Cameron Peak is the Lead Data Scientist at Synechron. In this role he leads client Data Science deployments, mainly in AML and Fraud Detection. Cameron also works within their internal R&D team, implementing cutting edge Machine Learning techniques to answer industry problems through their Accelerator programme.
In recent years, we have seen many businesses realise the potential of unstructured textual data to transform their businesses through automating the handling of vast data, such as for legal documents, corporate filings, email alerts, client correspondence and news sources. Each year has brought generational shifts in the possibilities of Natural Language Processing (NLP) techniques, for example GPT-3 and BERT, with language models that can now match or exceed human performance in comprehending and classifying text. This year I expect to see this trend accelerate, with wider adoption of Natural Language Generation (NLG), which uses AI to create many of the hand-produced documents we interact with every day. By deploying the summarisation capabilities of NLG, you can deliver highly personalised reports and analysis to users in an easily digestible form, as well as automating the repetitive and time consuming production of reporting and workflow documents.