John Randles CEO PolarLake said, “Partnering with OnixS is a natural extension for PolarLake giving our clients a single platform to cover the range of data feeds from Market Data to Reference Data. Also we will able to offer a great set of FIX engines and certified Direct Market Access solutions to the most popular exchanges.”

Wayne Meikle, Commercial Director of OnixS added “We’re pleased to be working with PolarLake to expand the Direct Market Access services available to PolarLake customers. Our focus on market data and trading venue solutions and PolarLake's focus on data management and distribution create a compelling overall solution offering.”

About PolarLake

PolarLake works with Global Financial Institutions and Asset Managers to implement Pricing and Reference Data Distribution and Integration solutions. We help our clients to control the collection, access and distribution of Pricing and Reference Data to internal consumers across their organizations. They work with us to:

• Control and ensure transparency on their end to end Data Supply Chain
• Achieve faster Time to Market than is possible with generic approaches
• Manage the Complexity of Pricing and Reference Data Distribution and Integration.

PolarLake has been recognized by Industry Analysts as a leader in the Reference Data Distribution and Integration space, named by Aite as the most packaged Reference Data Distribution solution and included in the Gartner visionaries’ quadrant.

PolarLake’s clients include 6 of the top 10 Investment Banks, 2 of the top 5 Prime Brokers and 2 of the top 10 Asset Managers in the world.

About OnixS www.onixs.biz:

OnixS is a specialist software business providing high performance multi-platform, multi-venue Direct Market Access solutions with a Pay As You Use (PAYU) subscription commercial model.

The OnixS products include the OnixS selfConnect range of FIX engine and FAST encoder/decoder components designed to be easily integrated within existing .NET, C++ and Java application frameworks.

The OnixS directConnect products are calibrated and certified DMA market data and trading handler solutions for a wide range of exchanges, ECNs, and brokers designed for rapid and efficient integration.

“PolarLake is delighted to be exhibiting at the SIFMA Financial Services Technology Expo. We see huge interest in the area of Reference Data Distribution and Integration as major firms have settled on internal systems or commercial products to provide data centralization. The game has now changed to getting real value, decreasing costs, meeting regulations and getting a better view on risk through these data stores. The main stumbling block on all these is typically down to having smarter integration for better Reference Data Management. SIFMA is a great event to engage in these conversations. ” says John Randles CEO PolarLake.

About PolarLake

PolarLake works with Global Financial Institutions and Asset Managers to implement Pricing and Reference Data Distribution and Integration solutions. We help our clients to control the collection, access and distribution of Pricing and Reference Data to internal consumers across their organizations. They work with us to:

• Control and ensure transparency on their end to end Data Supply Chain
• Achieve faster Time to Market than is possible with generic approaches
• Manage the Complexity of Pricing and Reference Data Distribution and Integration.

PolarLake has been recognized by Industry Analysts as a leader in the Reference Data Distribution and Integration space, named by Aite as the most packaged Reference Data Distribution solution and included in the Gartner visionaries’ quadrant.

PolarLake’s clients include 6 of the top 10 Investment Banks, 2 of the top 5 Prime Brokers and 2 of the top 10 Asset Managers in the world.

For information

Cliff Cunningham, Director Product Marketing, Financial Services

PolarLake

Cliff.Cunningham@polarlake.com

+353 1 449 1010

There are a number of reasons why this now matters a heck of a lot more today than it used to in the pre-crisis world. Firstly nobody wants to be the next firm where a rogue trader is exposed. Controlling the appropriateness of reference data access can play a part in controlling the activities of traders. Secondly there is the issue of cost. Making sure all data access is controlled is a simple and effective way of making sure that only the data that is required and is appropriate is purchased from third party data vendors. How many applications in large firms are still requesting data daily which is no longer relevant to their current portfolio? And thirdly the issue of compliance with data vendor license agreements can be an area of risk for a firm. Do you know where all the data you have purchased is getting distributed? Is it licensed for those end users or geographies? What is the financial and reputational risk if the firm is inadvertently breaching license terms? And can I provide an audit to the data supplier of data usage by type, volume, role and territory over a particular time period?

