About a-team Marketing Services
The knowledge platform for the financial technology industry

A-Team Insight Blogs

Talking Reference Data with Andrew Delaney – The Curse of Approved Supplier

Subscribe to our newsletter

We were saddened to learn earlier in the summer of the demise of Hyper Rig, a pioneer in the area of risk aggregation. To us, Hyper Rig’s commercial offering seemed as close as one could get to meeting practitioners’ stated requirement for a means of deriving risk measurement/management information from the broad range of relevant data from across the enterprise.

The offering seemed to match what practitioners are describing to us as the Holy Grail: the ability to collect and integrate pertinent risk, position and market information into a single point of contact for risk management.

So what went wrong?

The Report to Creditors and Members issued May 30 makes for interesting reading.

Hyper Rig was in fact the marketing vehicle for CKlear, owned by Hyper Rig CEO Michael Coleman, which held the intellectual property for the risk aggregation platform. The company began trading in 2009 and managed to generate profit of £150,000 on revenues of more than £800,000 for fiscal 2010.

Despite the termination of a contract with Barclays Capital in late 2010, the firm secured paid-for trials at Credit Suisse, Deutsche Bank and Royal Bank of Canada, among others, with the prospect of some £2.5 million of revenue.

Based on this interest, the company embarked on a fund raising exercise in 2011, with commitments of between £1 million and £2 million, contingent on closure of a platform sale to one of the these prospects. According to the report, due to the ongoing problems in the Eurozone, budgets among triallists were frozen until February 2012 at the earliest.

Having struggled through 2011, the firm managed to gain interest from Royal Bank of Canada, which at the beginning of this year looked set to commit to a £800,000 contract. Moreover, an investor had also announced plans to deploy the system along with two of its customers.

Things were looking rosy, but a dispute among the shareholders – a minority shareholder sought to liquidate his holding – led to a statutory demand being served on the company in April. Funding and client interest unravelled from there.

That a shareholder dispute could lead to the downfall of a provider of a mission-critical function like risk aggregation speaks to the broader issue of scale. Financial institutions – today more cautious than ever – are nervous of buying from smaller players, no matter how visionary.

No-one got fired for buying IBM, as they say, and the curse of the ‘approved supplier’ list hits smaller, innovative companies everywhere. Hyper Rig seems to have paid the ultimate price.

Subscribe to our newsletter

Related content

WEBINAR

Recorded Webinar: The ROI of Data Trust: Quantifying the Business Value of Data Observability

Data is the fuel that keeps modern financial institutions’ motors running but if that data can’t be trusted then the decisions made based upon it, or the uses to which its put, will be compromised. That’s especially important for data that’s fed into artificial intelligence models. If the data isn’t clean, accurate and complete, then...

BLOG

Ataccama Gathers Data Capabilities into Focused EU AI Act Package

As the implementation date for the European Union’s AI Act looms, financial institutions are having to put their data estates on a secure footing to ensure they comply with the wide-ranging regulation. The Act requires organisations to have a broad and granular view of their data in order to show that they can trace any...

EVENT

Eagle Alpha Alternative Data Conference, Fall, New York, hosted by A-Team Group

Now in its 8th year, the Eagle Alpha Alternative Data Conference managed by A-Team Group, is the premier content forum and networking event for investment firms and hedge funds.

GUIDE

AI in Capital Markets Handbook 2026

AI adoption in capital markets has moved into a more disciplined phase. The priority is now controlled deployment: where AI can be used safely, where it can deliver measurable value, and how outputs can be governed, monitored and evidenced. The 2026 edition of the AI in Capital Markets Handbook examines how AI is being applied...