A blog which that talks what matters now and what will happen in the future. Markets are changing. The need to do more with less has never been greater. More transparent decision making, timely actions and continuous learning are vital to ongoing improvement and value creation.
I will focus my discussion on
Predictive Analytics / Statistical Model Building
MDM and Data Services
Business Intelligence, Analytics & Reporting
Big Data – Hadoop/Hive
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.
spending most of their time reconciling
data since underlying data originate from disparate systems.
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
organizations are struggling to measure ROI on risk management and
its process ,values and effectiveness to key stakeholders.
organization struggles to access enterprise wide risk exposure
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.
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
Retrieval of large to massive datasets (Big Data) focused on aggregation queries.
For more on rise of Column Oriented Database check out the presentation....
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
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
To find out more how it was done click the link below...............................
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
üSwap creation data (such as the primary economic terms of the swap and confirmation data.
üSwap continuation data (such as event data, valuation information and term changes.
·Swap execution facilities (“SEFs”)
·Designated contract markets (“DCMs”)
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)
ØThe 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.
ØThe 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.
ØThe 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:
·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.
üSwap Dealers (SD) and Major Swap Participants (MSP)
ØReport 1 - Executed on a platform and cleared
ØReport 2 - Executed on a platform and not cleared
ØReport 3 - Not executed on a platform and cleared
ØReport 4 - Not executed on a platform and not cleared
ØReport 5 - Credit and Equity Asset Classes – Cleared
ØReport 6 - Credit and Equity Asset Classes –Not Cleared
ØReport 7 - Interest Rate, Currency, and Other Commodity Asset Classes – Cleared
ØReport 8 - Interest Rate, Currency, and Other Commodity Asset Classes – Not Cleared