Analytics in Risk Management

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New York, September 2013 Simplicity is the Ultimate Sophistication » It is not hard to compose, but what is fabulously hard is to leave the superfluous notes under the table.« Johannes Brahms

description

This presentation covers the challenges of risk management, risk management strategy, consistent risk and P&L management, implementation, visual data discovery, and use case/benefits.

Transcript of Analytics in Risk Management

Page 1: Analytics in Risk Management

New York, September 2013

Simplicity is the Ultimate Sophistication

» It is not hard to compose, but what is fabulously hard is to leave the superfluous notes under the table.« Johannes Brahms

Page 2: Analytics in Risk Management

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Agenda

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The Challenges in Risk Management

Requirements / Basel Committee Principles

Enhance infrastructure for reporting key information

Particularly used by the board and senior management

To identify, monitor and manage risk in real time and on-demand

Improve decision-making throughout the bank

Enhance the management of information across legal entities

Facilitate assessment of risk exposure at the global consolidated level

Reduce the probability & severity of losses

Reduce the time required to access risk information

Improve the quality strategic planning

Regulatory Requirements

Basel Committee Principles

Capital Requirements

RWA

Shrinking margins

Cost Pressure

Strategic planning

Volumes

Key Challenges

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Drill Down

Real-time

Reporting/Analysis

On Demand

A well designed analytical dashboard provides users with a colour palette optimized for fast comprehension and filters to allow rapid isolation of potential problems and opportunities. It is the combination of a visual interface with an equally capable information architecture that allows traders and risk managers to understand precisely and instantly the drivers of risk and enables them to take immediate action on important finding.

Business Benefits

Significantly improved user experience

Allows user to focus on supervisory responsibility

(rather than report creation)

Data available on-line with drill down back to source

data

Availability of data quality information supports

communication with data owners and will eventually

result in improved quality

Objectives

Expand the user experience by leveraging new

technology, dashboard functionality and data

visualisation in order to create additional value

Provide a data presentation vehicle that allows users

to easily identify problem areas that require

attention

Provide a platform that supports drill down features

and on-line functionality

Risk Management - Strategy

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Consistent Risk and PnL Management / Control

PnL Attribution

Risk Based PnL

Validated PnL

Risk Sensitivities

VaR

Back Testing

Counterparty Risk Profiles

RWA Drill Down

Business Requirements

Analysis

Drill Down

Slice and Dice

Trend

Time Series

Monitoring

Real Time

Functionality / Features

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Implementation

Technology Challenge

It has proven difficult to build on demand risk systems using conventional risk technology; emerging technologies are now becoming sufficiently robust that they can be used as a basis for building enterprise risk systems that can monitor risk in real-time, on demand and on a historical basis

Conventional risk management technology platforms are based on established business information architectures:

Based on a sequential flow of data: extract, transform, load, enrich calculate and report

On demand, near-real time processing is implemented like ‘mini’ batch of the sequential processing

Performance constrained by the underlying data and processing architecture

Emerging technologies such as Complex Event Processing, in-memory processing and data visualisation tools enable a different architecture where trade and market events can be processed as they arrive:

These technologies are deployed as components that can be combined to provide tailored solutions

The same components can be used in different configurations for different applications

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Pre Attentive Processing

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How many 3’s?

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Visual Data Discovery

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Iterative Implementation Approach

Evolution Step 1 Existing Spreadsheet

Evolution Step 2

Evolution Step 3

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Iterative Implementation Approach – Swaption Dashboard

Step 1 Scenarios / Analysis Existing Spreadsheet

Step 2 Hierarchies

Step 3 Drill Down

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Use Case / Benefits

Focus

Front Office

Middle Office

Back Office

Wealth / Asset Management

Group Wide

Immediate Identification Risks/Opportuniti

es

Benefits

Efficient Processes, Consistent Use F2B Efficiency/Consistency

Less Reporting, No Spreadsheet Processes Workarounds

Quick Implementation, Opportunity Cost Time to Market

Less Proprietary development, Decommissioning of parallel Technology Cost Avoidance