ARMOL

PG Diploma in Securities Market: 2007-08 (SMP).

Indian Institute of Capital Markets.

Corporate project – Religare Securities Ltd.

Analysing Risk Management at the Operational Level in a Broking company.

The project is a credit paper of the PGDSM curriculum, IICM. This is a corporate project report prepared by Saurav Mishra with Religare Securities Ltd., BBSR.

Analysing Risk Management at the Operational Level in a Broking Company.

The report has been prepared as a corporate project with Religare Securities Ltd., (BBSR), as part of the Securities Market Programme, IICM curriculum. The user is solely responsible for conclusions, applications and results derived.

Preface -

The report aims at analysing and integrating the central Risk Management services and the risk management at the Operational level in a Broking company. This requires understanding of the causal factors effecting earnings of a unit/branch.

A Broking company at the operational level is exposed to credit risk owing to outdated credit rating model, business model and technical expertise.

The project has been undertaken to analyse causal factors which create bottlenecks in flow of information, thereby increasing time lag, risk and losses. Ex. Business model,response time, credit rating and accountability.

The report covers operational and market risk.While market risk measurement tools are applicable, Operational risk measurement tool provides the last mile coverage to credit risk in a Broking company.

Acknowledgement :-

I am grateful to Mr. Binodgopal Mukherjee, Zonal head (Religare Securities Ltd.) for providing the opportunity to work on this project.

References :-

Operational Risk – Measurement and modelling (Jack L King)

Measuring Market risk – (Kevin Dowd).



Contents…

Introducing Operational Risk Management.

Attribution of losses.

Measurement framework for OR

Implementation of the framework .

Process analysis .

Business model .

Key issues noted.

Technical risk factors w.r.t Dealing.

Client profiling and margin provisioning – Credit risk rating.

Credit rating model

MIS model implementation.

Margin system used by NSE,India.

Delta-EVT models for operational risk

Case-Genoa bank.

Summary.



Introducing Operational Risk management -

The project aims at analysing Risk Management at an operational level in a Broking company.

Operational risk is concerned with adverse deviation of a firm’s performance due to how the firm is operated as opposed to how a firm is financed. OR is defined as a measure of the link between a firm’s business activity and variation in business result. OR management aims to-

© Avoid unexpected losses and improve operational efficiency. © Efficient usage of capital. © Satisfy stakeholders. © Comply with regulation.

To begin, with Broking companies are exposed to credit risk. Risk management at an operational level in a Broking company can be segregated into Operational and Market risk. Operational Risk management aims at –

§ Value unfolding by reducing operational risk associated with performance. § OR is inherent to the way a firm conducts business and is closely linked to

performance. § Providing a relevant and objective OR measure. § Classifies performance that can be generally be categorised as frequent, low

level fluctuations or large performance differential. § Proposed OR measurement model – Delta-EVT combination.

Causality is the key to identifying and measuring controlled and uncontrolled events. While operational risk minimisation includes functional restructuring and measurement models, market risk minimisation benchmarks are as followed by the National Stock Exchange, India.

The report observes -

Operational risk.[ Client and company interface ] – Assignable/Controllable risk. § Functional -Management, services, sales. § Technical – systems.

Market risk measurement tools (as followed by the NSE and BSE ). [Company and the Exchange/Custodian interface] – Un-assignable/uncontrollable risk.

§ VaR § Excess Loss theory § Mark to Market theory



Attribution of losses. - Key in OR management is to identify and measure causal factors and corresponding risk. Losses are categorised as :

ð Numerate - accounting: ð Behaviour – human factors: ð Analytical – value – based:

Accounting categorisation of loss –

ð Valuation risk (wrong amount ) ð Reconciliation risk (wrong account ) ð Compliance risk ( wrong procedure ) ð Timeliness risk ( wrong time )

Human factors loss categorization –

ð Management oversight error ð Management fraud ð Employee activity error ð Employee fraud.