How can we tackle these concerns? Security in the enterprise is typically implemented based on user profiles in global directory services for email, operating system, and various applications that staff has access to. But when it comes to reference data is it a bit much to ask application administrators of trading, risk, accounting and portfolio systems to manage a new class of user authentication around data types and classifications as the data arrives into the system? This is something that has been centrally addressed for sensitive client data, but the range and diversity of reference data makes this a much more daunting task. And despite the aspirations of the centralized enterprise data management group, for many firms much data access takes place outside of their gaze.

From our experience in many data management projects the only manageable place to control this new type of access control is within the distribution mechanism. Some of our clients have gone from a position where equities systems were getting flooded with fixed income data at the peak of the crisis as prices were getting reset, to a situation where what they receive is controlled by a tight subscription of relevant, timely data, which is traceable and auditable back to all sources. Distribution systems are really the only mechanisms to provide this capability without upheaval and change in application administration. Doing reference data security at the distribution level is very different from locking down a single source of client data which has been centralised. Distribution touches all endpoints transparently and is by its nature non-invasive.

Reference data security is truly an enterprise issue where old tactics based on application security no longer cut it.  A light touch with potentially zero impact on the consumer is essential for success.

Talk to us to learn more of our thoughts on this fascinating emerging area. 

“PolarLake is delighted to be exhibiting at the North America Financial Information Summit. We see the Reference Data Management industry now focused on the end to end supply chain and integration of Pricing and Reference Data.  This is directly driven by the current focus on counterparty risk and regulatory compliance as risk managers and regulators want to see an end-to-end data process, not just islands of data. This event gives us a gives us a great opportunity to meet with people in real projects often struggling under the weight of integration complexity often driven by using generic ETL / EAI technology” says John Randles CEO PolarLake.
 

About PolarLake

PolarLake works with Global Financial Institutions and Asset Managers to implement Pricing and Reference Data Distribution and Integration solutions. We help our clients to control the collection, access and distribution of Pricing and Reference Data to internal consumers across their organizations. They work with us to:

Control and ensure transparency on their end to end Data Supply Chain
Achieve faster Time to Market than is possible with generic approaches
Manage the Complexity of Pricing and Reference Data Distribution and Integration.

PolarLake has been recognized by Industry Analysts as a leader in the Reference Data Distribution and Integration space, named by Aite as the most packaged Reference Data Distribution solution and included in the Gartner visionaries’ quadrant.

PolarLake’s clients include 6 of the top 10 Investment Banks, 2 of the top 5 Prime Brokers and 2 of the top 10 Asset Managers in the world.

For information contact
Cliff Cunningham, Director Product Marketing, Financial Services, PolarLake

Cliff.Cunningham@polarlake.com
+353 1 449 1010

This fact raises the bar and expectation of what is really meant by Enterprise Data Management (EDM). The ability of vendors and internal IT to build and run a centralized repository to collect and cleanse data is not in question. However what is in question is how much of the end to end “Supply Chain” of Reference Data Management is really going to be achieved by implementing EDM alone.

Our clients have been asking us how they can achieve end to end integration and management of supply and demand for Reference Data. They have recognized that it is needed to deliver on the promise of centralized Reference Data Management.

Today’s requirements coming from the business community when it comes to EDM systems are not as straightforward as they used to be. Some consumers want the raw vendor’s data, others want raw plus cleansed, others just cleansed, and others don’t want to deal with a central authority and go straight to the data vendor. This will vary according to asset classes and market sectors in the same firm typically. The trend of consumers getting closer to the data and wanting customized services means a new focus on data delivery SLAs, support for multiple formats and differing cardinalities, delivery status control, data access control mechanisms etc. These are the realities of Reference Data supply chain in 2010. More like a FedEx supply chain than a traditional view of Data Management.

