Global Investment Bank

Leveraging alternative data at scale through web scraping and AI.

Credera worked with a global investment bank to deliver a strategy and capability to dynamically identify, load, and use artificial intelligence (AI) to classify and extract key information from publicly available web sites and third-party data providers to fuel relationship building and company research efforts.

At a Glance

In a bid to differentiate and move up-market, a leading global investment bank partnered with Credera to leverage first- and third-party data for enhanced insights. Through a structured innovation approach, Credera and the client identified over 35 data product ideas, developing business models for the top 15 and prioritizing the top 10. Implementing advanced web scraping technology and a suite of natural language process (NLP) machine learning models, the team harvested publicly available information and converted it into actionable insights for the bank.

Collaborating with key client departments, Credera developed a comprehensive playbook for future data product development. As a result, the bank gained the ability to access and analyze web data within days, delivering differentiated insights on private transactions and proprietary datasets on private companies. These new capabilities fueled the bank's relationship development and prospecting efforts, paving the way for consistent, value-driven growth. Through Credera's innovative solution, the bank achieved a competitive edge in the dynamic financial environment.

The Challenge

Getting intuitive insights from a complex set of data sources.

The global investment bank has its foundations rooted in the searching and cultivation of transactional prospects. With expertise in investment banking, investment management, and private wealth management, the bank's leadership identified an opportunity to move up-market and differentiate through the creative use of first- and third-party data. They aspired to expand the insights available to bankers by harnessing publicly available and for-purchase third-party data for the identification, research, and cultivation of prospects.

The Solution

Going from conceptualization to implementation.

Utilizing a structured innovation approach, the global investment bank identified over 35 data product ideas to leverage publicly available data. The top 15 ideas were further scrutinized, leading to the development of business models, prioritizing the top 10, and formulating data pipeline designs to support their implementation. Credera also introduced the Data Product Development methodology. This approach facilitated collaboration with the legal, information security, procurement, operations, and technology teams to deliver a comprehensive playbook to guide the development of compliant, cutting-edge data products.

The Credera team recommended implementing web scraping technology to access the vast amount of data accessible on the internet, a veritable gold mine for company research and relationship-building endeavors. Credera leveraged and enhanced proprietary accelerators to produce a toolkit capable of efficiently extracting unstructured data from websites. This toolkit provided configurable patterns to locate pertinent web pages on a given topic, determine information relevancy, and mitigate many of the risks inherent to web scraping.

Once data was gathered, advanced NLP techniques for data extraction were employed, leveraging language understanding models including BERT and GPT-3. A human-in-the-loop review was incorporated to infer data from free text descriptions, biographies, communications content, regulatory filing documents, and forms.

The Results

Realizing value through the innovative use of alternative data.

The results of Credera’s involvement were transformative. The playbook has been instrumental in furthering consistent, value-driven execution as the bank's data team expands. A significant milestone was the bank's new capability to access and extract freely available data from the web within days. This solution continued to improve alongside rapid advances in AI and large language model (LLM) technology. 

Credera's solutions provided differentiated insights on key stakeholders for private company transactions, enabling enhanced relationship development efforts. For the corporate advisory team, a differentiated dataset was produced to quickly understand the sales process for all past public merger and acquisition transactions. Moreover, several proprietary datasets on private companies themselves were compiled, fueling the bank's prospecting efforts. 

The engagement provided the bank with a comprehensive, dynamic tool and process for harvesting key information from public sources, transforming how they approach relationship building and company research. This solution facilitated a more profound understanding of prospective clients and ensured the bank stayed ahead of the curve in a highly competitive financial environment.

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