AGNITYA Quantitative Solutions and Asset Management
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AGNITYA Quantitative Solutions and Asset Management

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  • AGNITYA Quant Solutions
  • Agnitya
    • About us
    • Career
    • Contact Us
  • Financial Services
    • Banking
    • Insurance
  • Quantitative Solutions
    • Risk Management Solution
    • Capital Market Solution
    • Asset Managment Solution

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Regulatory Models

Pillar-1 Capital Requirement Models

AGNITYA provides the Pillar-1 regulatory models under Basel-II for-

  1.  Capital requirement due to credit risk:  The Internal ratings-based (IRB) approach to capital requirements for credit risk with standard method and advanced method. Standard IRB  approach is an independent AgT-RMS module, which can be used with any position keeping system.
    We provide services to develop the advanced IRB (A-IRB) model to banking and Insurance industries.
  2. Capital requirement due to the operational risk: AGNITYA developed the independent module with
    i) Basic indicator approach
    ii) Standardised approach
    For the advanced measurement measurement approach (AMA), AGNITYA provides services to develop the model.
  3. Capital requirement due to market risk: AGNITYA develops the independent tool for the CAR due to market risk in banking book (IRRBB) and trading book (FRTB). The standard model for FRTB is an independent module of AgT-RMS and can be harmonised with any position keeping system.
    The IRRBB model is a framework and AGNITYA provides services to develop the IRRBB model to the client.
  4. SA-CCR Model: AGNITYA provides the tool for the standardised approach for measuring the counter party credit risk exposure.
    AGNITYA's advanced module can also provide the advance approach for CCR models based on 3-factor gaussian process.

Pillar-2 Capital Requirement Models

  1. Economic capital model:
    The AGNITYA solution for the Economic capital model is an extended version of VAR module of AgT-RMS,  which incorporate the dynamic interaction between the credit risk and other market risks under worst case scenario. 
  2. Liquidity risk model:
    The liquidity risk modelling is based on advance multivariate adaptive regression process with analytical traceability.

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