EU-wide 2016 stress testing results

By | Asset Quality Review & Stress Testing

We have put the EU wide stress test 2016 data published by EBA into a user friendly environment. The use can compare the resulst of different banks in different countries and jurisdictions.We will repeat this exercise in November 2018 once the new results are available.


All OSIS tools are available online and accessible through desktop or mobile devices.If you need mor detail, please contact us.

Athena™ Credit Risk Transfer Analysis

By | General

OSIS has developed Athena to support originators and investors to structure a Credit risk transfer transactions. With Athena the user can navigate through a changing regulatory and macro economic landscape and to optimize the underlying loan portfolio composition from both an investors’ and an originators’ perspective.

Dashboard of RWA and Expected Credit loss forecasting.

Athena offers easy to use portfolio analytics looking at many different variables:

  • Industry compositions (SME, CRE, Large Corp, Project Finance)
  • Single name concentrations (SME)
  • LTV buckets (RMBS, CRE)
  • PD and LGD compositions
  • Maturity profile
  • PD & LGD estimates from OSIS (RMBS).


Dashboard to stress test expected credit losses and RWA in function of EBA or FED defined macro scenarios.

Athena offers a credit model with in-depth economic analyses of the pool and potential tranches:

  •  IRR at each confidence level as a function of:
    • Attachment and detachment point of each tranche
    • Macro stress scenario
    • Coupon
    • Discount rate
    • Excess spread
    • Sequential or pro rate amortization
    • Time calls and clean up calls
  • Providing an iterative process to amend the composition of the pool or change pricing / tranching
  • Value the transaction in function of different stress and regulatory scenarios discounting the invested amount of capital against future capital repayments and realized capital relief, timing of provisions (CECL, IFRS9), protections fees and net income

Transaction performance outputs: expected IRR Investor, portfolio p&l forecast, cost of relieved capital, optimisation on tranching and check on SRT requirements.

Hypotheek Risico Checker

By | News

Hoe risicovol is uw hypotheek in vergelijking met die van andere huizenbezitters?

De Nederlandse huizenmarkt lijkt zich geheel hersteld te hebben van de kredietcrisis. Volgens Calcasa zijn de huizenprijzen in het eerste kwartaal van 2018 in 12 maanden tijd met 9% gestegen en zijn de prijzen landelijk al weer 12% hoger dan 10 jaar geleden. In Amsterdam liggen de huizenprijzen al weer 43% hoger dan 10 jaar geleden.

De vraag die zich nu aandient is staan we aan de vooravond van een nieuwe bubbel in de huizenmarkt en hoe bewust zijn de aspirant-kopers van het risico dat ze lopen bij het kopen van een huis en het aantrekken van een hypothecaire geldlening; voor velen de meest risicovolle beslissing in hun leven?

OSIS heeft statistisch model ontwikkeld op basis van 40% van de Nederlandse hypothekenmarkt. Op basis van 7 variabelen kan de gebruiker zien wat de kans op betalingsproblemen is en hoe het risico zich verhoudt ten opzichte van andere huizenbezitters met een hypotheek. Aan de linkerkant van het plaatje zitten de minst risicovolle huizenbezitters en aan de rechterkant de huizenbezitters met het hoogste risico.

Daarnaast kan de gebruiker bekijken wat de situatie wordt als er op korte termijn weer een huizencrisis komt zoals tijdens de kredietcrisis (huisprijsdaling 21%) of de nog grotere huizen crisis eind jaren ’70 (huisprijsdaling van 35%). In de laatste check gaan we er vanuit dat alleen het huis van de gebruiker door de crisis wordt geraakt en de distributie ongewijzigd blijft.

Met deze tool hopen we dat particulieren meer bewust worden van het risico dat ze lopen bij het aangaan van een hypothecaire geldlening. De resultaten van dit model zijn slechts een indicatie en dus aanvaarden wij geen enkele aansprakelijkheid. Daarnaast zal model in de toekomst worden aangepast op basis van nieuwe ervaringsgegevens waardoor de resultaten kunnen veranderen.


Mortgage Loan Risk Checker

By | News

How risky is your mortgage in comparison to other homeowners?

The Dutch housing market appears to be recovering from the credit crisis. According to Calcasa, property prices in the first quarter of 2018 increased by 9% over the previous 12 months and 12% over the last 10 years. In a city as Amsterdam, house prices have even increased by 43% over the last 10 years.

Are we entering a new bubble and are prospective homebuyers aware of the risks they run when buying a home with a mortgage – for many borrowers this could be the most risky decision of their lives?

OSIS has developed a statistical model based on 40% of the Dutch mortgage market. Based of seven variables, the user can see how their mortgage payment risk is rated relative to other home owners with a mortgage. To the left of the picture are the least risky homeowners and on the right, the most risky.

In addition, the user can see how things look in the short term if there is a housing crisis as during the credit crisis (house prices fell 21%) or an even larger housing crisis as in the late 1970’s (house prices fell 35%). In the last check we do, we assume that only the user’s home is hit by the crisis and the others remains unchanged.

With this tool, OSIS hope that individuals become more aware of the risks they run when taking out a mortgage. The results of this model are indicative only and therefore OSIS accept no liability. OSIS will adjust and update the model in the future based on new empirical data which may change the results.


IFRS 13 Residential Mortgage Valuation

By | General, News

IFRS 13 Residential Mortgage Valuation

We determine a fair market value of Dutch Residential mortgages, in accordance with IFRS 13 using a loan level data provided by the originators.

IFRS 13 does not specify a detailed approach to use for valuing assets and therefore there is no market standard for the valuation of mortgages. The market value is the price that a knowledgeable and willing seller and buyer would agree in an orderly arm’s length transaction at the reference date. IFRS 13 essentially requires to follow the same approach in valuation that such market participants would use to agree on the price.

The Dutch Central Bank (DNB) has published guidance on the fair value determination of Dutch mortgages for prudential purposes. Our valuation method aims to meet both IFRS and prudential requirements:

  1. The amortization type of the mortgages (annuity, linear, bullet)
  2. Time to interest reset of fixed rate mortgages
  3. The guarantee from NHG (if any)
  4. Current loan to value of the mortgage
  5. Product specific-options (caps/floors) including the option of the borrower to prepay without penalty

Further we model on the loan level expected credit loss (compliant with IFRS9), expected prepayments. We follow an extensive process to build these models.

Credit model flow chart explaining all individual steps in the modeling process.

Therefore, our valuations not only take into account the actual point of the cycle but also could be stressed in function of FED or EBA defined or user defined macro scenarios.

In-sample 1t and residuals for the reference default macro model (blue) and a model using the mortgage spread for comparison.

To contact us, complete the fields below and we’ll get back to you or call us at +31703260370.



Open Source Investor Services B.V. (OSIS)
WorldTrade Centre The Hague
Prinses Margrietplantsoen 33
2595 AM The Hague
The Netherlands

[TEL] +31 70 32 60 370