When it comes to Big Data, the financial services sector has been somewhat slow on the uptake. Neil Palmer, partner of SunGard Consulting Services’ Advanced Technology Business, explains it as a cautious approach to innovation driven by the heavily regulated nature of the industry. But with data growth becoming a challenge and increasing pressure to bring down operational costs, Big Data is beginning to shape financial services too.
After all, business analytics are the key to excellence in Financial Services, notes Michael Versace, research director of worldwide risk and big data industry leader at IDC Financial Insights.
Here are 10 trends that SunGard’s Palmer says will shape Big Data initiatives across all segments of the financial services industry in 2012.
Larger Data Sets of Historical Data are Needed
Larger market data sets containing historical data over longer time periods and increased granularity are required to feed predictive models, forecasts and trading impacts throughout the day.
Firms Face New Regulatory and Compliance Requirements
New regulatory and compliance requirements are placing greater emphasis on governance and risk reporting, driving the need for deeper and more transparent analyses across global organizations.
Increased Focus on Enterprise Risk Management
Financial institutions are ramping up their enterprise risk management frameworks, which rely on master data management strategies to help improve enterprise transparency, auditability and executive oversight of risk.
Desire to Leverage More Consumer Data Across Multiple Delivery Channels
Financial services companies are looking to leverage large amounts of consumer data across multiple service delivery channels (branch, Web, mobile) to support new predictive analysis models in discovering consumer behavior patterns and increase conversion rates.
Investment in Data Infrastructure in Post-Emergent Markets
In post-emergent markets like Brazil, China and India, economic and business growth opportunities are outpacing Europe and America as significant investments are made in local and cloud-based data infrastructures.
Drive to Unlock the Value of Data in Operations Departments
Advances in big data storage and processing frameworks will help financial services firms unlock the value of data in their operations departments in order to help reduce the cost of doing business and discover new arbitrage opportunities.
Need to Re-engineer ETL to Accommodate Data Growth
Population of centralized data warehouse systems will require traditional ETL (Extract, Transform, Load) processes to be re-engineered with big data frameworks to handle growing volumes of information.
Adoption of Predictive Credit Risk Models
Predictive credit risk models that tap into large amounts of data consisting of historical payment behavior are being adopted in consumer and commercial collections practices to help prioritize collections activities by determining the propensity for delinquency or payment.
Mobile applications and internet-connected devices such as tablets and smartphone are creating greater pressure on the ability of technology infrastructures and networks to consume, index and integrate structured and unstructured data from a variety of sources.
Big Data is Driving Big Data
Big data initiatives are driving increased demand for algorithms to process data, as well as emphasizing challenges around data security and access control, and minimizing impact on existing systems.