Notes: The table presents the treatment effects on loans and transfers of eligible Dabi and Progoti borrowers. All regressions control for the baseline value of the outcome, an indicator variable for the endline survey and district strata fixed effects.

The regressions are ordinary least squares OLS regressions based on specification 4. Randomization inference p -values of the null hypothesis of no effect are provided in square brackets.

In column 2 , the dependent variable is the principal amount in USD PPP of the BRAC loan the respondent had at the mid-line or endline survey. Non-BRAC loan value is the monetary value in USD PPP of all formal and informal loans taken from other lenders banks, MFIs other than BRAC, informal money-lenders or relatives and friends during the past 12 months.

Net borrowing or transfers is the monetary value in USD PPP of net borrowing loans borrowed minus loans lent and net tranfers tranfers received minus transfers given combined. The rest of Table 2 explores other outcomes related to credit and transfers. Starting with Dabi , while the treatment decreased the likelihood of having a non-BRAC loan by 4 ppt [column 3 ], the impact on the intensive margin is small and imprecisely estimated [column 4 ], barring any definitive conclusions on substitution effects away from non-BRAC lenders toward BRAC.

Eligible Dabi borrowers also receive more informal transfers from their social networks with the point estimate similar in size to the effect on the BRAC loan , albeit insignificantly so [column 5 ]. Column 6 examines transfers and loans provided to the social network.

The last column presents the effect on an aggregate index that combines the 7 indicators related to the credit market outcomes of the Dabi clients. We find that the aggregate index is significantly higher by 0. By contrast, Panel B indicates that the impact on the eligible Progoti borrowers is insignificant [with the exception of one outcome: the likelihood of having a non-BRAC loan in column 3 ].

As the aggregate index in column 8 is indistinguishable from zero, we conclude that the treatment did not significantly affect the credit market outcomes of the eligible Progoti clients.

Next, we examine the impact of repayment flexibility on a range of business outcomes. The upper panel of Table 3 shows effects for the eligible Dabi clients, starting with business ownership in column 1.

In terms of inputs, the treated Dabi borrowers invest significantly more in their business assets but not in labour. We do not find any significant effect in terms of labour inputs number of workers, business operating hours, and hours worked by the business owner.

Column 6 shows that treatment raised revenues by 28, USD PPP annually relative to the control sample. Eligible clients also had higher costs which is likely related to the larger investments in their business capital e.

cost of purchasing tools, machines, or inventories. Column 10 shows that Dabi businesses in the treatment group had more volatile revenues. As a proxy for volatility, we use the range of monthly revenues. Finally, column 10 shows that the aggregate index is up by 0. Overall, these findings suggest that the flexible contract not only led to more business activity and greater business investments, but also increased the volatility of the monthly business revenues among the Dabi borrowers.

In particular, there are no significant effects on any of the business outcomes except for the number of workers, and the overall impact on the aggregate index in column 11 is close to zero and insignificant.

Notes: The table presents the treatment effects on business outcomes of eligible Dabi and Progoti borrowers. Data comes from the mid-line and endline surveys. The regressions are OLS regressions based on specification 4. Business owner is a dummy variable equal to one if the respondent owns a business.

Business assets is the monetary value in USD PPP of business assets tools, machinery, furniture, vehicle and inventories at the time of the survey. Number of workers is the number of workers other than household members who work in the business on a typical working day.

Business hours is the number of hours that the enterprise was in operation over the last 12 months. Revenues is the monetary value in USD PPP of sold products or delivered services of the business over the last 12 months. Costs is the monetary value in USD PPP of the total amount the enterprise spent on personnel expenses, machines, tools, equipment, space, transportation, electricity, fuel for machines, and total purchase of stock over the last 12 months.

Profits annual is profit in USD PPP of the business over the last 12 months. Profits month is profit in USD PPP of the business over the month preceding the survey.

Range of revenues is the difference between the level of revenues during the worst month in terms of sales and the level of revenues during the best month in terms of sales during the past year.

If the respondent reported that revenues did not fluctuate throughout the year, the range of revenues is set equal to zero. The third and final set of outcomes are related to the socio-economic status of the eligible borrowers. Given that land ownership is a key indicator of socio-economic status in rural Bangladesh, this is an important sign that the status of the eligible Dabi clients improved as a result of the intervention.

