Large investment firms are tapping into natural language processing to build in-house automated solutions, according to a report published today by text analytics company FinText.
Large investment firms are tapping into natural language processing to build in-house automated solutions, according to a report published by text analytics company FinText.
The analysis reveals two forces are pushing investment banks and asset managers to experiment with this specialised branch of AI technology. Text is seen both as a new frontier for hidden market signals, and as a growing concern, with firms struggling to adapt traditional processes to the ballooning volume of written communications.
The report, How Finance Uses Natural Language Processing, highlights that while solutions are commonly initiated to improve an internal process, they often result in two additional gains: reduced human error, and new services.
The investment industry’s rush to embrace natural language process is fuelled by the rise in computational power and large text databases. Crucially, the shift to open source software gives the wider business community access to powerful new tools.
Vered Zimmerman, FinText Managing Director, explains: “When it comes to payoff, our assessment shows that monetary benefits are easiest to measure in terms of cost savings or excess returns. However, a greater impact is often seen with companies creating entirely new offerings, or successfully developing capabilities that were previously reserved only to larger incumbents.”
“What’s possible today was not available to most companies five year ago” notes Zimmerman. “Financial services firms are waking to the possibilities, and we’re seeing early movers capturing value with relatively little up-front investment.”
“The amount of text that investment companies are required to process is outpacing their internal processes’ capacity. Facing a tougher economic climate, firms are certain to look to make the most of their resources, and we believe we’ll see more creative applications coming out of banks and asset managers in the coming years.”
The solutions surveyed in the report include:
- Tracking media coverage
- Better sustainability investing
- Connecting data sources
- Extracting research insights
- Aligning marketing with sales
The analysis also finds that many of the solutions banks are currently deploying aiming to enhance human work rather than displace it. Applications typically target repetitive tasks and require specific tailoring to the relevant use case. For tangible gains, domain knowledge is still critical.
