Learn how Societe Generale has been working with Opensee to leverage data and innovation as part of the transformation of its risk and finance operations.
Data, disruption and innovation were top of mind at this year’s RiskMinds International conference, held in Barcelona 7-10th November. To delve deeper into these themes, Opensee invited Xavier Lofficial, Group Deputy CFO of Societe Generale, to discuss with its Founder and CEO, Stephane Rio, how the international banking group has been working with Opensee to leverage data and innovation as part of its transformation of its risk and finance operations.
The discussion began with Lofficial summarising the set of challenges facing the 158-year old banking institution. He pointed out that the only real way to navigate through this current uncertain environment is to have access to extremely relevant data. He added that regulators have been pressuring financial institutions for increasing amounts of detailed data, forcing them to align their internal production of this data with the new reporting requirements. As a result, banks are having to deal with a scale of data and a level of granularity never seen before, he noted. Not only has Societe Generale multiplied the amount of data it has to store, it has also had to increase the number of calculations it needs to run on a regular basis. Furthermore, Lofficial flagged that another challenge facing Societe Generale was its ambition to give back control over accessing the data to business users. As a result, the group is transforming the way it works, allowing end users to manipulate data at scale, with the ability to quickly drill down into the data and undertake calculations without needing to access the underlying data.
Both participants were then asked about how they were addressing these common challenges in terms of high-level, industry-wide initiatives. Lofficial explained that Societe General has adopted a modular architecture approach to its IT systems composed of best-of-breed solutions, which in turn have a very organised and standardised way of capturing information. What the group would eventually like to see, he remarked, is desk-top operators being able to access data lakes and implement calculators per risk family, with the ability to produce relevant information, for example, either regulatory or steering committee reports.
Later in the session Lofficial explained how Societe Generale’s decision to go forward with a modular architecture approach led it to set up an incubator programme for external companies. As a successful candidate, Opensee completed a minimum viable product (MVP) with Societe Generale and its users. Because of the close work with Societe Generale, Opensee was able to improve its product demonstrably and is now able to deliver some risk functions as a cloud-based, fully-packaged solution while still allowing users to access data at the granular level.
Rio pointed out that in today’s world, banks are being required to obtain granular access to gigantic datasets, including historic databases. He noted that manipulating this data at size and in a user-friendly manner can be a challenge. In fact, this has been a common factor across all risk use cases, including market risk, credit risk, liquidity risk, and ESG risk, he observed. Rio felt that ESG risk in particular would take the classic trajectory of other more mature risk classes, such that the macro level risks would eventually turn into more micro-level risk levels, which in turn would translate into more granular datasets. He also predicted that soon it would be possible to bring together two previously siloed risk sets, for example ESG risk and credit risk.
Both participants spoke about the benefits and results of Societe Generale’s key risk management initiative, of which Opensee’s data mining and analytics solution is an integral part. Lofficial explained the transformation occurring at the bank was still ongoing, and concentrated on the normalisation of the data feed to ensure that the back office systems around the finance and risk information systems can translate and transform the information in a standardised way. Yet, thanks to use of the data lake, standardisation of feeds, streamlining calculators and progressing on restitution, Societe Generale is now able to produce various and complex metrics at T+1 with data from the previous day, whereas a few years ago the lack of infrastructure and processes made this impossible. Rio was keen to emphasise the business value that can come out of this type of transformation. He explained that now the data has become more accessible and clean, an ongoing opportunity exists to discover new use cases, especially through the use of machine learning.
Going forward, Societe Generale intends to capitalise on its risk and finance transformation agenda to be prepared for any irregularity or uncertainty that might come its way. For Lofficial this means building an information system that provides easy accessibility to data at the highest level of detail in a near real-time environment. This will allow the Group to accelerate in whichever direction it wants, whenever it is needed, he concluded.
For Opensee, the acceleration of data is not going to slow down, so financial institutions need to start thinking about how machine learning can help manage and standardise data, as well as how the Cloud can accelerate time to market, thereby reducing costs. In the words of CEO Stephane Rio, therefore, the way financial institutions can best be prepared for the future is by providing scalable, resilient solutions that are flexible enough for information to be accessed easily.
Discover in this video the key takeaways of our panel discussion with Xavier Lofficial, Deputy CFO at Societe Generale, and Stéphane Rio: