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Оценка качества ссудного портфеля по данным на уровне займа // Assessing the quality of loan portfolio based on the loan level data

Author

Listed:
  • Хакимжанов С.Т. // Khakimzhanov S.T.

    (National Bank of Kazakhstan)

  • Конурбаева Н.А. // Konurbayeva N.A.

    (National Bank of Kazakhstan)

  • Нурханова О.В. // Nurkhanova O.V.

    (National Bank of Kazakhstan)

Abstract

В этой статье проводится анализ источника информации – Кредитный регистр, для оценки портфеля банков на уровне каждого займа (loan level data). В статье вводится понятие дефолта, основанного на косвенных показателях с использованием кредитного регистра. Разрабатываются показатели, которые можно использовать для оценки динамики состояния каждого займа с возможностью агрегирования на уровень заёмщика. Проводится аналитическая оценка, позволяющая выявить рефинансированные займы и «вечнозелёные» займы. Описаны и внедрены категории для распределения займов внутри портфеля с целью своевременного выявления ухудшения состояния займа, позволяющего применять меры раннего реагирования со стороны надзорного органа, а также оценивать кредитный риск на уровне банковской системы. Проведена проверка качества методики на основе имеющихся исторических сведений по передаче портфеля в Фонд проблемных кредитов и признания банком займов с просроченной задолженностью свыше 90 дней перед лишением лицензии, а также оценён объём ложноположительных значений, выявляемых по методике, но в последующем предоставленным в Кредитный регистр с нулевым основным долгом. Представленная методика является первой попыткой применения анализа на основе займа в Казахстане, которую можно развивать с использованием новых расширенных данных по займу и заёмщику, внедрённых в Кредитный регистр с июля 2019 года. Кроме того, следующим этапом после оценки качества портфеля планируется оценка вероятности дефолта заёмщика, а также проведение стресс тестирования. // This Paper analyzes the source of information – the Credit Registry – to assess the portfolio of banks at the level of each loan (loan level data). The Paper introduces the concept of default based on indirect indicators using the Credit Registry. Indicators that can be used to assess the dynamics in the status of each loan with the ability to aggregate at the borrower level are being designed. An analytical assessment is conducted to identify refinanced loans and “evergreen” loans. The categories for the distribution of loans within the portfolio are described and introduced in order to identify the deterioration of loan on a timely basis, allowing the application of early response measures by the supervisor as well as the assessment of credit risk at the banking system’s level. The quality of the methodology was checked on the basis of available historical information about the transfer of the portfolio to the Problem Loans Fund and the recognition by the bank of loans past due more than 90 days before the license was revoked; in addition, the volume of false positives detected by the methodology but subsequently submitted to the Credit Registry with zero main debt was assessed. The presented methodology is the first attempt of applying a loan-based analysis in Kazakhstan that can be developed using the new extended loan and borrower data incorporated into the Credit Registry since July 2019. Besides, the next stage after assessing the quality of portfolio will be the assessment of probability of borrower’s default as well as the stress testing.

Suggested Citation

  • Хакимжанов С.Т. // Khakimzhanov S.T. & Конурбаева Н.А. // Konurbayeva N.A. & Нурханова О.В. // Nurkhanova O.V., 2021. "Оценка качества ссудного портфеля по данным на уровне займа // Assessing the quality of loan portfolio based on the loan level data," Economic Review(National Bank of Kazakhstan), National Bank of Kazakhstan, issue 3, pages 4-24.
  • Handle: RePEc:aob:journl:y:2021:i:3:p:4-24
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    References listed on IDEAS

    as
    1. Liana Kirakosyan, 2014. "The Central Bank of Armenia's project of a credit registry," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Proceedings of the Porto Workshop on "Integrated management of micro-databases", volume 37, pages 15-17, Bank for International Settlements.
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      Keywords

      кредитный риск; кредитный анализ; вероятность дефолта; кредитный регистр; анализ на уровне займа; рефинансирование; «вечнозелёные» займы; credit risk; loan review; probability of default; Credit Registry; loan-level review; refinancing; evergreen loans;
      All these keywords.

      JEL classification:

      • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
      • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods
      • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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