Company
The client is a leading investment bank with multi-country operations. It provides financial advisory and capital raising services to organizations globally. A critical part of its due diligence and evaluation process is the comprehensive analysis of companies which involves the consideration of not just company-related data but also other information such as economic indicators, industry indicators and capital market data. Under the existing system, all data collection, aggregation and analysis were being done manually, with data needing to be aggregated from multiple sources.
The highly-competitive nature of investment banking necessitates taking critical decisions relatively quickly. The significant manual effort involved in analyzing companies impeded the client's ability to assimilate multiple data points, derive meaningful insights and get an overall view of a company. This adversely impacted its decision-making and investment opportunities.
The client sought help in developing an automated platform which could aggregate hundreds of data points - including real-time data - from diverse sources to facilitate comprehensive analysis of companies in the shortest possible time. The client also wanted to expand the universe of data sources through the use of the platform.
Challenge
Under the existing process, a team of research analysts had to frequently monitor multiple data sources to check for latest updates. The process was cumbersome, time-consuming and inefficient:
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Once latest updates were published, they had to be extracted manually and entered into financial models.
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The challenge increased when it came to integrating real-time data into the models. A manual system meant that updates of real-time data were delayed - this diluted the quality of analysis.
Due to manual processes and limited analyst bandwidth, the client also faced issues in aggregating data from new sources that would allow it to enhance the level of analysis and derive unique insights, thereby giving it a competitive advantage.
Solution
An extensive study of the existing process was undertaken to understand it in granular detail. The proposed solution had to not only automate the existing process but also make it dynamic so that new companies could be quickly set up for analysis on the automated platform.
Using proprietary technology, we developed a customized artificial intelligence (AI)-based dashboard that enabled the following:
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Automated data aggregation from 100+ sources comprising company data, economic data and industry data.
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Automated monitoring of data sources and key events to identify recent developments. The platform gave users the ability to update data in the models at the click of a button.
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One-click data export facility to download the analysis into Excel spreadsheets.
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APIs for integrating the dashboard with the client's internal tools.
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Automated alerts to enable timely intervention and decision-making.
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Easy setup of new companies through the application of standardized algorithms.
Impact
By using the AI-based dashboard, the client was able to
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Reduce the time for analysis by nearly 60%, enabling faster decision-making.
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Expand data sources by 150%, allowing for comprehensive and differentiated analysis.
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Access real-time data on a continuous basis.
Automating data collection and aggregation and consolidating it on a centralized platform led to significant reduction in manual effort. Analyst bandwidth that was previously used for manual, time-consuming work was diverted to more analytical work and client-servicing activities.
