“Credit unions are smaller than major banks and do not have the same quantity of data that banks are collecting from their customers. Data pooling seems to be the major key in this problem...”.
There are five reasons the credit union must be involved in data pooling: 1) Access to diverse data: data diversity is healthy for pooling and Advanced Analytics (AA). It is important to use the pool to maximum advantage to learn aspects that are in common, like economic sensitivities and to calibrate to the individual, so you get the benefit of the whole, especially to the individual institution. 2) Affordable access to data scientists: data scientists are expensive resources and having an important role in creating and analyzing predictive insights from raw data. If a data scientist works on a pool data, including 50 credit unions, those unions get to split the cost of the data scientist, making AA more affordable. 3) Encrypted and secure: the data in the pool is still anonymized. After the data reenters the firewall again, however, is it de-encrypted using a de-encryption key that only the credit union holds. 4) Quantity of data for Predictive Analytics: 95% of the credit unions in the United States are below $3.0 billion in Assets and do not have the appropriate amount of data to build accurate predictive models. Data pooling enables to analyze a larger data set. More credit unions help to decrease your margin for error and allow you to have more confidence in your data-driven decision making for the future. 5) Near real time industry data for peer to peer analysis: credit unions have as an ideal mode to perform peer to peer analysis, comparing data captured in 5300 Call Reports. It would be beneficial for credit unions to have access to this data before it is 4-5 months old. Data pooling provides access to industry data and analyzes data that is updated daily.