Value based loss categorization –

Value based control hierarchy for loss categorisation



Measurement framework for OR -

§ Identify important risks to the firm, § Classify risk as controllable and uncontrollable, § Identify causes for controllable risk, § Assign controllable risks to mitigation categories ( through assigned KRAs), § Provide measured feedback on changes in risks and relate to management actions.

The proposal aims at identifying risks at an early level and efficient FoI (Flow of information) along with increased accountability. Assumptions –

§ Financial system is safe and less prone to severe disruptions. (Regulators, institutions, brokers, DP)

§ To measure the OR, systems are needed that causally links operations of firm to earnings volatility.

§ An OR measure should reflect the variability of earnings as a result of losses due to errors , omissions and control breakdown or rare events, reflecting the two categories of high frequency, low impact events that are expected and cause operating losses , low frequency high impact events that occur unexpectedly and cause extraordinary losses.

§ The amount of control in a firm is reflected in the combination of controllable loss resulting from errors and omissions and uncontrollable loss resulting from exceptions , breakdowns, and rare events.

§ Operating losses are result of causal factors in activities of value adding process and is measured using a technique incorporating various factors in the model.

§ Excess losses result from rare events or control breakdowns and are not related to causal factors for the activities of value adding processes. They are analysed using an approach that combines actual internal events, external events and near misses into plausible scenarios of extreme events.



Implementation of the framework –

§ Establish the business model with value adding processes and activities, and any available large losses.

§ Determine risk factors for major activities in value added processes and their relation to earnings.

§ Estimate operational losses using uncertainty of risk factors propagated to the risk in earnings.(Delta method.)

§ Set the threshold of operating losses from the processes using the risk factor uncertainties and operating losses from the Delta method, and filter the large losses using the threshold.

§ Create a set of excess losses greater than the threshold using plausible scenarios based on actual historical losses, external events, and near misses and model them using extreme value theory (EVT).



Operational risk measurement framework consists of a business model and a measurement method.

Causal factors Business unit Earnings Business model Assignable losses Proxy for assignable losses measurement methodology unassignable loss



Front office Middle office

Centralised systems

Back office Accounting

Process diagram for operations in a Broking Co.

Process analysis –

Process engineering is applicable when re-engineering a process or re-visiting controls. It provides an overview and design for distinguishing the associated procedures and is a detailed description of the processes.

Process analysis relies on subjective evaluations. It can identify, classify and determine cause of risk associated with the processes.



Proposed Dealing room model for a broking house at an operational level.

KRA

KRA

KRA



Business model –

The business models are the basic unit of analysis for operational risk.It contains value added processes within each business unit in a firm, and the activities and factors within these processes that combine to form the hierarchy for the firm. Business models are generally firm specific. An efficient model assigns responsibilities and authority at each level defining parameters and de-bottlenecking management information flow, thereby leading to measurable accountability and higher efficiency. Business model refers to the structure of operations ( FoI ) with an aim to improve efficiency and effective strategy implementation.

Proposed functional restructuring

§ Dealing room defined with KRA at each level. § The suggested Dealing room model aims at de-bottlenecking flow of

information and owning responsibilities. § The model targets a streamline flow of information leading to higher

efficiency. § Information flow and hierarchy is useful for efficient strategy implementation. § Client profiling would decide regarding margin allotment and categorisation of

clients into particular style of investment, risk appetite and value added product. Profiling provides relevant background and trading history of the client, making maintenance easier.

Assumptions -

§ On implementation, a defined KRA to staff is priority. § Dealer-client relationship is to be limited to professional. § Systems and infrastructure should be in place. § Over leveraged and over trading in accounts are monitored. § Basic application MIS systems for position measurement are in place. § Dealers undergo client profiling and interface training along with market

fundamentals.

Key issues noted –

§ Undefined Dealer – KRA and accountability leading to chaos structure. § Delineation of Dealing and Sales functions. § Revision of Incentive and Brokerage charge structure. § Credit risk (margin) provision [margin calculator]. § Professional relationship between Client and Dealer.



The model suggests the Dealing room hierarchy aiming to minimise functional risk at an operational level. The flow chart defines the hierarchy and accountability for flow of information (FoI) with respect to KRA at each level.

ð Functional risk factors – § Dealer training & experience. § Client-dealer relationship beyond professional.

(leads to margin collection problems and over leveraging in an account). § Bottle necks in flow of information. § (Leads to time lag , bad service and management chaos.) § Chaos structure owing to unclear KRA. § Systems and Infrastructure.

ð Technical risk factors w.r.t Dealing includes - § Trading strategy § Credit risk § Measurement models

Proposed Technical suggestions -

§ Single screen interface models integrated with central MIS Risk Management catering to the Dealers back office support system(BOSS).

§ The MIS models aim at eliminating time lag in documentation and response. Ex. :

v ~1 Hour should be sufficient to check through 75 client position/ledger, compared to time consumed on gathering the decision making data at each level.

v Central RM can monitor the margin/VaR ratio of a clients, branches. This

would result in accountability converging to efficient risk management and measurement.



Post establishment of a business model, risk is segregated into certain and uncertain/controllable and uncontrollable.

Earnings Function Risk factors Uncertainty Sensitivity

Operation loss Distribution

Excess loss Distribution

Investment



Client profiling and margin provisioning – Credit risk rating.

At an operational level, a Broking company faces credit risk arising from margin provision for trading. The company risks the loss of money lent to traders as a margin facility.

The margin provision to a client is on the basis of soft judgement, specifically client rating. The stock exchanges provide risk management upto the brokers end of the chain, while the Broking company is allowed to practice indigenous Risk Management techniques for operations from and upto the client’s end.

Margin = fn(client rating,competition,market,regulations).

Client rating = fn(income,debt,experience,organisation,risk/return,style of investment, relationship with BFSI, margin requirement,etc.)

As a part of value added process, a 15 parameter profiling model has been structured to measure a client profile as well as calculate and upgrade a client rating. The client rating is the mean of values assigned to each parameter from a scale of 1-10.The mean or the client rating divisible determines the margin available to the client on dividing the required margin or gross exposure by the rating divisible.

The model on integration with central risk management systems would automatically be reflecting the margin and rating differential, thereby removing intermediaries in FoI to the RM, increasing Dealer accountability and eliminating margins of error. The model would be further used for trading history pattern with the company, influencing the rating divisible.

The model can be upgraded by central RM, relationship managers or the Dealer.

Ex-

An Infosys employee with a corpus of Rs. 150000 and 5 time margin (X) or 20% requirement has the following profiling –

The client has been allotted 25% margin on the basis of Credit rating. The mean derived from the rating data is applied as a divisible to the required client margin.

Credit available = Gross exposure or margin required/Credit rating divisible (CRD)

Note – The exhibit is a suggestive model and requires to be standardised.



Client profile model and margin calculator -

Infer CRD

1 Income ( pa) 250000 organisation Infosys Tech Experience 2 yrs Fair

2 Market experience 1yr yes 5yr 5yrs<x Nill

3 Exposure to market x >100000 1lac<x>5 lac yes 500000 < x Fair

4 Style Investment trading mix yes Fair

Style seggregation -

5 Investments - % Equity 50 % F&O 25 % MF 15 % IPO 10 Fair

6 Time period 3 mnths 25% 6 mnths 25% 12 mnths 25% 18 mnths 25% Balanced Exposure seggregation w.r.t time %

7 Expected RoI ( pa ) X>=25% 25% > X yes 40%<X Fair

Risk awareness I understand risk in market and my investments.

8 Risk apetite 10 % downside Low RA

9 Stock prefference NIFTY Mid CAP Small CAP range yes range

10 Service requirements - Regular updates yes Fair

Online services

Research

CRD – Credit Rating Divisible (range : 1-10)



11 Stocks with Religare Sec

Net Value

x > 50000

50000>x<100000 yes

x>2.5 lacs

2.5 lacs >x< 5 lacs

Net Value of stock

100000 Fair 5

12 Margin required - yes yes

(X) margin = 5

NV ( cash+sto

ck) 150000

Value gross Exp

750000 high 4

no

(%) margin = 20

13 Margin deposit provided by client 50000 yes

Margin provide

d 0.25207 low 4

by the Co.

