under the traditional model and accepted based on their EFL score and entrepreneurs accepted under the traditional model).

**Table 4. Testing Hypothesis 2: Credit to New Borrowers**

||Banked+|Unbanked|Ban|ked|Unba|nked|
|---|---|---|---|---|---|---|
||(1)<br>TM<br>Accepted|(2)<br>Diff §|(3)<br>TM<br>Accepted|(4)<br>Diff §|(5)<br>TM<br>Accepted|(6)<br>Diff §|
|Classification worse than "Normal" at SBS (12 months after app.)|0.295***|0.311***|0.293***|0.323***|0.305***|0.140|
||(0.013)|(0.042)|(0.013)|(0.044)|(0.036)|(0.170)|
|More than 90 days in arrears at SBS (12 months after app.)|0.145***|0.161***|0.147***|0.171***|0.130***|‐0.005|
||(0.010)|(0.043)|(0.011)|(0.045)|(0.028)|(0.121)|
|More than 90 days in arrears at SBS (during next 12 months following app.)|0.194***|0.221***|0.193***|0.244***|0.202***|‐0.036|
||(0.011)|(0.041)|(0.012)|(0.043)|(0.030)|(0.112)|
|Number of days in arrears (6 months after app.)|16.711***|44.742***|16.596***|46.828***|17.482***|23.435|
||(1.073)|(9.061)|(1.153)|(9.754)|(2.947)|(18.646)|
|Number of days in arrears (12 months after app.)|31.892***|59.108***|32.690***|62.909***|26.640***|4.582|
||(1.914)|(12.627)|(2.093)|(13.476)|(4.578)|(13.510)|
|Increase in debt at SBS (1 month after test wrt 1 month before app.)|0.501***|‐0.020|0.544***|‐0.079*|0.358***|0.267**|
||(0.013)|(0.042)|(0.015)|(0.044)|(0.026)|(0.124)|
|Increase in debt at SBS (6 month after test wrt 1 month before app.)|0.579***|‐0.060|0.620***|‐0.120***|0.440***|0.247**|
||(0.013)|(0.042)|(0.014)|(0.044)|(0.027)|(0.119)|
|Classification at SBS (12 months after app.)|0.885***|0.090***|0.999***|0.001|0.506***|0.244**|
||(0.008)|(0.015)|(0.001)|(0.001)|(0.027)|(0.112)|
|Loan from implementing institution|0.268***|‐0.021|0.280***|‐0.055|0.227***|0.210*|
||(0.011)|(0.036)|(0.013)|(0.037)|(0.022)|(0.126)|
|Number of observations|16|77|13|09|36|8|

Note: § Difference between entrepreneurs rejected under the traditional model and accepted based on the EFL score and entrepreneurs accepted under the traditional model. Ordinary least squares estimates. Outcome variables are for loans from all formal financial institutions, i.e., not limited to the implementing institution unless stated otherwise. Robust standard errors in parentheses: * p<0.1, ** p<0.05, ***p<0.01.

Table 4 shows evidence against hypothesis 2 (column 2). In fact, entrepreneurs rejected under the traditional model and accepted based on their EFL score exhibited worse loan repayment behavior than those accepted under the traditional method. These results seem to be driven by banked entrepreneurs, and suggest that the traditional screening method—which, for banked entrepreneurs, incorporates valuable information about their past repayment behavior—is a powerful tool to screen out high-risk applicants (column 4).

The differences in the loan repayment behavior patterns of unbanked entrepreneurs are smaller and not statistically different from zero (column 6). Moreover, the size of the coefficients is small compared to the coefficients for banked entrepreneurs. Our results thus suggest that the EFL tool can be used to offer loans to unbanked applicants who are rejected under the traditional method without increasing the risk of the loan portfolio. However, this finding does not hold for 17