Innovating with Data in the Financial Industries
Article written by Ian Allaway, Founder and Product Director at Wallscope
Wallscope has been working with Semantic Web Techniques and Machine Learning tools for several years. Their tools and services have been used to support Digital Transformation projects in the NHS and the Scottish Government. Here they explain how their technology can help manage big data across the financial sector.
“Like any large corporate or public sector organisations, the financial industries now have to come to terms with the ever-increasing growth of digital data. Data is typically stored in disparate sources ranging from legacy Content and Document Management Systems to relational databases and other data silos.
Finding information across these multiple sources can be time-consuming and overwhelming. There is a reliance on those who know where the information is stored, or the use of a traditional search engine to retrieve a linear list of documents.
How can a Knowledge Graph help?
A Knowledge Graph differs fundamentally from traditional search. It identifies entities (such as people, places, organisations or concepts) across vast amounts of data and exposes the relationships between them. This allows a dynamic exploration of resources which would otherwise be extremely time-consuming.
In the financial sector the use of this kind of technology has immediate benefits, particularly when combined with Machine Learning models. In the field of due diligence or know your customer, for example, it has many practical applications, allowing you to uncover related people, organisations or indeed financial transactions across multiple documents or data sources. It also makes it easier to collaborate across internal and external data sources, for example when performing credit checks. This has the potential to massively reduce the time spent on such operations.
Ontologies help us to organise complex information and aid the implementation of Knowledge Graphs. In the financial industries, existing ontologies are rapidly being developed and reaching industrial maturity, for example the Financial Industry Business Ontology (FIBO) and the STW Thesaurus for Economics.
Dynamic Data Discovery
Wallscope’s unique technology stack combines an Enterprise Knowledge Graph with Natural Language Processing, Named Entity Recognition engines and Machine Learning models to enhance the interoperability of contextual information.
Our Dynamic Data Discovery platform is currently being used within the Scottish Government and NHS Scotland to help unlock the value of their data. For example, we have developed a tool to help GPs work across disparate information sources, in order to better manage the care of patients recently discharged from hospital. This is a versatile application which could be used in any scenario where information sources are divergent. In professional fields where rapid response is a requirement it saves time and avoids unnecessary complexity.
We are now receiving interest from the financial sector which we are looking to expand on in the near future. We are looking forward to taking part in FinTech Scotland’s event on 27 September, exploring opportunities for cross-border collaboration between Scotland and Ireland.