The aggregate index in column 6 also shows a significant increase of 0. In contrast to the Dabi borrowers, there are no significant effects on any of the outcomes nor on the aggregate index for the Progoti clients Panel B of Table 4. Notes: The table presents the treatment effects on indicators of household socio-economic status outcomes of eligible Dabi and Progoti borrowers.

All regressions control for the baseline value of the outcome, an indicator variable for the endline survey and district randomization strata fixed effects. Consumption per capita is the monetary value in USD PPP of the total household expenditure per capita in PPP USD over the last 12 months divided by the household size on consumption measures.

Size of land wwned is the amount in decimals of land owned by the household excluding the homestead. Figure 3 provides a visual summary of the treatment impact on the eligible clients.

It plots the ITT effects on standardized indicators related to the three families of outcomes we study credit market, business, and household economic status. All the Dabi -related outcomes shown in Figure 3 A , with the exception of non-BRAC loan value and per-capita consumption expenditure, are positively affected, with a majority of them being statistically significant.

In particular, we observe large effects on business revenues 0. Overall, we do not find evidence of a significant average impact on the outcomes of the Progoti clients.

ITT effects: A effects on Dabi borrowers and B effects on Progoti borrowers. The sample includes eligible Dabi borrowers in Panel A; and eligible Progoti clients in Panel B. Standard errors are clustered at the BRAC branch office level. A possible concern with the large treatment effects detected among the Dabi clients is whether the results are driven by some peculiarity of our context or the eligible sample itself.

To assess this, we compare our estimates to the treatment effects found in Field et al. Even though the product we examine is quite different, allowing borrowers to manage payments freely over the loan cycle in a state-contingent manner, Field et al.

This builds confidence in the external validity of our findings and suggests that the large treatment effects are not driven by some special feature of our context or sample.

In particular, we test if the repayment rates of the eligible clients and their demand for BRAC loans are affected by the introduction of the flexible loan contract. Table 5 reports the impact on client retention and default for the eligible borrowers. Column 1 shows that treated Dabi clients are 6.

The effect on Progoti borrowers is also negative but imprecisely estimated. We first present the official default classification used by BRAC [column 2 ] and then assess how repayments change depending on the time elapsed since the start of the contract [columns 3 and 4 ] or since the end of the loan cycle [columns 5 — 7 ].

Specifically, column 2 reports the effect on the official default rate defined as the likelihood of not having repaid the loan by the end of the loan cycle. In the treatment branches, they are 1. The corresponding impact is close to zero for the Progoti clients. Notes: The table presents the treatment effects on retention and loan repayment of eligible Dabi and Progoti borrowers.

Borrower no longer with BRAC is a dummy variable taking the value of one if the client has repaid the loan and not taken out a new one as opposed to having a current loan or having defaulted. Default is a dummy variable taking the value of one if the borrower was categorized by the credit officer as not having repaid the loan by the end of the loan cycle.

Loan not fully paid in 12 months is a dummy variable taking the value of one if the borrower does not repay the full loan by the end of the loan cycle 12 months.

Loan not fully paid by the end of the loan cycle is a dummy variable taking the value of one if the borrower does not repay the full loan within the 14th month in the treatment branches and by the 12th month in the control branches. Full loan not repaid within 2 6 [12] months after the end of the loan cycle are dummy variables taking the value of one if the borrower did not repay the full loan by the second sixth [twelfth] month after the end of the loan cycle.

For eligible clients in treatment branches, the end of the loan cycle is computed starting 2 months after the expected last collection date; in control branches from the expected last collection date see Supplementary Appendix B for further details.

Next, we examine the likelihood that the loan was not fully paid in 12 months to quantify the proportion of borrowers who extended the loan by using at least one voucher. Treated Dabi borrowers are 8. Similarly, we see a 5.

Column 4 investigates the actual end of the loan cycle, defined as 12 months in the control and 14 months in the treatment branches.

Hence, by the end of the contract, the de facto default rate was significantly lower in the treatment branches. The remaining columns report the effects on the probability of not having repaid the full loan within 2, 6, and 12 months [columns 5 , 6 , and 7 ] after the end of the loan cycle as defined in column 4.

