Goldman Sachs, Research Renaissance and Mergers: A Week in Review

Goldman Emulates Google

How do you manage and optimize data operations in a financial institution that counts over 32,000 staff, of which 8,000 are engineers or computer scientists who work with and produce enormous datasets on a daily basis? According to Joanna Hannaford, head of technology at Goldman Sachs, the answer is to seek inspiration from the likes of Google and Amazon.

Speaking at the WatersTechnology Innovation Summit, Hannaford explained how these consumer-facing giants informed the bank’s data strategies to not only cope with the ever-increasing quantities of data that are now produced through banking operations, but also how to best use datasets that would otherwise have gone to waste.

Itivti & Ullink Merger

The merger and acquisition (M&A) merry-go-round shows no signs of stopping at the end of 2017, thanks to the latest deal between two European tech vendors to join forces. Sweden’s Itiviti has announced it will acquire French counterpart Ullink, effectively quadrupling its client base and significantly building out its buy-side offering at the same time.

Ullink has been a staple of WatersTechnology’s various awards over the years, winning consistent acclaim for its FIX order routing network, Nyfix. While financial details of the deal have not been made public, Ullink’s credentials are clear to see and it will more than likely wind up being a good deal for Itiviti CEO Torben Munch and his business.

Research, Analytics Renaissance

While the topic of research has been, to a certain extent, hijacked by the incoming Mifid II unbundling requirements, there are a huge number of new technology developments going on in this space. Our US editor, Anthony Malakian, has put together a fascinating insight into some of these advances and trends pertaining to quantitative analytics.

As Anthony rightly points out, these systems still “need more time in the oven,” but it’s exciting to see various industry players putting time and resources into elements such as machine learning, natural language processing, new programming languages, alternative data and open-source projects to really drill down into the data they have at their fingertips. It’s definitely worth a read.