L’approche Big Data en finance de marché 1/2

14
Quartet FS Powering Operational Decision Making in the Big Data Era www.quartetfs.com

description

L'outil ActivePivot de Quartet FS dans l'approche Big Data en finance de marché

Transcript of L’approche Big Data en finance de marché 1/2

Page 1: L’approche Big Data en finance de marché 1/2

Quartet FS

Powering Operational Decision Making in the Big Data Era

w w w . q u a r t e t f s . c o m

Page 2: L’approche Big Data en finance de marché 1/2

Solving the operational decision-making needs of business users working in time-sensitive and data-intensive environments

About Quartet FS

Established in 2005

5 offices New-York

London

Paris

Singapore

Hong Kong

70+ employees

50+ implementations

30 client organisations

6 ISV & SaaS partners

Page 3: L’approche Big Data en finance de marché 1/2

Gartner Cool Vendor, In-Memory Computing 2013

Gartner Hype Cycles “Sample vendor”, especially:

- Supply Chain Management 2012

- Business Activity Monitoring 2012

- Big Data 2012

- In-memory computing technologies and Analytical In-Memory database systems

“Quartet FS…….the surprise package of our study in that the

company is already in a position to boast of a number of top-

tier financial institutions using its ActivePivot in-memory

analytics product”.

ActivePivot™: Market recognition

Page 4: L’approche Big Data en finance de marché 1/2

Big Data

TIME-

SENSITIVE

Intraday,

real-time

DATA-

INTENSIVE

Exponential

volumes

COMPUTING-

INTENSIVE

New metrics &

calculations

Page 5: L’approche Big Data en finance de marché 1/2

CVA : Compute-intensive calculations

20 Billion simulations

= (8-20 TeraBytes of data)

1 trade = 1,000 simulations

200 time points = 200,000 simulations

100,000 trades = 20,000,000,000 simulations

Page 6: L’approche Big Data en finance de marché 1/2

Multidimensional analytics

In-Memory Computing

Mixed Workload

DBMS ActivePivot

Real-time data aggregation and calculations

Using ActivePivot, our clients are able to embed high performance analytics into their organizational processes so that action can be taken at the right time.

Enabling Data-and Event Driven Decision Making

Page 7: L’approche Big Data en finance de marché 1/2

Meaningful KPIs

Freedom of analysis Speed

The Essence of Multidimensional Analytics

Page 8: L’approche Big Data en finance de marché 1/2

Meaningful KPIs

Freedom of analysis

Speed

Meaningful KPIs

Freedom of analysis

Speed

Meaningful KPIs

Freedom of analysis

Speed

or or

Legacy OLAP Visualisation software In-Memory SQL Database

What Are the Alternatives Today?

Page 9: L’approche Big Data en finance de marché 1/2

ActivePivot in the Analytical Landscape

Meaningful KPIs

Freedom of analysis

Speed

ActivePivot

Page 10: L’approche Big Data en finance de marché 1/2

Real-time, cross-asset VaR,

Credit risk (PFE, CVA)

P&L explain

Liquidity

IM/VM

Collateral optimisation

Some Use Cases in Financial Services

Position keeping, sensitivities

Real-time desk trading

Limit monitoring

FX book management

Real-time P&L

Continuous hedging

Enterprise Risk Management

Front-office Risk

Technology Enablers

Aggregation of non linear data from multiple sources

Calculation capacity to run on large data sets

Predictive Analytics and “What-if” simulations

Instant response times for dynamic analysis

Data analysis across many dimensions

Consolidation data across heterogeneous data silos

Page 11: L’approche Big Data en finance de marché 1/2

PRE-PROCESSING

Data enrichment

Pre-calculations

Custom rules

AGGREGATION

Incremental updates

On the fly aggregation

POST-PROCESSING

Computes complex measures

Reacts to real-time streaming

Includes user specific behaviour

HETEROGENEOUS

DATA SOURCES

ActivePivot Aggregates data incrementally and in real-time Executes complex computations based on your business logic Supports on-demand “what-if” analysis on real-time data

USER INTERFACE

An Open Aggregation and Calculation Framework

What-if analysis

Intuitive exploration

Alerts

Page 12: L’approche Big Data en finance de marché 1/2

Multiple systems consolidation

Object oriented (vectors, matrices, …), intuitive data representation

Non-linear aggregations

Very fast multi-threaded loading and aggregation (64B Java 1.6)

Open choice of user interfaces (MDX)

In-Memory, Object-Based Database

Real-time (incremental) Transactional Engine

Multiple object input flow: Trade flow, Market data flow, etc.

Push & Pull technology

Alerts (continuous queries)

Distributed Deployment

Horizontal Distribution

Polymorphic Scalability

ActivePivot Key Features

Page 13: L’approche Big Data en finance de marché 1/2

ActivePivot Sentinel Builds On and Extends ActivePivot

Streaming and

Processing

Complex

business rules

SEAMLESS INTEGRATION

Input stream

ActivePivot Sentinel

Email

Application

AP Live

RECORDED DATA

REAL-TIME ALERT

+

Page 14: L’approche Big Data en finance de marché 1/2

Thanks !

Armen TCHILIAN Head of Sales and Solutions, Paris

Mail : [email protected] Tel : +33 1 40 13 84 52

QUARTET FS (Paris, London, New York, Singapore) 2, rue Jean Lantier 75001 Paris, France

Tel : +33 1 40 13 91 00 Site internet : www.quartetfs.com