Eligible Dabi clients are 1. While imprecisely estimated, the effect is similar in magnitude to the default indicator [column 2 ] used by BRAC. Overall, the patterns imply that the flexible contract improved repayment among the eligible clients in the treatment branches, at least in the short run, while loan repayment rates were more similar in the treatment and control groups in the longer term.

The results so far demonstrate that repayment flexibility led to improvements in business outcomes and socio-economic status without an increase in the default rates for the Dabi clients, with much more modest and insignificant effects for the Progoti borrowers.

Viewed through the lens of our model, these findings provide some initial evidence of the mechanisms at play. The relatively large impact experienced by the Dabi clients is consistent with increased risk taking because of imperfect insurance markets and, possibly, credit rationing.

By contrast, the absence of discernible effects for Progoti either implies that these firms were unconstrained or that they face too much risk even with the vouchers due to other external commitments. In the latter case, the model shows that the flexible contract induces safer low-return investments, again owing to imperfect insurance, binding credit constraints, or an incompleteness in both markets.

To shed light on the channels, we now test more directly for the presence of insurance and credit rationing. According to our theory, repayment flexibility should increase risk taking if insurance markets are imperfect and the loan payment is the main outstanding obligation.

To examine this link empirically, we explore four pieces of evidence. First, an implication of greater risk taking is that some firms will flourish while others, if unsuccessful, may fail.

The finding that treatment increases sales volatility [column 10 , Table 3 ] is supportive of this, at least for the sample of eligible Dabi clients. To probe the idea further, we study the heterogeneity of the treatment effects. Average treatment effects in terms of business growth and household economic wellbeing may mask considerable heterogeneity that can tell us something more about whether the flexible contract induces risk taking, resulting in success as well as failure.

To explore this, we estimate the following quantile treatment effect QTE specification:. where Δ y i t is the change in the outcome of interest for individual i at survey t mid- or endline relative to the baseline and the rest of the parameters are defined as in equation 4 above.

One caveat to bear in mind is that, due to the small sample size, we lack the power to estimate precise treatment effects across the distribution. Figure 4 displays the results for the eligible Dabi clients. The QTE estimates reveal substantial heterogeneity in the effects of the flexible contract.

While we observe a positive impact on business asset value at any centile above the median Figure 4 A , the treatment effect at the lowest centile is negative although insignificant. The pattern is even more striking when we study the QTEs on business revenues and household labour income Figure 4 B and C.

While most treated clients raise their revenue and household income, those at the lower end of the distribution do worse relative to the control group. As an alternative way of exploring the effects throughout the distribution, we also plot the cumulative distribution function CDF of log household income in Figure 4 D.

This is consistent with repayment flexibility leading to greater risk taking among treated clients, causing some households in the treatment group to lose out relative to control while others do better. By contrast, when we conduct the same analysis for the Progoti borrowers, we find no evidence of any heterogeneity.

Heterogeneity of treatment effects among Dabi borrowers: A business assets value; B business revenues annual ; C household income annual ; and D CDF of Log household income. Notes: The sample includes eligible Dabi borrowers.

Panels A—C plot QTEs estimated according to specification 5. Each specification controls for the survey wave. Values are in PPP USD.

Panel D plots the CDF of log household income plus 1 in the treatment and control samples. Second, we estimate the heterogeneity of the treatment effect with respect to the uncertainty of the local business environment.

As implied by the model, the flexible contract should facilitate riskier investments more exposed to aggregate uncertainty in the case insurance constraints bind.

As an indicator of business uncertainty, we rely on the baseline data from the SME sample. Using this information, we calculate the average coefficient of variation CV of expected demand growth among SME owners within a cluster BRAC branch office and divide the clusters into two groups: those where the average CV of expected demand growth is high above median or low below median at baseline.

If the flexible contract helps eligible borrowers undertake riskier investments, we expect the effects to be larger in clusters with greater demand uncertainty.

Table 6 shows that this is indeed the case among the Dabi borrowers. Moreover, the impact on profits seems to be concentrated among borrowers located in clusters with higher demand growth uncertainty the interaction terms in columns 4 and 5 are large and positive though somewhat imprecise. This implies that among the Dabi borrowers, repayment flexibility helped borrowers particularly in markets with high demand uncertainty at baseline.

