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Estimating Loss-Given-Default through Survival Analysis: A quantitative study of Nordea's default portfolio consisting of corporate customers
Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
2016 (English)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

In Sweden, all banks must report their regulatory capital in their reports to the market and their models for calculating this capital must be approved by the financial authority, Finansinspektionen. The regulatory capital is the capital that a bank has to hold as a security for credit risk and this capital should serve as a buffer if they would loose unexpected amounts of money in their lending business. Loss-Given-Default (LGD) is one of the main drivers of the regulatory capital and the minimum required capital is highly sensitive to the reported LGD.

Workout LGD is based on the discounted future cash flows obtained from defaulted customers. The main issue with workout LGD is the incomplete workouts, which in turn results in two problems for banks when they calculate their workout LGD. A bank either has to wait for the workout period to end, in which some cases take several years, or to exclude or make rough assumptions about those incomplete workouts in their calculations.

In this study the idea from Survival analysis (SA) methods has been used to solve these problems. The mostly used SA model, the Cox proportional hazards model (Cox model), has been applied to investigate the effect of covariates on the length of survival for a monetary unit. The considered covariates are Country of booking, Secured/Unsecured, Collateral code, Loan-To-Value, Industry code, Exposure-At- Default and Multi-collateral. The data sample was first split into 80 % training sample and 20 % test sample. The applied Cox model was based on the training sample and then validated with the test sample through interpretation of the Kaplan-Meier survival curves for risk groups created from the prognostic index (PI). The results show that the model correctly rank the expected LGD for new customers but is not always able to distinguish the difference between risk groups.

With the results presented in the study, Nordea can get an expected LGD for newly defaulted customers, given the customers’ information on the considered covariates in this study. They can also get a clear picture of what factors that drive a low respectively high LGD. 

Abstract [sv]

I Sverige måste alla banker rapportera sitt lagstadgade kapital i deras rapporter till marknaden och modellerna för att beräkna detta kapital måste vara godkända av den finansiella myndigheten, Finansinspektionen. Det lagstadgade kapitalet är det kapital som en bank måste hålla som en säkerhet för kreditrisk och den agerar som en buffert om banken skulle förlora oväntade summor pengar i deras utlåningsverksamhet. Loss- Given-Default (LGD) är en av de främsta faktorerna i det lagstadgade kapitalet och kravet på det minimala kapitalet är mycket känsligt för det rapporterade LGD.

Workout LGD är baserat på diskonteringen av framtida kassaflöden från kunder som gått i default. Det huvudsakliga problemet med workout LGD är ofullständiga workouts, vilket i sin tur resulterar i två problem för banker när de ska beräkna workout LGD. Banken måste antingen vänta på att workout-perioden ska ta slut, vilket i vissa fall kan ta upp till flera år, eller så får banken exkludera eller göra grova antaganden om dessa ofullständiga workouts i sina beräkningar.

I den här studien har idén från Survival analysis (SA) metoder använts för att lösa dessa problem. Den mest använda SA modellen, Cox proportional hazards model (Cox model), har applicerats för att undersöka effekten av kovariat på livslängden hos en monetär enhet. De undersökta kovariaten var Land, Säkrat/Osäkrat, Kollateral-kod, Loan-To-Value, Industri-kod Exposure-At-Default och Multipla-kollateral. Dataurvalet uppdelades först i 80 % träningsurval och 20 % testurval. Den applicerade Cox modellen baserades på träningsurvalet och validerades på testurvalet genom tolkning av Kaplan-Meier överlevnadskurvor för riskgrupperna skapade från prognosindexet (PI).

Med de presenterade resultaten kan Nordea beräkna ett förväntat LGD för nya kunder i default, givet informationen i den här studiens undersökta kovariat. Nordea kan också få en klar bild över vilka faktorer som driver ett lågt respektive högt LGD. 

Place, publisher, year, edition, pages
2016. , p. 39
Keywords [en]
Survival analysis, Cox proportional hazards model, Loss-Given-Default, workout LGD, Recovery data
National Category
Mathematics
Identifiers
URN: urn:nbn:se:umu:diva-122914OAI: oai:DiVA.org:umu-122914DiVA, id: diva2:942475
External cooperation
Nordea Bank AB
Educational program
Master of Science in Engineering and Management
Supervisors
Examiners
Available from: 2016-06-27 Created: 2016-06-24 Last updated: 2016-06-27Bibliographically approved

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