This is where the golden copy approach, somewhat unfairly I believe, got a bad name. Clients are telling us that they now see golden copy system as a subset an end to end solution or Reference Data supply chain. What happens then when the business starts to focus of one data vendor for a particular type of data and where golden copy system now cleanses on a single source? In this case the process being automated is now primarily one of a data supply chain and validation not cleansing in the purest sense. And this is a trend that is gaining momentum, a move away from seeing EDM as broad cleansing alone (putting together a “golden” record with fields from multiple vendors) more to a flexible approach where I can decide I will trust a particular vendor’s data for a particular asset class (e.g. Reuters for US Equities Security Master) and handle exceptions in the quality of this feed alone. So in this situation distribution, access control and exception management to the data is as important as sophisticated cleansing heuristics and complex data model that builds a “golden” record. An extension may be trusting one vendor’s data for all data in one asset class except for pricing fields where they want to validate pricing against another vendor’s data with associated human workflow and automated business rules. This is especially true as firms are consolidating on the numbers of Reference Data vendors they are subscribing to. When the markets were booming the number of times a piece of data was sourced from multiple vendors was irrelevant. Not anymore. Efficiency in the supply chain now has to ensure there is no redundant vendor Reference Data being ordered or erroneously reordered.

According to the APICS dictionary (Association of Operations Management) it defines Supply Chain Management as the "design, planning, execution, control, and monitoring of supply chain activities with the objective of creating net value, building a competitive infrastructure, leveraging worldwide logistics, synchronizing supply with demand, and measuring performance globally."

This sounds like a more realistic description of what people are trying to achieve in Reference Data Management in 2010 than a the pure focus on collection and cleansing of Reference Data that EDM has long been known for.

The Financial Crisis has created a drive for improved operational efficiency, risk management and regulatory compliance. This has raised the bar dramatically on what is meant by Reference Data Management particularly the end to end delivery on that vision, not just cleansing alone.

EDM may in fact be about to turn into Reference Data Supply Chain Management.

• Data access control policies based on user and application profiles
• Routing policies and priorities, such as what the downstream update order is for new issues or issuers
• Data usage quotas to ensure appropriate and controlled use of data
• Expected delivery schedules and exception escalation paths
• Take-on of new data feeds via a soft model without the need to rebuild the system
• Ability to learn and adopt the model based on observing of change in data patterns over time
   

Commenting on the release, Warren Buckley CTO PolarLake says “Data Management has matured to the extent that firms are more interested in configuring their own business policies into a flexible platform rather than being constrained by traditional boundaries of data models and integration adaptors.  Semantics are a great way to express business policy and control which is fundamental to Data Management, Distribution and Integration. The application of these technologies to risk management, adopting for new regulations and distribution and integration of data is endless.”

Liam Ó Móráin of the Digital Enterprise Research Institute (DERI), a world leading research centre on semantics, commented “semantics will be the future way that information is described, shared and integrated. This approach and technology has huge potential to solve the complexity issue in Data Management in Financial Services. From our work in academia and interaction with leading users of this technology in industry we see PolarLake’s use of semantics as having the potential to be transformational in terms of how people think of, implement and manage Data Distribution and Integration in Financial Services.

About PolarLake

PolarLake works with Global Financial Institutions and Asset Managers to implement Pricing and Reference Data Distribution and Integration solutions. We help our clients to control the collection, access and distribution of Pricing and Reference Data to internal consumers across their organizations. They work with us to:

• Control and ensure transparency on their end to end Data Supply Chain
• Achieve faster Time to Market than is possible with generic approaches
• Manage the Complexity of Pricing and Reference Data Distribution and Integration.

PolarLake has been recognized by Industry Analysts as a leader in the Reference Data Distribution and Integration space, named by Aite as the most packaged Reference Data Distribution solution and included in the Gartner visionaries’ quadrant.

