@inProceedings{
 title = {Cell Phone Based Microcredit Risk Assessment using Fuzzy Clustering},
 type = {inProceedings},
 year = {2006},
 identifiers = {[object Object]},
 pages = {233-242},
 websites = {http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=4085537},
 month = {5},
 publisher = {IEEE},
 city = {Berkeley, CA},
 id = {80fccad5-804e-3ef6-8e3f-3b595a95020f},
 created = {2011-01-22T16:11:59.000Z},
 accessed = {2011-01-23},
 file_attached = {true},
 profile_id = {6f7bea39-60a4-30c0-9f16-3f628e0125c1},
 group_id = {4f826467-3c93-312b-9254-7cacd890372b},
 last_modified = {2014-08-26T12:08:40.000Z},
 tags = {m4d},
 read = {true},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 citation_key = {Sathe2006},
 source_type = {Conference Proceedings},
 abstract = {One of the key issue in microfinance is credit risk assessment. In this paper, exploiting fuzzy symbolic clustering, we have developed a fast turn around time microcredit risk scoring system. From field studies we identified a large number of parameters for credit risk assessment; most of them were subjective and thus our preference for fuzzy symbolic approach. We have proposed two cell phone based models to execute the developed microcredit risk assessment scheme. Experimental results are presented to validate our approach},
 bibtype = {inProceedings},
 author = {Sathe, Saket K and Desai, Uday B},
 booktitle = {2006 International Conference on Information and Communication Technologies and Development}
}

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