Business Intelligence in Financial Services By Naveen Perla, National Head, Satco Capital Markets

Business Intelligence in Financial Services

Naveen Perla, National Head, Satco Capital Markets | Wednesday, 08 March 2017, 06:39 IST

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It's important for companies to use data to create sound budgets and complete accurate reports in order to make better decisions. Nowhere is that more paramount than in the financial services industry, which has fallen under heavy scrutiny over the past couple of years.

A 2015 paper predicted these developments in the business intelligence market. Because of lack of information, processes, and tools, throughout 2015, more than 35 percent of the top 5,000 global companies regularly fail to make insightful decisions about significant changes in their business and markets. BI has a huge scope in Entrepreneurship, however majority of new entrepreneurs ignore its potential.

In today’s fast-paced business world, it is imperative to have the insight and data in order to make the right calls at the right time. Business Intelligence is the key to making those correct decisions, as it joins data, technology, analytics, and knowledge to help businesses make optimal decisions that drive their enterprise’s success.

Typically, BI also includes an enterprise data warehouse and a BI platform or tool set to aid those executives in transforming the data into actionable information.

But, there is also an element to Business Intelligence that is not solely found in technology on a computer: “the human element”. Business Intelligence experts, consultants, and insiders have the knowledge it takes to turn the data into results.

In the 1970s, Pershing LLC was on the cutting-edge of IT when it started providing clients with electronic reports instead of paper-based consumer data reports. Nearly 30 years later, however, it was still using the same dry, row-based reports and its customer data-related BI capabilities were stuck in a decade long gone by — i.e., no ad hoc querying or interactive dashboards.

Pershing was looking for more flexible ways to look at their customers and behavior. So in 2002, they sent out an RFP for a BI product that could integrate with its financial trading platform to allow clients to manipulate customer data and conduct advanced analysis.

The implementation provided Pershing's clients with access to customers' account data as structured, ad hoc reports with tabular results, interactive dashboards and scorecards. It also allowed clients to do all their analysis from a single portal without the need of help from Pershing's staff or IT.

The most important factors that financial companies need to consider for a successful application are data design, quality of data and data interpretation.

Functions of BI

BI technologies provide historical, current and predictive views of business operations. Common functions of business intelligence technologies are reporting, online analytical processing, analytics, data mining, process mining, complex event processing, business performance management, bench marking, text mining, predictive analytics, and prescriptive analytics.

Uses of BI

BI can be used to support a wide range of business decisions ranging from operational to strategic. BI can be also used as an effective tool in entrepreneurial ventures.

Basic operating decisions include product positioning or pricing. Strategic business decisions include priorities, goals and directions at the broadest level. In all cases, BI is most effective when it combines data derived from the market in which a company operates (external data) with data from company’s sources to business data such as financial and operations data (internal data). When we combine external and internal data, they provide a more complete picture which creates an "intelligence" that cannot be derived by any singular set of data.

Amongst myriad uses, BI tools empower organizations to gain insight into new markets, assess demand and suitability of products and services for different market segments and gauge the impact of marketing efforts.

Conclusion

Without proper data, or with too little quality data, any BI implementation fails; it does not matter how good the management sponsorship or business-driven motivation is. Before implementation it is a good idea to do data profiling. This analysis identifies the “content, consistency and structure” of the data. This should be done as early as possible in the process and if the analysis shows that data is lacking then put the project on hold while the IT department figures out how to properly collect data.

When planning for business data and business intelligence requirements, it is always advisable to consider specific scenarios that apply to a particular organization, and then select the business intelligence features best suited to the scenario. 

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