by retailers of all kinds to gather transaction data . Retailer loyalty cards can provide important insights into consumers ’ income and even family structure ( for example , buying diapers or school supplies is a good indication of children at home ).
Governments are developing improved identification and tracking systems for their citizens , to improve delivery of government services , among other things .
Leverage on this , click and conversion data based on various levels of engagements helps identify opportunities to map out customers based on how frequently and recently they interact with your brands .
There is the risk of validating the metadata from the phones using robust tools and skills . For example , an organization that wants to use data gathered from mobile operators , grocery stores , and utilities will probably need to have expertise in each of these sectors to determine which data are meaningful , what level of detail is optimal , and what combinations of data are most effective . There are chances that the
‘‘ Prepaid-minute purchase patterns can indicate a steady or uneven cash flow , and the timing and frequency of calls and text messages can indicate whether someone is working in a steady job .’’
organization might not have that skill .
That poses difficulties for risk modelers . While some new technologies are throwing off reams of data , others are allowing us to collect , aggregate , and analyze them in ways never before possible . There are new data standards and protocols , and new tools to bring together disparate data sets , matching and comparing them to generate insights .
Many practitioners are not yet skilled in these and are unfamiliar with aggregating diverse and oblique data to derive meaningful insights .
Gaining access to data can be difficult as well . In many cases , the data sets that lenders want is owned by entities ( telecommunications companies , utilities , or retailers , for instance ) that may not want - or are not allowed - to share them .
They may be dis-inclined to take the risk of offending their customers by sharing the information , and they may not have an immediate incentive to find ways to share it , even with their customers ’ consent . Regulatory requirements and privacy laws may prohibit lenders from gaining access to certain types of information . Governments are likely to be particularly cautious about sharing identity and other information that they collect about citizens .
Timothy Oriedo is a Certified Big Data Scientist ( MIT ), Certified Business Coach ( ICF ), Lead , Group Digital and Partnerships at Royal Media Services , a CIM Instructor Digital Marketing , and Adjunct Business Coach at Strathmore Business School . You can indulge him on this or related matters via mail at : Timoriedo @ gmail . com .