Importantly, the corresponding analysis for the Progoti clients shows no detectable heterogeneity. Notes: The table presents the heterogeneity of the treatment effects on key business outcomes of the eligible Dabi borrowers with respect to uncertainty of demand growth at baseline among local businesses.

demand uncertainty. Third, in addition to expectations about future demand, the realization of actual shocks should be particularly important for borrowers who take on more risk.

To test this, we explore variation in local demand shocks caused by changes in agricultural productivity. In addition, Bangladesh is one of the most climate-vulnerable countries in the world, with droughts and heavy floods having a strong negative effect on rice yields and subsequent income Khandker, ; Bandyopadhyay and Skoufias, ; Rahman et al.

To capture sharp changes to rice productivity and thus to the local economy, we explore the occurrence of heavy floods during the growing season December to May of the most important rice variety, Boro.

To construct the shocks, we compute the rainfall distribution for a 25 km radius from the centroid of each branch separately over the period — A negative shock is proxied by a one standard deviation increase in rainfall within the 25 km buffer zone.

To match our mid- and endline survey, collected in May through August of and , we measure shocks in December to May in and in relative their historical distribution. Importantly, this implies that the extreme floods occur unexpectedly after the announcement of the flexible credit contract offer in September In Table 7 , we study the riskiness of the business activity by interacting the rain shock with the treatment indicator as well as adding an independent shock variable.

A negative coefficient on the interaction term implies that activities undertaken with access to vouchers were more sensitive to demand shocks as captured by the undesirable rainfall shock.

The effect of the shock itself should also be negative as it lowers overall demand. We have a negative and significant interaction term for business revenues, costs, and profits.

Specifically, the treatment effect on revenues is 38, USD PPP in the absence of the negative rainfall shock, while the impact is only 7, USD PPP and imprecisely estimated for borrowers exposed to the shock.

This is in line with the shock lowering sales in general. In treatment branches, the effect of the rainfall shock almost doubles. Similarly, the responsiveness is also sizable in terms of costs and profits.

A similar pattern is observed for monthly profits, but the interaction term of treatment with the rainfall shock is imprecisely estimated at conventional levels.

Notes: The table presents the heterogeneity of the treatment effects on key business outcomes of the eligible Dabi borrowers with respect to the likelihood of having experienced an excessive rainfall shock. The geographical area over which the rainfall amount was calculated corresponds to a 25 km radius around the branch where the firm is located.

All regressions control for the baseline value of the outcome, an indicator variable for the endline survey, district-by-survey year fixed effects, and flexible controls for the probability of rain.

Overall, the interaction effect with the negative rainfall shock entirely removes the positive impact of treatment on revenues, costs, and profits which in absence of floods is significantly greater among Dabi clients in the treatment group relative to control.

We also see a negative effect on the extensive margin, as fewer individuals are business owners in treated branches who experienced the negative rainfall realization.

Together, these findings imply that Dabi clients with access to the flexible contract shift their activities to take on more demand-related risk. Fourth, the theory is based on the idea that the flexible contract raises investments in illiquid and thus riskier business assets if the insurance market is incomplete.

We begin by breaking down this effect for the Dabi borrowers into 6 different categories: tools and utensils, furniture, machines, vehicles, inventories, and buildings.

While Panel A of Table 8 shows that treatment and control were as likely to own an asset within each group, Panel B reveals that the aggregate value increased across the majority of categories.

Specifically, treatment increased the ownership of tools and utensils by 73 USD PPP [column 1 ], furniture by 57 USD PPP [column 2 ], machinery by USD PPP [column 3 ], and inventories by 1, USD PPP [column 5 ].

The point estimates for vehicles and buildings are negative but imprecisely estimated. Notes: The table presents the treatment effects on business assets of the eligible Dabi borrowers.

Panel A reports estimates of the extensive margin likelihood of owning assets of each type , Panel B on the intensive margin monetary value of assets owned of each type.

In Panel C, the dependent variable is the number of distinct types of assets owned within each asset category, and in Panel D the outcome is the per unit value of assets of each type owned by the firm. In Figure 5 , we plot the percentage of the asset value that respondents reported they would lose in case of a rapid sale conditional on having a given type of asset.

