Each loan's collateral is modelled from the property up and run through 10,000 correlated economic scenarios. Probability of default, loss given default, expected loss and maximum probable loss are measured for every year of the loan, and across the whole book.
Book a 30-minute callCredit decisions are expected to show their working: what a loan could lose, how likely that is, and what would change it.
Market risk and the risk specific to each loan, from a tenant leaving to a contractor failing, combined in one measure.
Credit losses follow non-normal distributions, skewed and long in the tail. Each loan's distribution is measured directly, tail included.
The analysis that priced the loan supports the provision, the capital assessment and the stress test.
PROMS Lender models the property behind each loan, from its leases or occupancy, operating costs and capital expenditure, then applies the loan's own terms: interest, covenants, reserves and repayment. The loan is then run through 10,000 correlated economic scenarios. In each one it performs or defaults, and any loss is measured. The share of scenarios that end in default is the probability of default. The losses give loss given default, expected loss, and the maximum probable loss at any confidence level.
The scenarios start from whichever view of the market the institution holds: its house view, its own data, or the major providers, including market subscriptions under the client's own licence. That data is put to work measuring volatility, which is what sets the range of outcomes for every loan.
Because every input sits in the same model, the drivers are visible as well as the result. Change the NOI, the capital expenditure, the property value, the interest rate or the refinancing assumptions, and probability of default, loss given default and expected loss move with them, so a credit team sees what is driving the expected loss as well as its size.
The highlighted step is where one cashflow becomes 10,000 outcomes. Everything to its right is measured from those outcomes.
Move any driver and trace its effect through to PD, LGD and expected loss. PROMS shows what is driving the expected loss.
NOI against debt service · $000s a year
Loan balance against collateral value · indexed to 100 at origination
Probability of default, loss given default, expected loss and maximum probable loss for every loan, translated into an agency-equivalent rating.
Risk-adjusted return and economic profit for each loan and tranche, with alternative structures compared before terms are agreed.
Collateral values, covenants and ratings kept current between valuations, with expected loss and stress reporting supported by the same numbers.
Every stage of the credit lifecycle is computed from the same collateral model, so valuation and credit work from one set of numbers, with a traceable record from the valuer's base case through to reporting.
Property-level cashflow model and concluded value at deal entry, tied to your loan management system.
Indexed LTV, DSCR and ICR re-run against centralised market assumptions.
Probability of default, loss given default and expected loss measured from the collateral cashflow model, to support provisioning and credit review.
Concluded value reconciled to your loan management system, cashflow reconciled to the valuer base case.
Probability of default, loss given default and expected loss translate into an agency-equivalent rating, then into risk-adjusted return and economic profit, so senior and junior tranches are priced for the risk each carries. Maximum probable loss, at the confidence level the institution sets, supports capital analysis, loan by loan and across the book.
Capital follows measured risk, and pricing follows capital.
Alternative structures are compared on their loss distributions alongside the base case: seniority, maturity extensions, repayment arrangements, reserve accounts and cash traps. Each shows its effect on the probability of default, on recoveries if the loan does default, and on risk-adjusted return. Refinancing risk is measured at maturity, where the property's value and income in each scenario show whether the loan can be repaid or refinanced on the terms the market will then offer.
The credit committee compares risk-adjusted returns and can see the effect of each structure.
Indexed collateral values keep loan to value and covenant ratios current between full external valuations. Expected loss, grade migration, and tenant and sponsor concentration show where the book is exposed. Outputs to support CECL, IFRS 9 and CCAR reporting come from the same model the underwriters used.
Risk can be reviewed as assumptions change, while there is still time to act.
Every loan priced, structured and monitored on one measure of risk, from the underwriter's desk to the board.
Thirty minutes with the team to understand what you are trying to solve and where PROMS fits.
Reference material for the reader who has to build the case internally.
Senior to mezzanine, stabilised to construction, on one engine.
Senior loans, B notes and mezzanine. Construction, value-add and bridging loans. Fixed and floating, syndicated and bilateral, multi-tranche and multi-currency facilities, and full recourse lending with sponsor financials. Secured on all major CRE asset types. Construction loans simulate delay, budget overrun, contractor default, lease-up and exit value together.
A distribution of outcomes, with the tail measured directly.
Each loan's collateral is modelled and run through 10,000 correlated economic scenarios, combining market risk with events specific to the loan, such as a tenant default, a lease expiry or a contractor failure. Probability of default, loss given default and expected loss are reported year by year and over the life of the loan. Maximum probable loss is reported at a chosen confidence level, on a marginal or standalone basis. Each distribution is measured directly, including the non-normal, long-tailed shape of credit losses.
How a loan defaults, as well as whether it does.
Each scenario records the event behind a default: a credit or in-life default when income no longer covers debt service; a refinance default when the loan performs through its term but the property's value or income at maturity will not support repayment or a new loan; a construction default from delay, overrun or contractor failure; and covenant breaches that trigger before payments stop. PD, LGD and expected loss are reported by event, so a loan that looks sound on in-life measures can still show refinancing risk building ahead of maturity. Monitoring and lending decisions can then respond to the event most likely to cause a loss, as well as to the overall level of risk.
Every loan assessed for its risk, return and capital needs.
Agency-equivalent ratings from probability of default and expected loss. Risk-adjusted return, risk-adjusted return on capital (RAROC) and economic profit, by loan and by tranche. Maximum probable loss and economic capital measures help lenders assess the capital required for the risk each loan carries.
Any view of the market, put to work measuring volatility.
The house view, the institution's own data, or the major providers, including market subscriptions under the client's own licence. Published Federal Reserve CCAR scenarios can be used for stress testing. Assumption sets are version-controlled and applied consistently across the book, and any period can be re-run under any set to attribute the variance.
Collateral and covenants kept current between full valuations.
LTV, DSCR, ICR and debt yield tracked against covenant thresholds, with early warning indicators. Indexed collateral values support monitoring between external valuations. Maturity dates and extension options are captured at deal level.
The book's exposure and reporting inputs, from one run.
Grade migration, exposure run-off, and concentration by tenant, sponsor and sector. Bottom-up stress tests across every portfolio. Expected credit loss and stress outputs, by loan and by portfolio, support CECL, IFRS 9 and CCAR reporting workflows.
Every number can be opened, traced and reproduced.
Appraisal, underwriting, annual review and portfolio monitoring run on one flow of information, so front and middle office work from the same data. Every version is named and date-stamped, workflow confirms that risk mitigants are in place and documents are signed off, and any historic analysis can be reproduced exactly. Every input, assumption and output exports to Excel.
No. Each institution chooses the level of analysis it needs, from loan ratios to full simulation, and the economic scenario sets are maintained and refreshed each quarter by Radley Associates.
Yes. Argus files import directly, and an API connects PROMS to loan administration, servicing and data systems.
No. Existing credit committee and regulatory reports can be reproduced as templates driven straight from the model, so committees and regulators keep receiving the output they recognise.
AI-native deal screening. From broker PDF to institutional underwriting in minutes.
Cashflow forecasting, Underwriting, Asset & Fund-level reporting. Rapid Stress testing on individual assets, portfolios and funds.
Macro-economic simulation, portfolio construction, value-at-risk, Benchmarking and alpha analysis.
Underwriting, pricing, ratings and portfolio risk. CECL, IFRS 9 and Basel II built in.