On setting up a data governance program, one of the most important stages is to determine the data domains for each line of business. Usually the customer data domain is the top priority.
The identification of a data domain starts with a business need or problem, the most frequent can be, increasing up-selling or cross-selling, improving customer experience, regulatory obligations, etc.
Once the customer data domain is selected, we’re faced with the fact that this domain touches dozens or even hundreds of systems and applications, business processes, data elements.
The risk of creating an unmanageable scope, leaves no other option the to identify what’s in fact critical to business.
Customer domain critical data elements for banks
The challenge is to understand what is in fact critical in a moment of enormous challenges with digital transformation processes, major disruptions on the industry, and a shift on the objectives of obtaining customer data.
No longer limited to the information needed for loans or deposits, customer information is being used to get predictive insights about risk, customer profitability or marketing.
The list below, a although not complete, contains the information that is vital to drive the most important decisions for long term commercial customer relationship management, profitability, credit risk or AML risk.
· Personal Information — Title, first name, last name, date of birth, gender.
· Location information — postal address, geo-location.
· Telephone Information — Home, work, mobile number.
· Email Address Information — Personal, work email address
· Social Network Information — Facebook identifier, Twitter address, Linkedin identifier.
· Account Information — Details of account ids or user ids.
· Job Information — Company name, department, job title
· Industry — Allowing to monitor the industry to better manage the relationship.
· Profitability/Products — Aggregation of the customers products and services.
· AML Ranking
· House-holding (related parties) — Other entities associated with the customer, such as relatives, affiliates, subsidiaries or parent companies
· Financial — Level and changes in revenue, operating margins, net income, inventory levels and salaries
All this data exists, although scattered across numerous data silos across the organization, sometimes with contradicting versions.
This is the moment where a master data management solution should be considered as one of the outcomes of the data governance process, enabling customer data being used to drive new business opportunities, identifying, consolidating and linking customer data across the organization. Consolidating all the siloed information and producing a single, 360-degree view of the customer.