Tiwari, Tanu, Srivastava, Alpana and Kumar, Surendra
Measuring financial inclusion and digital banking: A study in context of suitability of normalized weighted score - Bihar Journal of Public Administration - 16(1), Jan-Jun, 2019: p.93-104
Financial Inclusion (FI) programs across the globe target to bring everyone under mainstream of banking and finance. Regulatory bodies periodically report the extent of performance in terms of financial inclusion index. These agencies consider only one or two key attributes in their reports and miss the impact of other financial parameters. Also, measures from two different agenciesare not comparable. This study aims to propose a simple weighted scoring method over four key financial services to obtain a robust measure of FI. Weights are obtained from the data itself using relative frequency approach and normalized to range between zero and one. Results shows that 60% are fully or partially under FI, among which only 10.71% are fully included. The result also portray that 21.27% are completely excluded. The findings of this study could be used by policymakers to estimate FI at individual level and prioritizing the policies. Using data driven weights the scores could be compared from two different measures. Further, the method and findings could be extended to logit and classification methods such as C4.5 or CART for one to one scoring as well as segmentation for further study.- Reproduced
http://www.iipabiharbranch.org/upload/Complete%20BJPA%20Vol%20XVI%20No.%201%20-%202019.pdf
Financial inclusion, Weighted-score, CD-ratio, Digital-India, DFI, Measure, Index.
Measuring financial inclusion and digital banking: A study in context of suitability of normalized weighted score - Bihar Journal of Public Administration - 16(1), Jan-Jun, 2019: p.93-104
Financial Inclusion (FI) programs across the globe target to bring everyone under mainstream of banking and finance. Regulatory bodies periodically report the extent of performance in terms of financial inclusion index. These agencies consider only one or two key attributes in their reports and miss the impact of other financial parameters. Also, measures from two different agenciesare not comparable. This study aims to propose a simple weighted scoring method over four key financial services to obtain a robust measure of FI. Weights are obtained from the data itself using relative frequency approach and normalized to range between zero and one. Results shows that 60% are fully or partially under FI, among which only 10.71% are fully included. The result also portray that 21.27% are completely excluded. The findings of this study could be used by policymakers to estimate FI at individual level and prioritizing the policies. Using data driven weights the scores could be compared from two different measures. Further, the method and findings could be extended to logit and classification methods such as C4.5 or CART for one to one scoring as well as segmentation for further study.- Reproduced
http://www.iipabiharbranch.org/upload/Complete%20BJPA%20Vol%20XVI%20No.%201%20-%202019.pdf
Financial inclusion, Weighted-score, CD-ratio, Digital-India, DFI, Measure, Index.