PolarLake’s clients include 6 of the top 10 Investment Banks, 2 of the top 5 Prime Brokers and 2 of the top 10 Asset Managers in the world.
 

PolarLake RDD is the world’s first and only purpose-built Reference Data Distribution business application and has been implemented in sell side and buy side organisations.

Industry analyst estimates spend on Reference Data Distribution will be $2.5bn in 2008 and $3.5bn by 2010.

Commenting on the report, PolarLake CEO John Randles said, “PolarLake is very pleased with the validation of its position by Aite. The report recognizes that financial services organizations are spending vast amounts of money on integration. We believe this is largely due to the fact that people are using the wrong tools for the job. Building Reference Data Distribution with generic EAI tools is so expensive because they are not designed for the complexity of the build problem nor the ongoing maintenance problem. This is why a purpose-built platform like PolarLake RDD can be implemented with 80% less resources and 75% less time to market than traditional EAI tools.”

PolarLake helps companies to distribute data throughout their organization in less time, for less cost and less risk than it would take with traditional SOA / EAI / ETL solutions. PolarLake's industry specific solutions have been delivered with 80% less resources and 75% faster time to market than traditional horizontal solutions. Built on PolarLake's proven patented rule layering technology, PolarLake's industry solutions enable large firms to handle the complexity of operating in today’s interconnected data networks without spending large amounts on coded one off solutions.

Financial Services customers include JPMorgan, Société Générale, Dimensional Fund Advisors, Pioneer Investments, Nissay Dowa, Man Financial and Bank of Ireland Security Services. Government customers include the UK Home Office, UK Crown Prosecution Service, UK Courts Service, UK Youth Justice Board, Warwickshire Police Service, UK Metropolitan Police and the UK Department of Constitutional Affairs. Manufacturing and Telco customers include Sony, Toshiba, Ricoh, KDDI, Midwest Wireless and NTT Group

Customer Profile

The company is a leading global financial services firm with assets of over $1 trillion and operations in more than 50 countries. The firm is a leader in investment banking, financial transaction processing, asset and wealth management, and private equity.

Requirement: Manage Risk Through Optimal Credits Trading

The company is using PolarLake to manage risk exposure through real-time communication across bond, futures and credits trading. Specifically, PolarLake is being used to ensure that risk associated with bond and future trading is managed as efficiently as possible and trading performance is improved.

In order to offset risk, the Credits business relies on data relating to bond and future trading, plus price and position information, to be supplied in real-time to the Murex platform that supports credits trading. In order to build such a solution, it is necessary to manage a number of data transformations in real-time.

Solution: Real-Time Delivery of Trade Data to Credits Platform

This role is performed by PolarLake, operating within the bank's 'Credits Message Broker' (CMB), which:

• Receives data relating to bond and futures trades in XML format from Rosetta (which in turn has received this data from the bank’s internal trading platform), and converts this into the MxML format required by Murex.
• Splits multi-event messages into single-event messages, in order to support the integration process
• Where relevant, requests and attaches appropriate Reference data – retrieved from the bank’s internal Reference Data management solution – and delivers this to Murex alongside the trade data.
• Records and audits all messages passing through the CMB, and writes this data to an external database

Why PolarLake? Configuration of Complex Transformations

The transformation of formats from Rosetta XML to MxML is extremely complex. Changes in either schema can involve substantial re-development with significant time and cost implications. However, by using PolarLake this transformation can be configured in its entirety, which in turn means that the solution can be easily adapted to meet changing requirements.

This ability made the PolarLake solution preferable to the alternatives, whether these involved 'hard-coding' the integration process or relying on proprietary integration tools. By delivering improved flexibility PolarLake ensured that the finished solution will support the business by delivering both improved trading performance and increased operational efficiency.