While these findings need to be interpreted with some caution with data collected 5 years after the baseline survey and during the Covid pandemic , the evidence suggests that business assets in general are difficult to liquidate in this setting and, as such, investing in them entails substantial risk for small businesses.

Notes: The figure shows the liquidity of business assets owned by eligible borrowers Dabi or Progoti by category, and overall. The information comes from a phone survey that was conducted in May The figure plots the mean level for the percentage of value lost if a firm has to liquidate assets in 1 day as opposed to 1 month conditional on having any assets of a given type.

Returning to Table 8 , in Panel C we explore the variety of business assets held by the eligible Dabi clients by counting the number of different asset types within tools and utensils, furniture, machines, and vehicles. Finally, Panel D of Table 8 reports differences in terms of the unit value of the business assets held in each category.

To the extent that the wider variety of inputs captures increased experimentation with the production process Panel C and that these possibly less common inputs carry a higher unit price Panel D , it is a further indication of more risk taking.

While the results square well with the theoretical prediction that repayment flexibility induces risk taking, pointing to the presence of insurance rationing at least for the Dabi clients, they are open to interpretation for the Progoti borrowers.

The lack of increased risk taking among the larger firms either suggests that insurance constraints are less important to them or that too much risk remains because of other periodical external commitments, such as rent, utilities, transportation, and salaries.

To investigate this last point, we compare annual recurrent costs across the Progoti and Dabi firms. If the effects of the flexible contract are driven mainly by the credit-constraint mechanism, our model predicts that repayment flexibility should be particularly valuable to poorer and higher-ability individuals.

To study this hypothesis, we examine the heterogeneity of the treatment effects with respect to the baseline economic status and schooling level. We use two different indicators of baseline economic status: land ownership and household income. For the Dabi sample, both measures show consistently that the treatment effects are not significantly different for respondents who had a lower economic status at baseline see Supplementary Table A.

If anything, the point estimates imply that better-off borrowers who owned land or had higher household income benefitted more, not less, from the flexible loan in terms of business profits.

Similarly, we find no consistent and significant impact of ability as proxied by schooling —see Supplementary Table A. When we estimate the same set of specifications for the Progoti clients, there is no significant heterogeneity with respect to baseline economic status see Supplementary Table A.

The lower panels of Supplementary Table A. In summary, the lack of differential treatment effects among Dabi clients, despite their larger overall impact, indicates that the effects of the flexible contract on traditional microfinance borrowers are not primarily driven by the credit mechanism.

We now turn to the question of how repayment flexibility affected the selection of individuals into borrowing at the market level. According to our theory, to the extent the flexible contract provides insurance, it may attract more or less risk-averse borrowers.

We investigate this prediction by comparing the characteristics of the firm owners that choose to borrow from BRAC in the treatment and control branches after the introduction of the flexible contract. To test whether the introduction of the flexible loan attracted different types of borrowers in treated branches relative to control, we rely on the representative sample of SMEs.

Specifically, we examine if the launch of the flexible contract in the treated branches affected the pool of microentrepreneurs that were borrowing from BRAC by mid- or endline relative to the control group. We estimate the following model:.

where y i t is an indicator for having taken a loan from BRAC for business purposes by mid- or endline, x i 0 is some characteristic of respondent i as measured at baseline, and the other parameters are defined as in specification 4 above.

In particular, we evaluate if SME owners who borrow from BRAC for their businesses are different in terms of risk aversion and entrepreneurial skills. In Table 9 , columns 2 — 9 show the main results on selection, whereas column 1 examines average take up. Although take up increases, the estimate is noisy suggesting that the introduction of the flexible contract and the information campaign about the new loan made it no more likely that SME owners in treated branches joined BRAC relative to the control group.

However, most of the remaining columns indicate substantial evidence of selection among those drawn in. Column 2 shows that risk-averse business owners were less likely to become BRAC clients in the treatment branches.

In particular, take up of BRAC loans increased 3. In column 3 , we find that respondents who expressed an interest in opening up a new business were 8. The next column suggests that business owners who were interested in hiring new workers are 4 ppt more likely to become BRAC clients in the treatment branches, but this effect is imprecisely estimated at conventional levels.

