Big Data in Financial Services Industry: Market Trends, Challenges, and Prospects 2013 – 2018
Big Data is making a big impact already in certain industries such as the healthcare, industrial, and retail sectors. With the exception of the government sector, no other industry has more to gain from leveraging Big Data than the financial services sector. Big Data technology will help financial institutions maximize the value of data and gain competitive advantage, minimize costs, convert challenges to opportunities, and minimize risk in real-time.
Big Data technologies provide financial services firms with the capability to capture and analyze data, build predictive models, back-test and simulate scenarios. Through iteration, firms will determine the most important variables and also key predictive models.
There is a huge opportunity for financial services firms to apply new data sets and new algorithms to optimize capital allocation, cash management, and currency processing. The financial implications are manifest in improved capital flows and profitability for many firms within the ecosystem.
This report evaluates Big Data prospects and opportunities within the financial services sector and answers the following key questions:
- How is Big Data expected to impact the financial services industry?
- What are the Big Data players financial management solutions and their impact?
- What are the Big Data financial management models and how are they applied?
- What are the near-term and long-term benefits to the financial services industry?
- What are the specific challenges that the financial services industry faces with Big Data?
The report also analyzes Big Data prospects for financial services within the emerging markets including Brazil, China, and India.
- Big Data companies
- Telecom service providers
- Financial services companies
- Data services and analytics companies
- Cloud and telecom infrastructure providers
Companies in Report:
- 10GEN 65
- BOOZ ALLEN HAMILTON
- CISCO SYSTEMS
- MU SIGMA
- OPERA SOLUTIONS
- TIBCO SOFTWARE
Mind Commerce Publishing's research methodology encompasses input from a wide variety of sources.
We rely heavily upon our Subject Matter Experts (SME) in terms of their market knowledge, unique perspective, and vision. We utilize SME industry contacts as well as previous customers and participants in our market surveys and interactive interviews.
In addition, we rely upon our extensive internal database, which contains modeling, qualitative analysis, and quantitative data. We review secondary sources and compare to our primary sources to update previous findings (for prior version reports) and/or compile baseline information for technology and market modeling.
We share preliminary models with industry contacts (select previous clients, experts, and thought leaders) to verify the veracity of initial modeling. Prior to final report production (analysis, findings, and conclusions), we engage in an internal review with internal SMEs as well as cross-expertise, senior staff members to challenge results.
We believe that forecasts should be prepared as part of an integrated process which involves both quantitative as well as qualitative factors. We follow the following 3-step process for forecasting.
Step 1 - Forecasts Input:
The inputs for the present and historical revenues are derived from industry players. Financial and other quantitative data for individual sub-market categories are derived from original research and tested with interviews with major industry constituents.
Step 2 - Forecasting of Future Years:
Mind Commerce extends forecasts based on a variety of factors including demand drivers as well as supply side data. Key success factors and assumptions are considered.
Step 3 - Validation of Data:
The final step is to validate projections, which is accomplished in consultation with both internal and external industry experts, including both topic and regional experts. Adjustments are made to the forecasts based on factors identified throughout this process.