The Post-POINT Transition Series - Part 2: Data Considerations

Posted by Lisa Conner, Head of Data Management, BISAM on Aug 4, 2016 7:00:00 AM
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What is the best alternative for Barclays POINT Software?

In the world of Risk and Performance and Attribution, the players are buzzing – what is going on with Bloomberg LP and the acquisition of Barclays POINT and the Barclays Fixed Income indices? 

Looking back over the past few years prior to the announcement of this deal, the market was spinning with rumors of the acquisition, and market data consultants were polling every subject matter expert to speculate who might be in a position to buy this application and content.  What would happen to the data? The quality? The unique position that Barclays has in the fixed income portfolio management world?

The Domino Effect

POINT is a mission critical application across many front- and middle-office functions and processes that now stand to be disrupted. Concerns about the domino effect across organizations have most POINT users now looking for alternative applications to fill the gaps and ensure their groove is not disrupted. 

Last week my colleague, Sean Murray talked about the extensive industry discussions currently revolving around the search for a new solution…or solutions. Sean looked at the considerations to be made for application functionality. Today I will discuss related data considerations.

The Data Discussion

What are the underlying data implications when it comes to outlining a firm’s POINT replacement plan?   What is the best way to go about doing the analysis necessary to make the best decisions for your enterprise?   

POINT covers the full spectrum of asset classes within Fixed Income and subsequently has the analytics to support them.  With this single source going away, is it cost effective to consider multiple fixed income data sources to create a golden copy that mirrors the firm’s IBOR or PBOR?  For Chief Data Officers and data experts who are working with data governance counsels across firms, what are the key variables to include in the decision to ride the migration out or jump ship?   Does it make sense for your firm to have a waterfall approach to mining data from multiple sources into a single analytical platform - like BISAM’s B-One, for instance?

Consider the Index Data

Barclays has built a series of world class indices with stringent market-tested methodologies and there’s transparency around those rules of inclusion and rebalancing. But what about the continuity?  Will the history be restated to correspond to Bloomberg Fair Value?  Will there be an effect date of the change so from one day to the next, the pricing methodology will change?  Could it be optional – use restated data historically or not?  Again, it comes down to how much change that POINT users are willing to accept and how much change Bloomberg will effect. With so much uncertainty, combined with client expectations that processes (reporting, etc.) will continue as expected, the client pressure to remain consistent is a major variable.   Is it possible that a new set of indices will challenge the Barclays indices now that they’re part of the Bloomberg world?  There have been several firms throwing their hats into the index arena, and data managers would be well-advised to do their research and understand current and emerging options.

The final part of the equation I’ve thought about is related to the middle office. Does the POINT situation give market players an opportunity to make some critical infrastructure decisions related to the middle office that could drive their firms toward a unified solution to suit all aspects of the business? 

I’ve previously written about central data warehouses with tenants conformed to a firm’s data governance rules for access, audit, history, validation, versioning. If this is something your firm has long been considering, now is the time to consider a performance and attribution system that takes into account your own holdings and transactions, while enabling you to incorporate your own custom rules, generate reports using multiple models and pair P&A alongside a world class risk system. Consider the value in having everything under a single umbrella, complemented by robust analytics engines and the “right” data.

Topics: Data Management, Fixed Income Attribution, Performance & Attribution, Risk Management, Barclays POINT Transition Series

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