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Conclusions

Our work has been exploratory, seeking to understand how CDFI banks performed over the past decade and the extent to which publicly available data can assist in measuring its performance. Based on the same logic underlying the lending test and service test undertaken as part of a CRA examination, we propose that DLI and DDI can be useful SPMs because they standardize comparison of a bank's underlying business model.

We have plumbed the limits of readily available public data. The SOD provides a useful profile of the location of deposit-taking operations of all banks, which can be summarized in the DDI measure proposed here. On the lending side, for banks focused on home lending, HMDA remains a very useful source of data, which may be used to calculate the DLI (HMDA) measure reported here. However, for those banks not focused on housing (and even for those that are but undertake substantial other development lending activities), the available public data are not adequate to develop benchmarks.

We have also demonstrated the possible use of these measures: creating consistent, relevant categories using these new measures in order to more fairly compare financial return measured by ROA across a broader category of institutions. While publicly available data do not allow for the calculation of SPMs per se, they can enable more meaningful comparison of financial measures across different types of banking institutions as we have demonstrated. These measures also help to track the focus of a bank's service model over time – highlighting whether it is becoming more or less development focused on these tems in a way that would invite further investigation.

Our findings suggest that the DLI and DDI measures are useful SPMs warranting further exploration. First, it is essential to fill out the DLI measure to include other categories of lending than those available from HMDA alone. CRA examination reports provide some data for each institution, although these are published on a three-year cycle publicly available in a pdf format and have to be accessed for each lender. Nonetheless, there is more relevant public data to be accessed, although the method of access is time consuming. However, the potential value of the DLI measure suggests that such effort may be worthwhile for CDFI banks at least. If these data cannot be accessed, then the alternative is to consider the incentives and inducements for lenders to self-report it.

Second, even if limited to using the more restricted DLI (HMDA) measure, it would be worth applying the DLI and DDI criteria as screens to identify a possible wider universe of CDFI banks beyond the small number of banks that have presently chosen to apply for CDFI status. DDI and DLI thresholds can be applied as the first cut toward identifying those banks with the potential for higher social performance. Of course, further exploration would be necessary to establish definite potential in each case. However, even to make the first cut requires investment in the hardware and software capacity to manage substantial volumes of data.

Third, changes in DDI and DLI observed over time deserve closer investigation because we lack an empirically verified theory of how double bottom fine banks change over time. For example, do some banks move upmarket from necessity, opportunity, or even success in their development mission as depressed areas turn around and no longer qualify? Do others intentionally pursue high development intensity over time? In our opinion, it would be worth following up with banks that have shown increases or declines in DLI to determine the underlying factors for and results of these changes over time.

Note

David Porteous, Director, Bankable Frontier (bankableffontier.com), and Saurabh Narain, Chief Fund Advisor, National Community Investment Fund (NCIF) (ncif.org), would like to acknowledge the hard work of Corinne Bradley, Joe Schmidt, and Benecia Cousin and the advice from numerous others, including trustees of NCIF, George Surgeon, Ron Grzywinski, Mary Houghton, Ellen Seidman, Dan Immergluck, Malcolm Bush, Bob de Young, and Mike Berry. This chapter was commissioned by NCIF with the kind support of the F. B. Heron Foundation and the CDFI Fund. NCIF expects to use the methodology discussed in this chapter for creating a direct link between availability of more capital/fund- ing and community development outputs. Development Lending Intensity and Development Deposit Intensity are terms used by NCIF to measure social performance of community development banks.

 
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