Institutions crave a more efficient, repeatable approach to compliance, boosted by intelligent automation, new JWG research suggests. Inforalgo’s Jordan Ambrose reports.
A raft of new and updated requirements to international trade reporting obligations are pushing many financial institutions to crisis point. That’s because they are struggling to meet all of the diverse requirements in the time frames allotted, and with the resources open to them.
These are among the findings of new research by independent financial regulatory think-tank JWG, in partnership with Inforalgo. They reveal that project costs, and the risks of non-compliance, are rising. Consequently, a majority of FS providers are reviewing their approach to transaction data management, and looking for a more sustainable, repeatable approach to preparing reports.
Regulatory demands are certainly increasing. There’s MiFID II, now almost a year into its implementation; EMIR, which is currently being re-written; Dodd-Frank; FINRA TRACE which is increasing the scope of reportable instruments; CAT and SFTR, which are due to go live in 2019; and MAS, due to be upgraded in 2020. Put all of these developments together, and there is no let-up for trading firms keen to maximise global trading opportunities.
But JWG’s in-depth, qualitative research, conducted with senior executives from 12 global financial institutions in October 2018, highlighted firms’ growing frustration with the processes involved with trying to meet all of the associated reporting obligations.
“(The) business is fed up with investing in regulation! Instead, we need to slash costs,” commented one project manager from a major German bank currently grappling with MiFID and MAS (Singapore authority) reporting.
Reduce, reuse, recycle
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.
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.
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.
Since different regulators demand different data, 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, where there is a close match between requirements from one authority to another.
The study also found that firms are beginning to take a more holistic approach to automation of trading data management. The need to control costs more broadly, and maximise revenues, is turning attention to the concept of a ‘centralised data hub’ – one that can support multiple trading-related process requirements, and increase visibility of transaction data and activity with scope to reduce the cost of trading and improve yields. Most of the firms JWG spoke to had already begun to allocate some resources to this kind of strategy, in recognition that a more holistic data automation approach could offer a degree of market advantage.