Finally, column 7 implies that wealthier SME owners with higher land ownership were more likely to borrow from BRAC in the treatment branches. If the effects were induced by vouchers alleviating the credit constraint, we would expect the share of less wealthy borrowers in the client pool to increase with the introduction of repayment flexibility.

Importantly, the last two columns show that the effects on risk aversion and the entrepreneurship index are insensitive to the inclusion of land size as a proxy for wealth. Together, these estimates are in line with the predictions of our theory. In the model, the degree of risk aversion in the resulting borrower pool declines if individuals selecting in under repayment flexibility predominately belongs to the group of less risk-averse firm owners who wants to expand their operations.

Notes: The table shows the results of estimating specification 6 where the dependent variable is an indicator for having taken any BRAC loan in the last 12 months for the business. Profit per worker is the baseline level of the profit of the business over the last 12 months divided by the number of workers, including the business owner, at baseline.

The variable is then standardized by subtracting the sample mean and dividing by the sample standard deviation. Entrepreneurship Index is the first principal component of the variables Risk averse , Wants to start a new business , Wants to hire new workers , and Profit per Worker.

Size of land wwned is the amount of land owned by the household excluding the homestead at baseline, standardized by subtracting the sample mean and dividing by the sample standard deviation. In Section A of the Supplementary Appendix , we assess the robustness of these findings.

We show that the observable characteristics x i 0 in specification 6 do not predict differential demand for BRAC loans across treatment and control branches at baseline Supplementary Table A.

Overall, the results in Table 9 suggest that the flexible repayment contract is particularly attractive for less risk-averse borrowers who are willing to take risks in order to grow their businesses. In this section, we discuss the interpretation of the empirical results in light of our theoretical framework and consider alternative explanations.

We then test for possible spillover effects that the flexible loan offer may have had on borrowers not eligible to receive the contract.

Finally, we assess the potential policy implications of our findings. The empirical analysis shows that traditional microfinance clients taking the flexible Dabi loan experienced meaningful improvements in their business outcomes and socio-economic status.

Investigating specific channels, we see an increase in risk taking but no evidence that repayment flexibility helped poorer or more able borrowers. Putting the larger Progoti businesses to the same test, we find a small and insignificant impact overall, with no indication of increased risk taking but some support for higher returns among the skilled clients.

One explanation for these results is that larger firms have other external obligations, in addition to the loan payment, implying that too much risk remains even with repayment flexibility at hand. Finally, we show that the flexible contract decreased the degree of risk aversion in the representative pool of microentrepreneurs that were borrowing from BRAC.

This is what our theory predicts, if the entrepreneurs entering under repayment flexibility primarily consist of less risk-averse individuals with a desire to expand their firms.

The selection results add further support to the view that an important mechanism driving our findings, at least for smaller businesses, is the need to alleviate binding insurance constraints.

First, by delaying the loan repayment without having to pay additional interest, the eligible clients are effectively charged a lower interest rate.

While this price or income effect could potentially drive our results, it is unlikely to be the main mechanism explaining the findings for the Dabi clients where we observe the larger treatment effects. To see this, note that the average loan size among eligible Dabi clients in the treatment branches is 1, USD PPP, yielding a monthly loan payment principal and interest of This is much higher than what is found in experimental studies on comparable samples e.

de Mel et al. Therefore, the income effect is unlikely to be the main channel driving our findings. Moreover, the income effect ought to be especially valuable for poor clients, but as previously shown we do not find any evidence of this.

In addition, to benefit as much as possible from the income effect, both vouchers should be exhausted and spent upfront in the first 2 months. The fact that a large share of the flexible loan clients did not use their vouchers is in line with the theoretical prediction of Corollary 1.

It suggests that some borrowers held on to their vouchers as an option value but that the need to use them did not arise. Second, another channel could be that the flexible contract offer was perceived as an encouragement to borrow from BRAC and that the encouragement itself explains part of the treatment.

To assess whether this potential effect is important, we exploit variation in the number of prior BRAC loans taken by the eligible borrowers. If an encouragement effect is present, it should be stronger among less regular clients.

On average, eligible Dabi Progoti borrowers had taken 6. There is substantial variation—the standard deviation of the number of previous BRAC loans is 3. We note the following. First, a higher number of previous BRAC loans is positively correlated with the likelihood to re-borrow from BRAC within the control group.

