Banking

The most common problem in data monetization is data quality, consistency, accuracy, complexity and the right timing – i.e. the need for data to be available for analysis in the shortest time possible from the moment they are created. Data warehouse provides the basis for quality analysis of available data by deriving accurate information from data. In recent years, banks have accumulated large amounts of data from business and now it is time to turn data into money. Such great amount of data provides a big opportunity for analysis.

Data Warehouse Model for Banking

Benefits

Poslovna Inteligencija Banking Data Warehouse Model (PI Banking Data Warehouse Model) is business oriented, designed to support different business needs from regulatory and daily/weekly/decade/monthly operational and management reporting to very complex ad hoc analysis  and simulations:

  • Based on industry standards and implementation best practices,
  • Proven in real implementation projects,
  • Step by step deployment offers banks a choice to implement fully functional modules (“departmental data marts”) adjusted to their needs,
  • Enables business users to generate quickly actionable insights and easily customize or extend DWH capabilities,
  • Minimizes development costs,
  • Reduces the risk of failure by facilitating an incremental approach to delivering integrated data warehouse solution,
  • Fosters collaboration and approval between business and IT, as necessary, to turn business requirements into actionable solutions,
  • Provides a solid basis for regulatory reporting as well as decision support and executive KPIs.

New version and model updates are released on regular basis.

 

Business Areas

PI Banking Data Warehouse Model consists of eight Business Areas that form the foundation for Business Solutions.

Product Business Area

  • Contains product catalog and defines financial and non-financial goods and services.
  • Designed to support past, active, and future products and services with possibility to join it into bundles.

Party Business Area

  • Contains all information about the Bank itself, their customers, partners, employees, competitors, or any other individual or legal entity that has any sort of relation with the Bank (guarantor, rating company, insurance company, etc.).
  • Relations noted are not only contractual relationships, but also relations resulting from contacts through marketing activities, promotions, socially useful activities, contests, etc.
  • There are 3 basic Party Types: Individual, Legal Entity and Organization Unit, and 5 subareas: Organization, Individual, Legal Entity, Customer, and Human Resource.

 

 

Account Business Area

  • Contains information on various accounts: customer, internal, subsidized, nostro, loro, competitors etc.
  • Supports different relations between contract/annex and account, including product(s) and all account conditions, such as fees and interest rates.
  • Offers history of all changes during the account lifecycle, payment plan information, relations between different accounts and relations between accounts and security items
  • Includes definitions of rate and exchange rate list.
  • Keeps track of securities and credit protection on loans including collaterals, credit derivatives and guarantees.

 

Account Business Area describing bank’s accounts, their conditions and relations among them.

Transaction Business Area

  • The most complex part of the model that supports all types of transactions, financial or non-financial.
  • Also includes information about channels used to generate or settle the transaction
  • Provides a detailed view of transactions and various postings of the transaction amounts into general ledger.
  • Capable of monitoring mobile payments as well as payments that will be enabled through PSD2 directive.
  • Important for the analysis of the potential of specific locations for opening new branches or set up new ATMs.

GDPR AREA

  • Includes records of personal identifiable information, their mappings to various source systems and their categorization.
  • Holds the information about all the consents given and their relationship to consent donors which allows for transparent GDPR compliance.

Other Financial and HR Area

  • OPEX and OPEX subject areas provide information about cost centers and various distributions of costs per organizational units.
  • HR subject area allows to perform headcount analysis, workforce composition or prepare data for employee performance reviews.

Contact Center and Loyalty Area

  • Contains entities needed to capture the interaction between customers and contact center personnel as well as to keep track of case statuses and resolutions.
  • Loyalty Program subject area holds information of rewards and loyalty points given and spent.

General Area

  • Encloses references tables like Time dimensions, different Segmentation dimensions, Classification dimensions, information about source systems and past/running/future projects.
  • Describes physical and logical locations about which the Bank stores information (street and web addresses, phone numbers, business regions, etc.).
  • Includes resource items that are owned or used by the Bank in terms of capital or business.

Data Mart Solutions

Predefined structures for purposes of reporting and advanced analytics, applicable for every bank, but also open for changes and additional customizations. List of  available Data Mart solutions:

INTELLECTUAL PROPERTY

PI Banking Data Warehouse Model is an exclusive intellectual property of Poslovna inteligencija. PI grants a nontransferable and nonexclusive right to use the PI Banking Data Warehouse Model, with delivered customizations and extensions to its Customers who purchased the model.


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