The data management and risk functions of financial institutions have become subject to a “shotgun wedding of sorts”, as firms aim to tackle their underlying data quality issues in the post-crisis environment, according to panellists at last week’s A-Team Group Data Management for Risk, Analytics and Valuations (DMRAV) conference in NYC (see details of the London sister event coming up on 17 October here). Firms have therefore moved from the stages of denial of the problem to acceptance and change (albeit gradually).
Bottega recommended that firms looking to set off down the path towards tackling their underlying data management challenges (be it to support the risk function or otherwise) should first take stock of where they are currently. “A simple inventory of where you are at the moment with regards to data management and where the gaps are is the most important first step,” he said. “This must be done before any data quality metrics or data governance structures are set in place.”
The challenge, as always, is also to ensure that momentum is maintained throughout the data management change programme, once it has been kicked off, agreed panellists. Thomson Reuters’ head of strategy and business development for Enterprise content Tim Lind added that the function would have to continue to fight its corner and ensure that it doesn’t miss the window of opportunity granted by the financial crisis and regulatory change. “Never waste a good crisis,” he joked.
Of course, other business changes such as M&A activity will continue to pose a challenge to data management teams in the interim. The data quality panellists noted that going back to fundamental data definitions during an M&A process and ensuring that all parties are talking the same language is the most efficient and practical way of tackling this challenge. Sanjay Vatsa, managing director and head of transformations for Citi Securities & Fund Services, for example, indicated that he has been through three M&A events in his current role and that moving from multiple languages to a single language for data was a key coping strategy for his team.
“In a merged company you need to define common ground,” added HSBC’s Serenita. “Clear business definitions of data items are needed at the outset and this back to basics approach is a very important first step to take before you can put any kind of execution plan together.”
Vatsa compared data management to a religious cult with strict discipline and a set dictatorship to follow. “Data items X, Y and Z should not be subject to discussion and should have the right governance structure around them to ensure they are subject to strict validation rules,” he elaborated.
So, data has been married off to risk and compliance, gone through a ‘Who Moved My Cheese’ change programme and taken on cult like status. Some progress indeed for what many have called an unglamorous back office function. From wallflower to wedded bliss via a crisis.