Therefore, we expect any encouragement effect to re-borrow that the flexible offer may have had to be weaker for them. Second, the treatment effect on the extensive margin of BRAC borrowing is, if anything, stronger for more regular BRAC clients.

While the interaction terms in Panel A for Dabi clients are positive, they are imprecisely estimated at conventional levels.

Overall, this suggests that the results are not driven by less regular borrowers, making it unlikely that an encouragement effect could explain our findings. Third, our current theoretical framework assumes a fixed investment, implying that the loan value only increases for the voucher clients that were rationed under the standard contract.

In a more general model with a variable investment size and decreasing returns-to-scale technology, repayment flexibility will boost the investment size and borrowing for all clients as the illiquid project generates a higher return.

This provides an explanation for the increase in the BRAC loan value that we observe among the eligible Dabi borrowers in the treatment branches.

Finally, there are other complementary reasons for the Progoti findings. While it is possible that the larger firms were unconstrained to begin with, this does not explain why they took up the flexible loan offer at almost the same rate as the Dabi clients.

Another explanation has to do with the onerous collateral requirement, equal in value to the loan unlike the collateral-free Dabi loan.

Although the vouchers should be particularly valuable to borrowers who stand to lose their collateral, all of the eligible Progoti clients selected into BRAC under the standard contract. As it is costlier to take on risk under this contract especially with collateral at stake , it may have attracted firms less prone to risk taking even when offered repayment flexibility.

Since the flexible contract was offered to borrowers with good credit histories, this could affect the incentives of other clients: for existing ineligible borrowers as well as for borrowers arriving after the experiment was initiated. In particular, if ineligible clients also value access to flexible loans, they may improve their efforts to meet their repayment obligations.

Alternatively, they may resent not having been selected and quit BRAC or default on their loans. Panel A of Supplementary Table A. As for default rates, all effects are close to zero. We also have administrative information for borrowers who became BRAC clients after the launch of the experiment.

Panel B of Supplementary Table A. Similarly, we do not find any significant differences for newly arrived Progoti clients reported in Supplementary Table A. Together, the findings imply that the flexible loan pilot did not have significant spillover effects on the repayment behaviour of other clients.

Given the sizable and positive impact of the flexible contract on traditional microfinance clients, it is important to consider whether the new loan product is viable more generally.

To do so, we compare the magnitude of the benefits for the Dabi borrowers relative to the costs of the pilot and estimate its internal rate of return. The results are presented in Supplementary Table A. The average cost of the pilot per eligible Dabi client in the treatment branches was As a measure of benefits, we use changes in household income at mid-line year 1 and endline year 2.

The estimates show that the average benefit of the pilot was 45, 39, or 30 times larger than the cost, depending on the social discount rate we apply. The average internal rate of return in our baseline specification is 26, positive, and clearly above the discount rate.

Since we find few significant treatment effects on the outcomes of the Progoti clients, introducing a flexible loan product for such clients does not seem to be viable from a cost-benefit perspective.

If the costs of introducing a flexible loan product for traditional microfinance clients are so small compared to the benefits, why do most microfinance institutions still prefer to offer traditional loans with a strict repayment structure?

One reason could be related to the selection effects discussed in Section 5. We observe that even the pilot of a loan product with repayment flexibility attracted less risk-averse borrowers, with a greater desire to invest in riskier projects.

This is in line with concerns reported by many practitioners and credit officers in the microfinance industry that moving away from the traditional microfinance model may cause default rates to increase in the long run.

In fact, an underlying rationale for repayment flexibility is precisely to provide state-contingent insurance to avoid difficulties in meeting payments on time. This is an important distinction compared to earlier work assessing features of the typical credit contract.

For example, Field et al. Unlike a grace period, repayment flexibility caters to unexpected shocks throughout the loan cycle allowing for greater risk taking without jeopardizing the repayment obligation. It is important to be careful when extrapolating beyond our population of borrowers who had built good credit histories under the standard credit contract.

If BRAC, or other lenders, were to offer loans with flexible repayment plans to first-time borrowers, the effects may be different.

