IBS Journal September 2016
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with applications and services running in-house. That mode is becoming more and more unsustainable as costs mount up. The savings of moving to the cloud are outweighed, in the minds of some, by its reputation as an unreliable place to store data. This opinion has persisted since the early 2010s when the cloud first became a widespread option for global businesses. A few firms are coming around to the idea of trusting their data to outside companies like Amazon, especially as hacks and data breaches continue to show that they can’t trust their own systems. By encrypting non-core data and moving it to the cloud, firms are promised a greatly reduced cost. The increasing proliferation of cloud-based data applications, which can allow a firm to store, code, de- code and analyse its Big Data without having to deal with the costs of in-house server architecture and security. It seems that the industry is catching on to these benefits, as a Cognizant survey revealed that up to 87% of investment firms use some form of cloud computing service.
So what about automation? The use of artificial intelligence could be a potential way of gaining useful insight from the reams of data gathered by banks. Josh Sutton, Global Head of Data and AI at
Publicis.Sapient, reckons that there are three primary ways that capital markets firms are leveraging AI technologies today: insight generation, customer and client engagement and business acceleration.
“An example of insight generation,” he tells IBS Journal, “is using AI tools to extract ideas from unstructured data such as social media and online blogs. The power of today’s tools to translate this raw data into tradable information is creating alpha generating ideas for today’s top firms.” Business acceleration, he adds, is a term for the uplifting of knowledge-based activities via the use of AI tools. These can range “from resolving trade settlement issues to creating comprehensive research documents on a given company”. The creation of BCBS 239 compliance reports “will almost definitely” be enabled by AI tools in the short term, says Sutton. “That being said, the challenge that most organisations will have is the deployment of these solutions – similar to any large data problem at a large capital markets firm, the challenge is more often in finding and aggregating
the required data than it is in performing the actual analytics.”
AI is beginning to be a lot more welcome to firms in the industry. “Nearly all of the firms that I am talking with are beginning to experiment with artificial intelligence tools,” states Sutton. “This is a substantial difference from a year ago when many people were talking about AI but very few companies were actually doing anything. I think it is safe to say that if a firm isn’t at least exploring the uses of AI within their organisation, they are beginning to fall behind their competitors.”
Perhaps no other buzzword will throw up more puzzled looks than blockchain. The vice-tight encryption methods of distributed ledger technology, along with its policies of mutual consensus verification and smart contracting, make the use of blockchain an attractive way to deal with data. The major criticism of incumbent technologies is that they are fragmented, highly complex and lack common standards – something that drives costs high and requires consistent reconciliation. All of these complaints could be solved by the introduction of a system based on a distributed ledger, say evangelists. But how? Pre-trade, blockchain offers transparency and verification of holdings, mutualisation of data and simpler know your customer (KYC) and know your customer’s customer (KYCC). In trading, transactions are performed in real-time and provide immediate irrevocable settlement with the confirmation stored on both payer and payee’s systems as tamper-proof block information. Automatic reporting can also be integrated, adding an extra layer of transparency when dealing with regulatory bodies. A “perfect” blockchain system also offers no central clearing, reduced margins, auto- execution of smart contracts and a system of common reference data.
So what’s the hold up? Despite its exciting burst onto the FinTech stage at large, blockchain has yet to prove its credentials at large-scale companies, and whether it can play nice with legacy systems like risk management. Blockchain firms have also been preventing from attempting such large-scale tests by regulatory stumbling blocks. Anonymity, a cornerstone of many processes in capital markets, is both a blessing
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