Risk Management Information System

Risk Management Information System Risk Management Information System

Nurhastuty K. Wardhani &

Shaista Arshad

Prof. Dato’ Dr. Kamaruddin Sharif

Computerized systems that assist in consolidating information and provide reporting capabilities to enable you to monitor and control your overall cost of risk.

ISO 31000 – The effect of uncertain objectives, whether positive or negative.

Risk Management Information System

Risk Management

INTRODUCTIONINTRODUCTION

• Management of risk data and information vital to success of RM department.

• RMIS is used to support expert advice and cost-effective information management solutions.

• Involves key processes such as:• Risk identification and assessment• Risk control• Risk financing

INTRODUCTIONINTRODUCTION

Index of Leading RMIS Companies

• American Technical Services• Aon eSolutions• Certificate Management Solutions• Envision Technology Solutions LLC• Mountain View Software Corp.• Origami Risk • Riskonnect

FUNCTIONS OF RMISFUNCTIONS OF RMIS

• The business need that drive financial firms to implement risk management functions are:

ROLE OF RMISROLE OF RMIS

• The RMIS should provide managers with the data needed to meet the business need.

• Managers require four things from their RMIS:

ROLE OF RMISROLE OF RMIS

• Problem of designing RMIS : Problem of Aggregation

Data from each of a firm’s trading locations worldwide must be aggregated to calculate Value at Risk or to perform a scenario analysis on the firm’s worldwide

portfolio.

• Different methodologies require different information, thus imposing different requirements on the RMIS.

INFORMATION SYSTEMS REQUIREMENT

RISK MANAGEMENT METHODOLOGIES

• Value at Risk : Delta Normal and full revaluation Monte Carlo. Centralized vs. Decentralized Methodology

• When selecting a methodology some problems a firm setting a RMIS may face are :

• VaR: Widely used risk measure of the risk of loss on a specific portfolio of financial assets.

• It measures risk as mark-to-market loss on a fixed portfolio over a fixed time horizon.

• Each methodology combines an assumption on the future distribution of market risk factors and current data on portfolio positions.

• There is often a trade off between accuracy and computational demands when calculating VaR.

• Two VaR methodologies: Delta-Normal and Full Revaluation Monte Carlo.

VALUE AT RISKVALUE AT RISK

• Delta-Normal methodology stipulates that:

• Future Distribution of changes in market is assumed to be multivariate normal

• Delta is the change in the position’s for one-unit change in market risk factor

• Distribution of change in portfolio value is linear

• The delta-normal method requires the RMIS to know the deltas of each trading unit’s portfolio

• This requires access to a large amount of data ( CF of each instrument in the portfolio)

DELTA-NORMALDELTA-NORMAL

FULL REVALUATION MONTE CARLOFULL REVALUATION MONTE CARLO

• When choosing between the two, the firm will trade off the accuracy of its VaR estimates with the computational burden required to compute its estimates.

SELECTIONSELECTION

• Cannot predict where an firm will choose to be on the trade off curve. • Technical progress will cause the curve to shift out making the

tradeoff more favorable.

• RMIS is more important in Islamic banks as the impact of PLS methods on depositors and the need for such investment is at the core of IB.

• An information system will help in reducing the possibility of asymmetric information, adverse selection and moral hazard.

• Advantage of such a system:• Help depositors with diversification and fund allocation questions

• Disclosure provides information on the main risk factors

• Good governance and internal control : reduce mismanagement

RMIS & ISLAMIC BANKSRMIS & ISLAMIC BANKS

• Verasis represents a new generation of software systems and was developed by Veratec Limited, a software company operating exclusively in the banking and finance sector.

• Veratec recognized that the proactive measurement and management of multiple risk and regulatory disciplines did not necessitate the implementation of multiple risk and regulatory requirements; but to consolidate these requirements into a single integrated application.

CASE STUDY - VERASISCASE STUDY - VERASIS

The Challenge

• Changing Markets and Trading Systems• Regulatory Environment• Risk Methodology• Old Technology

The Solutions

• Leverage modern technology to provide clients with the ability to collect, collate, calculate and distribute the information from multiple trade sources across a range of Risk disciplines including:

– Historical Simulation Value at Risk– Market data risk (Interest rate, FX Rates, Volatility, Price)– Credit Risk– Liquidity Risk– Counterparty Risk– Asset & Liability management– Hedge effectiveness

• Consolidate multiple Risk, Regulatory and Management disciplines into a single integrated application and consequently deliver:

- Cost effectiveness by reducing head count and system requirements (single valuation methodology, single data warehouse, single application environment, single set of interfaces)

- Consistency by ensuring that the same market data, methodologies and math libraries are used for valuation and processing within all functional business components

• Clarity by combining a configurable multi-format reporting engine with standard multi-level drill down architecture, allowing users to isolate and communicate results and issues quickly and effectively. Verasis Risk delivers reporting that is flexible, functional, and integrated

Verasis Risk A Risk and Regulatory Management System for Treasury

Anglo Irish Bank

• Anglo Irish Banking Corporation (AIBC) is based in Dublin and has offices in Austria, Ireland, the Isle of Man, Switzerland, the UK, and the USA.

• AIBC has enjoyed a sustained market-leading performance, which has resulted in Total Assets surging from €15.8 billion (30 Sep 2001) to €73.3 billion (30 Sep 2006).

Verasis Risk at AIBCValue at Risk Hedge effectiveness (IAS39) compliance Interest rate riskAsset and Liability management Mark to Market

• This provides a fast and flexible Historical Simulation/ Monte Carlo-based VaR solution.

• Combine retail/corporate assets and liabilities with the financial instruments that fund and hedge them

• Analyze the Market Valuations and Interest Rate Risk in the Banking Book (IRRBB) using standard and non-standard yield curve rate shocks

• RMIS are designed to overcome the problem of aggregating data

across diverse trading units.

• The design of an information system depends on the risk

measurement methodology that a firm chooses.

• Tradeoff between the accuracy of the resulting measures of risk

and the burden of computing them.

CONCLUSIONCONCLUSION