Required client margin/ Credit divisible=Available margin

14 Operational loans yes Amount

250000

high leverag

e 2

15 Relationship with BFSI

ICICI Bank

Kotak

India Bulls Fin. risk

2.33

rating 3 3 1

relationship rating 2.33

Client Rating (divisible) 3.99

Credit rating and margin provided are inversely related.

Margin required by

Religare Sec in Rs.

188022

Margin provided for Rs.750000 exposure is Rs.150000. As per the margin calculator, the client requires to provide Rs.188022 as the margin money or Religare can provide a 25% margin.

Margin available to client = 25%.Margin required =20%.



Ex- rating factors and measurement

Income , experience & Organisation Style

Relationship with BFSI

icici bank

market penetration/network/sales 7 strategy/Dealing 2.5

Company grade 6

Forecasted relationship/sales 6 credit risk/ risk management 2.5 company business 2

Investment corpus 5 sales 7 relationship 1

credit worthiness 3 liquidity/Dealing 7 competetive interest 1

Revenue 5 Revenue 5 experience 4

Rated 5.2 4.8 2.8

Operational loan Margin requirement

Debt/earnings 1 Multiple 4 Approx . Payout/income per month 4 stocks 5 Approx. savings/income per month 1

risk apetite 2

Experience 1 return 5

Margin requirement 4 credit worthiness 3.75

Rated 2.2 3.95

The client is rated from 1-10 on the basis of subjective value assignment.

Ex.

Infosys employee is a sales target and rated as a good client, besides providing an entry into corporate specific sales. –

Therefore, on basis of market penetration/network/sales – CRD =7/10 . The mean derived from factor rating sum is assigned as the parameter rating.



Proposed Technical suggestions -

§ Single screen interface models integrated with central MIS Risk Management catering to the Dealers back office support system(BOSS).

Dealer - MIS

client stock stock (AHC)

available balance VaR margin(X) Margin/VaR Order

% var DoD

hs118 240000 180000 34000 14.7 25 1.700680272 CLEAR

pr116 177000 152000 13000 7.5 25 3.333333333 HOLD

b4343 57000 31290 7000 17 19 1.117647059 CLEAR

sn220 320000 276000 10000 10 21.75 2.175 CLEAR

Threshold 10 25 2.5 HOLD

No. of clients AuM AuM AHC Cash Var Avg. (X)

4 794000 639290 64000 12.3 22.6875 1.844512195

Client - MIS

HS118

Stocks Sector cp/unit Units Buy amt. CMP CM value %exposure P/L

P/L% var DoD

hind lever FMCG 199 500 99500 220 110000 43.279687 10500 10.55276382

hmt DIVERSE 56 1000 56000 65 65000 24.358417 9000 16.07142857

ITC DIVERSE 248 300 74400 207 62100 32.361896 -

12300 -16.53225806

Net position 229900 237100 100 7200 3.131796433

Stocks Instrument cp/ unit Unit

Buy amt. CMP CM value

% exp P/L

% var DoD VaR

Margin/VaR

NIFTY FUTURES 5255 50 262750 5108 255400 100 -7350 -2.79734

Net position 262750 255400 100 -7350 -2.79734



Client Financials -

Stocks Stocks AHC F&O Position Margin Ledger balance Available balance Max. exposure VaR

Manager Dealing - MIS

client stock stock (AHC) available balance VaR margin(X) Margin/VaR Order

hs118 240000 180000 34000 14.7 25 1.700680272 CLEAR

pr116 177000 152000 13000 7.5 25 3.333333333 HOLD

b4343 57000 31290 7000 17 19 1.117647059 CLEAR

sn220 320000 276000 10000 10 21.75 2.175 CLEAR

Threshold 10 25 2.5 HOLD No. of clients AuM AuM AHC Cash Var Avg. (X)

4 794000 639290 64000 12.3 22.6875 1.844512195

Suggested MIS models. Note – The models do not include Beta factoring.In real time Beta factoring is the basis for hedging and derivative positions alongwith VaR.



