Monday, January 13, 2014

Data architecture around risk management

Data architecture around risk management

In today's competitive market, many organizations are unaware of the quantity of poor-quality data in their systems. Some organizations assume that their data is of adequate quality, although they have conducted no metrical or statistical analysis to support the assumption. Others know that their performance is hampered by poor-quality data, but they cannot measure the problem.
Enterprise are spending most of their time reconciling  and validating business data since underlying data originate from disparate systems.

Data quality is concerned not only with the structure of the dataset, but with the usefulness and value of the information it contains, record by record and field by field.

Most organizations are struggling to measure ROI on risk management and
communicate its process ,values and effectiveness to key stakeholders.

Most organization struggles to access enterprise wide risk exposure

Regulatory compliance posing greatest obstacles  against  developing enterprise risk management solutions

Top executive do not articulate risk appetite properly\

Lack of human resource and expertise

The greatest setback posed by various business units inside an organization is to unable to  make Risk based

Find out more on  "Rise of Data Governance"!

Saturday, May 4, 2013

Where does Hadoop fits in

In today's dynamic world ,a fresh approach to data management is required, and Hadoop helps fulfill this need.
Hadoop is not the hammer to make everything a nail. Queries are batch driven, not real time. It is not designed to be optimized for specific scenarios. There is no transactional model.

So let see where it fits in ...................

Rise of Column Oriented Database Technologies

Most database vendors like Oracle, Microsoft, Sybase, Informix,  base their technology on this ANSI standard.  Column-oriented databases are indeed what you might surmise; tables of data where columns of data values represent the structural storage.  

The real value in using column-oriented database is 
  1.  High performance
  2. Scalable storage 
  3. Retrieval of large to massive datasets (Big Data) focused on aggregation queries.
For more on rise of Column Oriented Database check out the presentation....

Will appreciate your Comments and Suggestions .....

Big Data Analytics in Politics

We live in a data-driven world. Increasingly, the efficient operation of organizations across sectors relies on the effective use of vast amounts of data. Making sense of big data is a combination of organizations having the tools, skills and more importantly, the mindset to see data as the new "oil" fueling a company. Unfortunately, the technology has evolved faster than the workforce skills to make sense of it and organizations across sectors must adapt to this new reality or perish."Andreas Weigend, Ph.D Stanford, Head of the Social Data Lab at Stanford, former Chief Scientist

The hottest job in today’s Presidential campaigns is the Data Mining Scientist -- whose job it is to sort through terabytes of data and billions of behaviors tracked in voter files, consumer databases, and site logs. They’ll use the numbers to uncover hidden patterns that predict how you’ll vote, if you’ll pony up with a donation, and if you’ll influence your friends to support a candidate.

To find out more how it was done click the link below...............................

Will appreciate your Comments and Suggestions .....

Friday, November 11, 2011

Reporting Requirements Swap Data Repository - DODD FRANK Regulation

BI Reporting Requirements for over-the-counter (OTC) 
by DODD-FRANK Regulators  - Part 1
Compiled by Suvradeep rudra

New reporting and record keeping rules generally distinguish between two categories of information
ü  Swap creation data (such as the primary economic terms of the swap and confirmation data.
ü  Swap continuation data (such as event data, valuation information and term changes.

·         Swap execution facilities (“SEFs”)
·         Designated contract markets (“DCMs”)

1.       TOP  SWAPS
a.       Top 10 record (Swaps ) in $ values  for the Day
b.      Top 10 record (Swaps ) in $ values  for the Month
c.       Top 10 record (Swaps ) in $ values  for the Qtr

Reports should include following columns           
                                                               i.       Unique Counterparty Identifier (UC )
                                                             ii.      Unique Swap Identifier (USI)
                                                            iii.      Unique Product Identifier (UPI)
                                                           iv.      Start Date
                                                             v.      Expiration date
                                                           vi.      $ amount

Ø  The UCI would identify the legal entity that is a counterparty to a swap.  Under the proposed rules, the Commission would require use of UCIs in all swap data reporting.
Ø  The Unique Swap Identifier (USI) called for by the proposed rules would be created and assigned to a swap at the time it is executed, and used to identify that particular swap transaction throughout its existence.
Ø  The Unique Product Identifier (UPI) called for by the proposed rules would categorize swaps according to the underlying  products referenced in them. While the UPI would be assigned to a particular level of the taxonomy of the asset class or sub asset class in question, its existence would enable the Commission and other regulators to aggregate transactions at various  taxonomy levels based on the type of product underlying the swap.

2.       Reporting of Swap Creation Data – Executed on a Platform

 The Dodd-Frank Act lays the foundation, defining a SEF to be "a facility, trading system or platform in which multiple participants have the ability to execute or trade swaps by accepting bids and offers made by other participants that are open to multiple participants in the facility or system, through any means of interstate commerce."

The expected role of a SEF is to provide pre- and post-trade transparency, encourage competitive execution for the entire institutional marketplace, and provide the tools required to ensure a complete record and audit trail of trades. There could be a significant shift in the way derivatives trading is ultimately executed, and Tradeweb has made great strides to be ahead of the curve for our clients.

Legislative bodies in the U.S. and Europe are moving to increase regulation of the over-the-counter (OTC) derivatives market. These global financial reform initiatives seek to achieve three key objectives for the OTC derivatives markets:
·         Increase transparency
·         Improve market efficiency
·         Prevent market abuse
How Derivatives are Currently Traded
Over-the-counter, or "privately negotiated", derivatives are currently traded on the telephone and increasingly on electronic markets, such as Tradeweb. There are two sectors of the market: institutional dealer-to-client (D2C) and inter-dealer (D2D). These markets are approximately the same size in terms of trading volumes, but there are many more participants in the D2C marketplace than D2D.

Reporting Counterparty
ü  Swap Dealers (SD) and Major Swap Participants (MSP)
ü  Non-SD/MSP Counterparties

Ø  Report  1 - Executed on a platform and cleared
Ø  Report  2 - Executed on a platform and not cleared
Ø  Report  3 -  Not executed on a platform and cleared
Ø  Report  4 - Not executed on a platform and not cleared
Ø  Report  5 - Credit and Equity Asset Classes – Cleared
Ø  Report  6 - Credit and Equity Asset Classes –Not  Cleared
Ø  Report  7 - Interest Rate, Currency, and Other Commodity Asset Classes – Cleared
Ø  Report  8 - Interest Rate, Currency, and Other Commodity Asset Classes – Not Cleared