As the fuel that powers business, data is a highly prized commodity, with the need for access and control driving a wave of M&A activity among financial data providers. This vital information however is useless without proper implementation. Firms need effective data analytics in the investment banking industry in order to make informed decisions.
The Growth of Big Data in Investment Banking
Data is a topic that has remained in the spotlight throughout the year. It’s one reason why we’ve seen IHS Markit in the news around several developments, including S&P Global’s recent purchase of the data giant for $44bn. This follows IHS Markit’s own acquisition of Ipreo in 2018.
Separately, although the London Stock Exchange Group’s purchase of data provider Refinitiv isn’t a done deal yet, it is prepared to spend $27bn. LSEG expects to triple its revenues and gain a huge competitive boost in areas that require large volumes of (expensive) market data, such as ESG and other areas of the automated trading landscape.
Incorrect Use of Big Data in Investment Banking
These unions have created powerhouses that control rapidly expanding, high quality datasets. But is bigger always better for end-users? Not necessarily. Size can be an impediment to innovation, as large conglomerates often lack the ability to act as quickly or nimbly as fintechs. The exclusive focus on the data itself, rather than effective data analytics in investment banking and capital markets, means that many end-users are missing out on crucial insights.
The banking and capital markets industries are especially susceptible to inefficient usage of data. Here, users may find themselves with access to premium data from a leading provider, but one that lacks the commercial incentive to develop the tools needed to tap its full potential.
The Importance of Effective Analytical Tools
Using powerful data to feed a mediocre CRM is somewhat analogous to putting Formula 1 gasoline into a kid’s go-kart. It costs a lot but the desired results will be limited because the necessary pieces are not in place. Similarly, if the firm’s CRM is unable to provide a 360-degree aggregated view of client relationship data with proprietary methodologies applied and lacks the flexibility to adapt to shifting client needs and regulatory developments, then it is not delivering the greatest potential value from that premium data. Ultimately, this is limiting the firm’s ability to effectively and efficiently service clients to the extent that a competing firm utilizing proper data analytics in investment banking and capital markets, is able to.
Taking this further, consider the recent news that JP Morgan will be integrating IHS Markit’s macroeconomic data into its DataQuery platform. This development comes one month after JP Morgan added RepRisk’s ESG risk data from more than 150,000 companies to the same platform. Both moves align with two of the most important structural developments in capital markets this year – an increasing appetite for better, more comprehensive data and an expanded focus on the ESG sector.
If any institution does not have the capabilities to capture and organize these immense data sets, we’ve essentially embarked on a fruitless pursuit. However, the right fintech vendor can add value by providing unique capabilities that complement and optimize the data, not hinder it. Consider a specialized, experienced fintech provider that has anticipated the evolution of big data and invested in forward thinking strategies to prepare smart systems and analytics. Such a provider would be best positioned to consume, process and triangulate data to surface powerful insights in a timely manner.
Data Analytics in Investment Banking
Let’s apply this to investment banking. This is an area that can benefit from more effectively connecting multiple data points – market data, transaction data, research, company data, client data, etc. – to power analysis, streamline workflow and drive better decisions. For investment banking, having comprehensive data working harmoniously with a high-performance CRM that is designed to capture, process and analyze any data source will deliver valuable insights that help generate a quantifiable return.
Finding the right expertise, and frankly the bandwidth, to make this happen with internal resources is usually the biggest hurdle. But it is possible to achieve this, cost-effectively and quickly. This is where fintech providers with investment banking, big data and CRM specialization have a key role to play.
Effective CRMs for Investment Banking and Capital Markets
At Tier1 Financial Solutions, we offer industry specific CRM capabilities for investment banking, investment management and equity research sales and trading professionals. Data analytics in investment banking and capital markets can only be as effective as the tools you implement. Efficiently and effectively organize and utilize data with our CRM and workflow solutions optimized for your firm, to ensure you stay at the forefront of your industry.
Contact us to learn more about Tier1’s client relationship management and workflow solutions for capital markets and investment banking, or to request a Tier1 demo.