Margin system used by NSE,India. (source – Understanding margins , Risk Management [ The NSE, India]. Categorisation of stocks for imposition of margins The Stocks which have traded atleast 80% of the days for the previous six months shall constitute the Group I and Group II.

Out of the scrips identified above, the scrips having mean impact cost of less than or equal to 1% shall be categorized under Group I and the scrips where the impact cost is more than 1, shall be categorized under Group II.

The remaining stocks shall be classified into Group III.

The impact cost shall be calculated on the 15th of each month on a rolling basis considering the order book snapshots of the previous six months. On the basis of the impact cost so calculated, the scrips shall move from one group to another group from the 1st of the next month.

For securities that have been listed for less than six months, the trading frequency and the impact cost shall be computed using the entire trading history of the security.

Categorisation of newly listed securities

For the first month and till the time of monthly review a newly listed security shall be categorised in that Group where the market capitalization of the newly listed security exceeds or equals the market capitalization of 80% of the securities in that particular group. Subsequently, after one month, whenever the next monthly review is carried out, the actual trading frequency and impact cost of the security shall be computed, to determine the liquidity categorization of the security. In case any corporate action results in a change in ISIN, then the securities bearing the new ISIN shall be treated as newly listed security for group categorization.

Daily margins payable by members consists of the following : Value at Risk Margin Extreme Loss Margin Mark to Market Margin Daily margin, comprising of the sum of VaR margin, Extreme Loss Margin and mark to market margin is payable.

http://www.nseindia.com/content/nsccl/nsccl_eqmargins.htm#var

http://www.nseindia.com/content/nsccl/nsccl_eqmargins.htm#elm

http://www.nseindia.com/content/nsccl/nsccl_eqmargins.htm#mtm



Value at Risk Margin All securities are classified into three groups for the purpose of VaR margin For the securities listed in Group I, scrip wise daily volatility calculated using the exponentially weighted moving average methodology shall be applied to daily returns in the same manner as in the derivatives market. The scrip wise daily VaR would be 3.5 times the volatility so calculated subject to a minimum of 7.5%. For the securities listed in Group II, the VaR margin shall be higher of scrip VaR (3.5 sigma) or three times the index VaR, and it shall be scaled up by root 3. For the securities listed in Group III, the VaR margin would be equal to five times the index VaR and scaled up by root 3. In case of securities in Trade for Trade segment (TFT segment) VaR as applicable to Group 3 (illiquid securities) shall be applicable VaR margin rate for a security constitutes the following:

Value at Risk (VaR) based margin, which is arrived at, based on the methods stated above. The index VaR, for the purpose, would be the higher of the daily Index VaR based on S&P CNX NIFTY or BSE SENSEX. The index VaR would be subject to a minimum of 5%.

Security specific Margin: NSCCL may stipulate security specific margins for the securities from time to time.

The VaR margin rate computed as mentioned above will be charged on the net outstanding position (buy value-sell value) of the respective clients on the respective securities across all open settlements. There would be no netting off of positions across different settlements. The net position at a client level for a member are arrived at and thereafter, it is grossed across all the clients including proprietary position to arrive at the gross open position. For example, in case of a member, if client A has a buy position of 1000 in a security and client B has a sell position of 1000 in the same security, the net position of the member in the security would be taken as 2000. The buy position of client A and sell position of client B in the same security would not be netted. It would be summed up to arrive at the member’s open position for the purpose of margin calculation. The VaR margin shall be collected on an upfront basis by adjusting against the total liquid assets of the member at the time of trade.

The VaR margin so collected shall be released on completion of pay-in of the settlement. The details of all margins (VAR, extreme loss margin and mark to market) as at end of each day will be downloaded to members in their respective Extranet directory.