Customer Profile

The company is a leading global financial services firm with assets of over $1 trillion and operations in more than 50 countries. The firm is a leader in investment banking, financial transaction processing, asset and wealth management, and private equity.

Requirement: STP in Credit Derivative Trading

The company is using PolarLake to improve the efficiency and accuracy with which trading systems are updated with credit default swap affirmations originating from inter-dealer brokers, such as ICAP, Creditex and GFI. By doing so the bank is improving both trading performance and competitiveness levels.

Solution: Automated Mediation Across Multiple Systems

Credit default swap affirmations, originating from trades with external inter-dealer brokers, and formatted in FpML (Financial Products Markup Language) format, are processed by a PolarLake server within the bank's 'Credit Message Broker' in order to support the needs of front and back office systems, and specifically Murex. These systems rely on the delivery of this information in as timely a manner as possible in order to support the trading function of the company. Murex itself had been adopted in order to ensure total compliance with regulatory requirements.

The PolarLake Server:

• Performs complex transformation logic in order to present these transactions in formats appropriate for downstream applications (for example MXML for the Murex trading platform)
• Incorporates and attaches Reference Data relating to trades where necessary
• Routes each transaction, via WebSphereMQ or other appropriate transport mechanisms, to the relevant downstream systems

Why PolarLake? Flexible, Extensible Architecture

The initial project was focused upon the delivery of straight through processing between inter-broker dealers and Murex. However, since deployment additional elements have been added to the solution:

• The range of incoming trades has been extended to include those from ECNs within North America such as Bloomberg and TradeWeb.
• Integration with the Tzero platform, supplying post-trade services, including affirmation, greatly increases the accuracy and speed with which credit default swaps are settled. PolarLake detects trades requiring routing to Tzero and runtime.
• Support for other lines-of-business, such as Prime Brokerage, that may also wish to trade credit default swaps, has been added, enabling them to also enjoy the benefits of straight-through processing of these financial instruments.

The finished project thus supports the credit default swaps business throughout the bank, handling integration with all relevant internal and external systems in order to deliver, in the most efficient way possible, data that is both timely and consistent – which in turn improves trading performance and competitiveness.

Customer Profile

A global investment manager with €147.2 (US$179.9) billion assets under management in a full range of asset management solutions including mutual funds, single manager funds, funds of hedge funds, managed accounts and structured products.

Requirement: STP Between Fund Manager and Transfer Agency

The customer is using PolarLake to integrate with a Transfer Agency application, submitting fund management instructions across the SWIFT network and integrating with the application through a Web Services interface.

The company wished to improve operational efficiency, guarantee accuracy, and lower the development cost and risk associated with integration with a third party agency.

Solution: Transformation of Complex Message Formats

By using PolarLake the customer is able to:

• Automate the complex data transformations - such as from SWIFT to XML - required within this project quickly and easily
• Perform ongoing auditing and monitoring of traffic between the two parties and integrate this function with existing Business Activity Monitoring approaches
• Significantly reduce the up-front and ongoing investment required to automate the relationship
• Convert outputs from the Transfer Agency application into SWIFT messages in order to communicate confirmations back to client brokers and dealers

PolarLake’s ability to support multiple data formats, transport protocols and integration methods supports asset managers developing tight integration with multiple business partners including transfer agencies, prime brokers and global custodians – each of whom may require data to be delivered in different formats and using different technologies.

Why PolarLake? Ability To Extend And Evolve

PolarLake was chosen for this project for a number of reasons, including:

• A preference for configuration over traditional code-centric approaches. The latter approach to this challenge would be complex and involve significant development risk. Within PolarLake, however, the integration can be configured graphically and prototyped rapidly
• The ability to extend the system quickly and easily as requirements for integration between the two organizations change over time
• The desire to adopt standards-based integration (based around XML and Web Services) required a solution capable of supporting both these standards and also the data formats (such as SWIFT) particularly associated with Financial Services environments. PolarLake was uniquely positioned to provide this functionality