THE CLIENT: A Swiss$-$based multi$-$asset management firm with $$95$ billion in assets under management.

USERS: Alternative Style Premia Team

This Swiss$-$based investment management firm specializing in alternative investing sought to leverage natural language processing $($NLP$)$ to extract valuable insights from earnings call transcripts. Managed as an independent company, the firm has developed long$-$term partnerships with its clients largely due to its expertise in private markets, liquid alternatives, and multi$-$asset solutions. Being a principal investor in its own strategies, the company has become a leading global alternative investment specialist.

The investment firm manages various asset classes throughout international markets, including equities, fixed income, private assets, and liquid alternatives. The Alternative Style Premia team is a middle$-$size group consisting of portfolio managers and quantitative strategists responsible for creating and implementing rule$-$based investment strategies that exploit various economic, price$-$based, and fundamental factors driving the cross$-$section of asset returns. To boost the performance of their market$-$neutral equity strategies, the team decided to expand the spectrum of investment signals by adding numerical scores derived from quarterly earnings call transcripts. Pain Points

The investment team needs to make both tactical and strategic decisions. Its members saw the benefits of using natural language processing $($NLP$)$ but gathering and maintaining the information as well as developing algorithms would require an extensive amount of time. In addition, the team was concerned about coverage, quality, and reliable data delivery on a daily basis.

They wanted to outsource this task to a reputable provider that offered:

A comprehensive set of elaborated sentiment and behavioural metrics that would allow for generating low$-$correlated investment signals.

Machine$-$readable data enabling full integration into the existing strategy$-$building process on the trading platform and leveraging the information available on the transcript component level.

Integrated meta$-$data to set up sentiment monitoring on the aggregated level $($e$.$g$.,$ sector, index, etc.$)$

The Solution

Solution engineers from S&P Global recommended enhancing the current strategy mix with numerical scores obtained from earnings call transcripts. As the investment firm has been using the CIQ Financial data for building and managing its equity strategies, the new dataset was integrated smoothly into the existing investment framework. The scores are delivered in a structured format facilitating an efficient strategy back test. The extensive meta$-$data allows for flexible score aggregation on the industry, geographical, and index levels. The scores are

delivered within $90$ minutes after the end of the earnings call which enables the investment team a timely reaction to any unexpected news. QUESTIONS $[40]$

$1\mathrm{.}1$ Using relevant research elaborate on what is natural language processing. $(15)$

$1\mathrm{.}2$ Examine how NLP can assist the organisation with digital marketing. $(25)$