Extreme Loss Margin The Extreme Loss Margin for any security shall be higher of: 5% or 1.5 times the standard deviation of daily logarithmic returns of the security price in the last six months. This computation shall be done at the end of each month by taking the price data on a rolling basis for the past six months and the resulting value shall be applicable for the next month. The Extreme Loss Margin shall be collected/ adjusted against the total liquid assets of the member on a real time basis. The Extreme Loss Margin shall be collected on the gross open position of the member. The gross open position for this purpose would mean the gross of all net positions across all the clients of a member including its proprietary position. There would be no netting off of positions across different settlements. The Extreme Loss Margin collected shall be released on completion of pay-in of the settlement. The details of all margins (VAR, extreme loss margin and mark to market) as at end of each day will be downloaded to members in their respective Extranet directory. Mark-to-Market Margin Mark to market loss shall be calculated by marking each transaction in security to the closing price of the security at the end of trading. In case the security has not been traded on a particular day, the latest available closing price at the NSE shall be considered as the closing price. In case the net outstanding position in any security is nil, the difference between the buy and sell values shall be considered as notional loss for the purpose of calculating the mark to market margin payable. The mark to market margin (MTM) shall be collected from the member before the start of the trading of the next day. The MTM margin shall also be collected/adjusted from/against the cash/cash equivalent component of the liquid net worth deposited with the Exchange. The MTM margin shall be collected on the gross open position of the member. The gross open position for this purpose would mean the gross of all net positions across all the clients of a member including its proprietary position. For this purpose, the position of a client would be netted across its various securities and the positions of all the clients of a broker would be grossed. There would be no netting off of the positions and setoff against MTM profits across two rolling settlements i.e. T day and T-1 day. However, for computation of MTM profits/losses for the day, netting or setoff against MTM profits would be permitted. In case of Trade for Trade Segment (TFT segment) each trade shall be marked to market based on the closing price of that security. The MTM margin so collected shall be released on completion of pay-in of the settlement.



Summary -

The project covers Operational and market risk.

Post-analysis of the business model, the credit risk model and the market risk models, inference points at requirement for infrastructure upgradation, technical expertise and a implementable business model.At the Operational Level Technical expertise is the major factor.

Infrastructure upgradation means data storage capability, communication and systems. The most relevant outcome is applicable to the project itself. Without data storage capacity, maintainance of MIS records and earnings causal factor data is not feasible. Until historic causal factor data is available for a period of 3-5 years, EVT or Delta models cannot be implemented as no formulations can be applied.

The preferred approach adopted is top –bottom. That implies, beginning with the business model and moving down to credit risk models and culminating at integration of information management systems (MIS models, Risk management and services).

Causal factors affecting the risk at operational level and cardinal to business operations are technical expertise and conflict of interest w.r.t incentive system. The

Market risk tools including VaR and EVT are implementable but cover the risk exposure of custodians and leaving the brokers and clients exposed to discretionary risks. The report aims at analysing and developing risk management tools at the Operational level and integration of the central risk management systems with branch RMC so as to monitor, rate and value risk at all levels.

Operational Risk –Measurement and Modelling (Jack L King ) provides us with a very detailed methodology to manage Operational risk. The book adopts the same top-bottom approach as has been followed through out the report. The methodology aims at minimizing risk at every level of operation, segregating risk into assignable and unassignable and finally measured applying Delta-EVT method.

The cost involved for system upgradation to back sophisticated and timely execution and implementation of strategy is a concern but cannot be escaped by a competitive player in the industry.

Observing the Indian stock broking industry, the cost incurred for systems and expertise is justified by opportunity cost theory. The economy has just started rolling. Indian players are not comparable with global standards by any yardstick of measurement and in the markets no one escapes risk.

To conclude,infrastructure, technical expertise and knowledge are the key factors for Capital Market businesses.



Saurav Mishra.

National Institute of Securities Market,SMP 2007-08.

ARMOL

Documents

Transcript of ARMOL