MiFID II delays helping firms reduce tech debt

Delays in the publication of Regulatory Technical Standards (RTS) for MiFID II are having a positive side effect - incentivising financial services firms to take on major system overhauls in a bid to reduce their technology debt, claims a paper from GreySpark.

  11 Be the first to comment

MiFID II delays helping firms reduce tech debt

Editorial

This content has been selected, created and edited by the Finextra editorial team based upon its relevance and interest to our community.

GreySpark argues that new regulations such as MiFID II normally increase 'tech debt' - inferior aspects of the technology environment - because firms are forced to rush to meet tight compliance deadlines without focusing enough on the knock-on effects.

The rush of new regulations introduced since 2009 has seen firms resort to "tactical bolt-on or hack-based fixes to existing software platforms as opposed to the application of the organisational effort required to redo those platforms completely," says GreySpark.

But the RTS delay is giving banks and buyside firms breathing space to think holistically about their technology upgrades, with many taking the opportunity to eliminate their tech debt balance by replacing legacy, siloed data management, data processing, risk management, reporting, compliance and client-facing systems with new, streamlined systems.

GreySpark cites one Tier 1 bank which has recently replaced a plethora of semi-golden sources and multiple reporting systems per business line with one, cross-organisational data warehouse and a fully customisable reporting engine.

Says the paper: "Therefore, from a technology perspective, the one-year delay in MiFID II’s implementation may bring benefits to those companies that were already proactively working to disavow the compliance gap."

Sponsored New Event Report – Natural Capital Finance

Comments: (0)

[On-Demand Webinar] PREDICT 2025: The Future of AI in the USFinextra Promoted[On-Demand Webinar] PREDICT 2025: The Future of AI in the US