To compete in today’s market, retail banks are moving from a line of business view of customers to a 360-degree view, where data integration, quality, and accessibility are pivotal.

In an increasingly competitive retail banking market, new customer acquisition and customer retention are key to growth and success. Whether bricks & mortar or direct, firms are striving to improve the experience of today’s connected customer by developing a 360-degree view of their clients.

To achieve this comprehensive view, information concerning all a customer’s products needs to be collected and linked in a business data warehouse and master data hub covering:

  • checking and saving accounts
  • credit cards
  • mortgages
  • IRAs and retirement accounts
  • Investments

Historically, retail banks were organized around separate lines of business making the achievement of this holistic view of a customer very difficult. Extraction, alignment and analysis of relevant information was made difficult through the long lead times to build a data warehouse and the slow processing supported by traditional extract, transform and load tools.

At the core of a customer centric bank is a centrally available, business data warehouse and master data hub containing information about customers and the products and services they use. This customer profile is built up based on multiple sources; past history across multiple products and accounts need to be extracted, cleansed and aligned to new customer centric business processes. The addition of external, third party data can be used to enrich a bank’s understanding and modeling of its customers’ behavior. At the aggregate, demographic and economic data can be employed to model changes in behavior based on events and trends.

As a result of building a comprehensive profile of customers and the products and services they use, banks will be able to better execute against:

  • Understanding Customer Profitability
  • Appropriate up-sell and cross product targeting and promotion
  • Predicting customer behavior based on analytic models and profiling
  • Local demand for branches, sub-branches and ATMs
  • Identification of underperforming products, branches or services
  • Detecting fraud identity theft and ensuring customer security

How Magnitude helps

  • Magnitude’s unique business model driven approach to automating the data warehouse results in an industry leading time-to-value as more effort goes into defining the business requirements of achieving a 360-degree view and less into the technical effort of building and maintaining the data warehouse
  • Visual and business-centric design tools enable banks to get their integrated data warehouse up and running with smaller teams and lower cost
  • Support identification of inefficiencies and cost saving opportunities
  • Offers an agile technology and approach to accelerate project delivery time to meet business needs faster
  • Avoid high risk “rip and replace” strategies, using the Magnitude Dynamic Information Warehouse (DIW) to incrementally integrate, manage and load transactional and operational data from disparate silo and legacy systems into your data warehouse.
  • Enrich data from new and third party sources for predictive analytics while maintaining quality and governance with Magnitude Master Data Management
  • Transform transactional and operational data to support reporting, analytics and dashboard reporting with synchronized business and analytic views supporting market leading Business Intelligence and analytic tools.
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