: scenario (default market_base), horizon bounds. Metric: rate_pct, unit percent, basis scenario.

http

GET /v1/rates/series?dataset=mortgage_reversion_scenarios&scenario=rapid_cuts&horizon_to_month=36

Modelled future reversion-rate assumptions based on the scenario and available benchmark evidence. They do not specify what a particular lender will charge under a customer's mortgage contract. No mortgage product, fixed term or LTV selector applies.

Financing Stress Scenarios

Dataset: financing_stress_scenarios. Required: dataset, scenario. Optional: horizon bounds and a metrics subset. Unlike the Bank Rate, buy-to-let refinancing and mortgage reversion scenario datasets, this grouped dataset requires an explicit scenario.

http

GET /v1/rates/series?dataset=financing_stress_scenarios&scenario=refinancing_stress&horizon_to_month=60&metrics=bank_rate_pct,btl_5y_75ltv_pct

Metric	Meaning	Unit
`sonia_rate_pct`	SONIA forward assumption.	`percent`
`bank_rate_pct`	Bank Rate assumption.	`percent`
`swap_2y_pct`	Two-year swap-equivalent assumption at the future start.	`percent`
`swap_5y_pct`	Five-year swap-equivalent assumption at the future start.	`percent`
`swap_10y_pct`	Ten-year swap-equivalent assumption at the future start.	`percent`
`btl_2y_75ltv_pct`	Two-year, 75% LTV BTL refinancing assumption.	`percent`
`btl_5y_75ltv_pct`	Five-year, 75% LTV BTL refinancing assumption.	`percent`
`mortgage_reversion_pct`	Mortgage reversion assumption.	`percent`

All eight are default metrics; access must cover every requested metric or the caller must select an entitled subset. Multiple metrics across all 121 horizon starts can span pages. Do not assume one HTTP response contains the whole requested surface.

Historical Scenarios and Time Axes

period/snapshot_date identify the saved model snapshot. horizon_month and projection/interval fields describe the future path from that snapshot. The API does not rebuild a past scenario using today's inputs, and an old daily date is not valid evidence that a historical scenario snapshot was retained.

Omit dates for the latest stored snapshot before horizon filtering. Missing nodes are not filled from older snapshots. Request a retained release_id and snapshot date when reproducing a prior analysis. A daily scenario refresh and a monthly mortgage observation can coexist: both dates matter.

For display, make the snapshot date visible next to the scenario name. Put projection dates, not snapshot dates repeated 121 times, on a future-path axis. Retain each instrument's interval end, because a five-year swap beginning at a horizon point is not a one-month rate at that point.