Passive Breach Risk

Posted under case studies on June 02 , 2020 by Rohan Jangid


In Mutual Funds, investments are done by Fund Managers. Their job is to invest the retail investors’ money in different securities and increase the value of the fund while maintaining the objective of the mutual fund schemes.

When a mutual fund scheme is launched (known as New Fund Offer [NFO]), it provides a document, called Offer Document (OD), it contains the profile of the fund and limits on various investments.

These objectives not only help the investors to choose the fund which aligns with their goals and risk profile but also for fund managers to keep their investment harmonized with the decided profile.

The above restrictions/limits must be maintained by the Fund Manager; they are called OD Limits.

The other restrictions are imposed by SEBI, to avoid any large concentration of a security/industry/company in the fund, and hence, any major risk. These are known as Regulatory Limits.

Internal Limits are similar to regulatory but are setup by the AMC for their internal use or as an alert system for the regulatory limits.

The last kind of limit is called Credit Limit. MF’s Analyst studies the companies’ profile and based on their ratings [Given by Credit Rating Agencies] they assign an investment limit based on the time-period. Higher the time-period, lower will be the investment limit because risk increase with time. SheetKraft maintains a separate module for Credit Limit.

Scope of the Problem:

These limits are managed by the Risk Management Department in an AMC. It is usually managed in two ways, manually in excel or some external automation platform.

Let us see the issues faced in the above two scenarios:

  1. Manual/Macro Excel
    a. Create another excel sheet for a new limit.
    b. No centralized data.
    c. Auditing is not possible.
    d. Slower to use.
    e. Prone to manual errors.
  2. External automation platform
    a. Only a generic set of limits can be created.
    b. Complexity in limit is not entertained. [Only a linear connection of AND or OR]
    c. New Limit cannot be created by the users.
    d. Calculation/Report generation is done on the user machine which makes the machine slower and/or unable to use during the run time.
    e. No backdated calculations.
    f. No bulk calculations.
    g. Users must retain each report for audit purposes.

Introduction of SheetKraft:

SheetKraft, a rapid application platform for all kind and nature of calculations and logics, was used to solve the above problems and to create a stand-alone application for all Passive Breach purposes, from uploading data to generating reports.

Passive Breach Risk in SheetKraft:


The above flowchart is for an AMC having 150+ Mutual Funds and 150+ Limits.

Features by SheetKraft for Passive Breach:

  1. A common user-friendly platform to encompass all the limits. Designed after studying 150+ Limits.
  2. By using the checklist [a SheetKraft feature of combining multiple process together], the whole process is covered in just 2-steps.
  3. Limits/Masters can be added/edited by the user.
  4. A new version of the limit can be created [For e.g., a policy is changed, and the limit must be slightly modified but the trend must be maintained for the same original limit.]
  5. The application uses SQL for calculation and hence can incorporate any level of complexities in the limit condition. [Combination of AND, OR, NOT, IN]
  6. All the calculations are done on the server and hence no load on the user’s machine.
  7. For the same reason as above, the user is free to utilize the machine during the calculation period for some other work.
  8. Provision for backdated calculations.
  9. Provision for bulk calculations.
  10. Audit trail maintenance. No need to keep the downloaded reports on the machine. User can download it from the SheetKraft as per the requirement.
  11. Generation of Limit-wise report, dashboard report, and trend report.
  12. Scheduled data import from NSE, AMFI websites.
  13. The user can update the limit value, and as everything is mapped with a date so no issues in the calculation/report.

Creating a Limit:

Let us go through an actual limit imposed by SEBI onto the mutual funds.

12.4.1 Mutual Funds/AMCs shall ensure that total exposure of debt schemes of mutual funds in a particular sector (excluding investments in Bank CDs, CBLO, G-Secs, TBills, short term deposits of Scheduled Commercial Banks and AAA rated securities issued by Public Financial Institutions and Public Sector Banks) shall not exceed 25% of the net assets of the scheme.

Provided that an additional exposure to financial services sector (over and above the limit of 25%) not exceeding 15% of the net assets of the scheme shall be allowed only by way of increase in exposure to Housing Finance Companies (HFCs).

Provided further that the additional exposure to such securities issued by HFCs are rated AA and above and these HFCs are registered with National Housing Bank (NHB) and the total investment/ exposure in HFCs shall not exceed 25% of the net assets of the scheme.

SEBI Circular:

The above draft from the SEBI circular can be divided in 4 simple parts:

  • In Closed-Ended Debt Schemes, investment in Non-Financial Services should be less than 25%.
  • In Closed-Ended Debt Schemes, investment in HFCs and Financial Services should be less than 40%.
  • In Closed-Ended Debt Schemes, investment in only HFCs should be less than 25%.
  • In Closed-Ended Debt Schemes, investment Financial Services and No HFCs should be less than 25%.

A given condition [Filter] is used to select the relevant data for the aggregation of the investment/market value.

The below filter is for the first limit, Investment in debt scheme and non-financial services should be less than 25%.


Using the above filter, we will get the SUM(Market Value) [Variable 1] and divide that with the AUM [Variable 2] at Scheme and Sector level. And this ratio [Aggregate Variable] should be less than 25% [Parameter Value] according to the limit.

Similarly, other 150+ limits are structured and stored in different database tables. The calculation is done for each limit over the standardized portfolio data and reports are generated.

Impact of Automating with SheetKraft:

The two-step process has substituted the earlier rigid system. The flexibility to add multiple and nested logic has helped to incorporate all the limits including the ones that were maintained separately on excel and were prone to error.

One of the clients have currently used SheetKraft’s PBR module to run the backdated calculation starting from 2018 to 2020 for audit check.

Elimination of all the manual errors with automation and with multiple validation checks, sanity check of all the different masters is possible and can be rectified in case of any error.

In short, SheetKraft’ stand-alone application for PBR has provided a simpler tool at the hand of the client and have pushed the time-consuming processes onto the server.

TAGGED:Passive Breach RiskMutual FundsSEBI

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