Recently, in my native state of Minnesota, a winter storm warning caused people to panic. Many people rushed to their local retailer for common household goods like fuel and food. They needed to store up different essentials in case they got stuck in their homes. It is amazing to see how people prepare when they know there is a storm brewing. Credit unions, similarly, are on the verge of a storm. Regulations and lending clubs are the main threats. Lending clubs are using data to steal members from credit unions while regulations are requiring more detailed (and forward looking) reporting. Lending clubs continue to take market share from credit unions without any physical branches. At the same time, the Financial Accounting Standards Board (FASB) has recently introduced a new regulation for calculating ALLL (Allowance for loan and lease losses), current Expected Credit Loss (CECL), and will require credit unions to account for the expected credit losses over the life of every loan. Credit unions must begin building their data reserves to support future decisions needed to serve their members. In order to comply with regulations and implement predictive analytics to stave off competition, credit unions must build a large data reserve.Analytic Data ModelIn order to prepare for regulations and defeat lending club competition, credit unions must begin storing their data. Deciding how to store data is a crucial strategic decision many credit union leaders are overlooking. Simply storing data in an archive is not enough. Data must be effectively integrated across systems to make sense of it at the organizational level. Executives do not want to know what data is in a loan origination system or a CRM database. They want to know what happened across the business over a period of time. Building an analytic data model (ADM) that syncs the business with its data is essential in preparing the data reserve. continue reading » 8SHARESShareShareSharePrintMailGooglePinterestDiggRedditStumbleuponDeliciousBufferTumblr
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