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By Jordan Ambrose is CEO at Inforalgo

Intensifying international regulatory demands around trading transparency are tipping financial institutions over the edge, according to new research. Inforalgo’s Jordan Ambrose interprets the findings

Jordan Ambrose is CEO at Inforalgo

Jordan Ambrose is CEO at Inforalgo

The latest wave of financial services reporting mandates, designed to foster greater trading transparency globally, is pushing many institutions over the edge. Compliance is consuming too much time and budget, they say – without adding any real value for the business.

So concludes new research from independent financial regulatory think-tank JWG, commissioned by Inforalgo. The findings shine a light on soaring data/IT project costs, and point to growing interest in alternative approaches to transaction data management. Instead of tackling each regulatory requirement separately, firms are seeking a more repeatable approach to collating and validating information, and preparing reports.

The regulatory burden is certainly substantial. Taken together, the new or additional requirements of MiFID II, EMIR, Dodd-Frank, FINRA TRACE, CAT, SFTR, and MAS, make for an onerous compliance exercise for trading parties keen to maximise global market opportunities, as each update goes live.

Costs & inefficiency soar

It isn’t only the risk of non-compliance, potential fines and reputational damage that has prompted a review as demands rise. Firms are also becoming more acutely aware of the amount of information repetition and duplicated effort involved as they collate, prepare and turn around trade data to fulfil each authority’s particular requirements.

“(The) business is fed up with investing in regulation! Instead, we need to slash costs,” remarked one project manager from a major German bank participating in JWG’s qualitative research, among 12 global financial institutions, late last year. The bank is currently grappling with MiFID and MAS (Singapore authority) reporting.

Time pressures are a very real concern too. If firms wait until the end of the day to reconcile all of their transaction data and generate reports, this can cause bottlenecks – especially if exception/query resolution involves input across different time zones.

Creating sustainable reporting

Above all, firms want to manage their regulatory obligations in a more efficient, reliable and repeatable way. Relying on manual processes and spreadsheets is impractical, burdensome, costly, inefficient and fraught with risk. It prevents a clear line of sight across trade activity, and hinders potential useful insights – for example, into the relative cost of transactions, or where common errors are concentrated.

Ideally, FS providers need to be able to routinely amalgamate data and get it into a robust, readily deployable and centrally viewable format – wherever the respective original sources and formats.

A senior technology leader at a North American bank, contributing to the research, admitted that, because his organisation still had a lot of manual reference data maintained in spreadsheets, and had many, varied data sources – six in Singapore for trading source data; three for reference data; and 20 connection points in Ireland – its reporting activities had become highly cumbersome.

Intelligent automation offers an answer

Because different regulators each have their own particular data demands, it isn’t a simple case of being able to prepare fields once to meet multiple needs. Rather, firms need to employ rules-driven workflow to automate reporting according to each authority’s particular requirements.

As an IT manager at a European investment bank put it, if he had spare budget to spend on regulatory reporting, he would spend it all on central eligibility rules. “Enrichment and transformation of data is easy once the rules are defined, known, agreed and accessible,” he said.

In JWG’s findings, firms were looking for an ability to complete each set of reporting fields automatically, with the precise information that is eligible for declaration under each set of regulations. Having a rules engine capable of assessing data’s fit, accuracy and completeness, without writing or embedding code each time requirements are revised or added to, was high on interviewees’ wish lists – as was being able to re-use rules for other regulations, wherever possible.

The study also revealed interest in a more holistic approach to automating trading data management, for instance via a ‘centralised data hub’ capable of both supporting multiple trading-related process requirements, and of providing insights that might help firms reduce the cost of trading and improve yields. Inspired by the potential, most of the firms JWG interviewed had already begun to allocate some resources to this kind of strategy.

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