Financial organisations dealing with hundreds of terabytes of data are currently sitting on unrealised opportunities to serve their customers, gain competitive insight and satisfy regulators.
Firms need to work more intelligently with today’s data volumes to become more resilient and better withstand future shocks to the global financial system. Yet many institutions are finding that the complexity and cost of accessing this data are proving
obstacles to using this information in a timely and meaningful way, while at the same time being under enormous pressure to economise by delivering much-needed divisional and enterprise-wise operating efficiencies.
What data analysis means today
The challenge of unlocking the business value of data has become an acute issue, with banks, hedge funds, asset managers and insurance companies looking to fully exploit the potential of all data. Financial institutions are sitting on vast amounts of data
as they store up to terabytes of newly generated data every day. With many having invested significantly in storing data, there is real business opportunity in being able to make these large quantities of data widely available internally and allow business
users to actually “play” with it. The world of finance is on a journey to optimise the use of all the data it holds, and data analytics “at scale” is helping to accelerate and release the value of all the information stored.
While recent storage solutions have allowed institutions to save and retain more information than ever, it is rarely well “cleaned”, homogenised or structured. Further, these storage solutions are not fit for purpose for business users of financial institutions
to interactively perform analytics on such large amounts of data. Many business users currently have to make conscious compromises, limiting their ability to fully leverage all the data they have stored. For example, choices around seeing less history or less
depth (i.e. accessing only pre-aggregations) in their data; or choosing to expand the data volume, but at an unsustainable and often spiralling complexity and cost. The constant compromise between speed, volume and cost control creates limitations in interactivity
and fails to optimise existing financial institutions’ investments in data.
Big data challenges
Those compromises create countless frustrations on the business side. Here are a few illustrations:
Risk managers want to interactively analyse market and credit risk in a single view. They need the capability to go from a high level visualisation of data to granularity of all available data in any direction, with any depth and any history, and be able
to interrogate the data in a way that’s meaningful and that they can easily understand.
Asset managers want to precisely analyse all the data at hand to deliver “true” best execution and minimise transaction costs.
Treasurers want the ability to aggregate all available data without limitations to precisely forecast their liquidity needs or surplus at any time.
Helping financial firms realise true data potential through analytics
Opensee, formerly ICA, was born out of our personal frustration as former capital markets senior executives, at not being able to find an appropriate Big Data analytics solution that would enable us to easily and efficiently manipulate, explore and perform
“what-if-analysis” on the hundreds of billions of data we were handling across the business. So we created a team of financial industry and data analytics experts and formed Opensee, to build our own solution and help others still struggling to unlock vital
business-user-led opportunities, “dive deeper” into their data.
We are focused on pushing the boundaries of self-service data analytics for financial institutions, building on our capital markets heritage to help banks, hedge funds and asset managers tackle their data challenges - at scale. Opensee gives financial institutions’
business users the autonomy to perform any aggregation and, more broadly, any analytics on demand.
A background of growth
We have seen an acceleration in the way our initial Tier 1 banking clients are using our Big Data analytics solution, from the Risk department to Treasury and then Commercial too. At the same time we are helping business users of smaller banks or on buy-side
(asset managers, hedge funds) harness 100% of their vast quantities of data and tackle their own data challenges. Our rename reflects these changes, marking a new chapter of growth.
We wanted a name that more closely captures our vision on big data and embodies our long-held belief that there is a better way to help business users across financial institutions analyse today’s very large amount of available data, deeper and faster.