Advancements in natural language generation (NLG), a software process that automatically transforms data into a written narrative, is making lightning-fast generation of expert business intelligence a reality in today’s financial markets.
The potential for NLG to transform the way analyst reports are generated and distributed is no secret in the fintech industry. As more banks seek to equip themselves with the tools to instantly turn data into relevant, intuitive and timely information, the NLG market is expected to more than double in value from USD 322.1 Million in 2018 to USD 825.3 Million by 2023.1
The drivers behind this demand are clear. Banks face increasingly complex challenges every day, competition is fierce and the effect is that profits are harder to generate than ever before. Meanwhile, increasing regulation and transparency requirements are an ever-growing burden.
Banks already have the data they need to overcome these challenges, but converting it into intelligence that can support informed decision-making ties up their data experts or quants with routine and repetitive tasks. Given the exponential growth of available data, surfacing the most relevant insights is the most worthwhile goal. NLG can automatically turn this data into human-friendly prose.
NLG has existed in more basic forms for some time, but only recently has the technology become advanced enough for application in sectors such as capital markets. A simple, early example of NLG usage, albeit in consumer rather than wholesale financial markets, is a system that automatically generates form letters, such as a letter telling a consumer they have hit their credit card spending limit.
These simple systems use templates not unlike a Word document mail merge, but today’s increasingly sophisticated NLG systems dynamically create text using either explicit models of language or statistical models derived by analysing human-written texts.
For banks, this holds the key to major improvements in efficiency for their business intelligence departments and beyond. As the amount of data available continues to grow, banks are increasingly overwhelmed with report writing, presentations, client reviews, sales performance and regional reviews – the list goes on and on.