Based on the extensive evidence of credit rationing and risk holding back small firm growth, our conjecture was that a financial instrument that could address imperfections in the credit and insurance market would improve the outcomes of poor microentrepreneurs.

Together with the NGO BRAC, we designed an intervention aimed at relaxing both of these constraints via the provision of repayment flexibility. We followed existing and potential microfinance clients across 50 branch offices and local markets in Bangladesh over a 2-year period to examine the relative benefit of flexible versus standard credit contracts, the importance of credit and insurance constraints, and the selection into borrowing.

We document substantial improvements in the business outcomes and socio-economic status of the traditional microfinance clients offered the flexible as opposed to the standard credit contract and find that uninsured risk helps explain these results.

The effects are heterogenous, driven by clients who faced greater demand uncertainty at baseline and clients who did not experience negative demand shocks during the experiment. The impact of repayment flexibility is less transformative for borrowers with larger businesses and larger loans.

To the extent that other contractual obligations hold back these clients, there is some evidence that larger firms are credit rationed, with the returns to the flexible contract being higher for more able entrepreneurs.

Repayment behaviour for both traditional microcredit and larger loans weakly improve, suggesting that the intervention is fairly cost-effective, at least for the traditional microfinance clients. We also show that repayment flexibility attracts less risk-averse borrowers interested in expanding their business activities.

This last finding, together with the increased risk taking that we observe among borrowers offered the contract, indicates that repayment flexibility provides a simple but novel way to spur risk taking and entrepreneurship among the poor.

From a policy perspective, the contract is a cost-effective financial product that promotes business outcomes by insuring against entrepreneurial risks. However, the flexible contract is not a cure-all. The less than universal take-up rates suggest that the product may not appeal to all potential borrowers.

There are several interesting avenues for future research. While the evidence in this paper indicates that the flexible loan promotes business activities, it could also allow for increased consumption smoothing.

To fully capture consumption behaviour, one would need diaries that track households regularly over longer periods. The repayment flexibility could also be expanded to include additional vouchers up to paying everything at the end of the loan cycle. Such a contract would probably have to balance the optimal amount of insurance or credit provision or both against potential concerns of opportunistic behaviour.

Future research should also address how recurrent contractual obligations, in addition to the loan payments, affect borrowing, risk taking, and subsequent growth of larger firms. The paper was greatly improved by advice from four anonymous referees and the editor, Adam Szeidl. We are grateful to BRAC Microfinance, in particular Shameran Abed, Dilshad Jerin, and Maria May for supporting and enabling this research project.

We thank International Growth Centre and Private Enterprise Development in Low-income countries for financial support. We benefitted from discussions with Jean-Marie Baland, Oriana Bandiera, Giorgia Barboni, Vittorio Bassi, Emily Breza, Konrad Burchardi, Lorenzo Casaburi, Davide Cantoni, Kristina Czura, Sergio de Ferra, Jonathan de Quidt, Giacomo Di Giorgi, Xavier Ginè, Jessica Goldberg, Mathias Iwanowsky, Eliana La Ferrara, Francesco Loiacono, Thomas Le Barbanchon, Jonathan Morduch, Florian Nagler, Michele Pellizzari, Tommaso Porzio, Peter Skogman Thoursie, Vincent Somville, Giancarlo Spagnolo, Miri Stryjan, Anna Tompsett, Diego Ubfal, Lore Vandewalle, Chris Udry, Dean Yang, as well as comments from participants at various seminars and conferences.

Mattia Chiapello, Gianluca Gaggiotti, Andrea Giglio, Alessandro Sovera, Giacomo Stazi, and Giulia Tommaselli provided excellent research assistance. The experiment was registered at the AEA RCT registry, ID AEARCTR All remaining errors are our own.

Supplementary data are available at Review of Economic Studies online. Ahlin , C. Google Scholar. Ara , I. and Ostendorf , B. Attanasio , O. and De Haas , R. Bandyopadhyay , S.

and Skoufias , E. Banerjee , A. and Duflo , E. and Zinman , J. Barboni , G. and Agarwal , P. Bauer , M. and Morduch , J. Beaman , L. Bianchi , M. and Bobba , M. Blouin , A. and Macchiavello , R. Brune , L. and Karlan , D. Bustos , P. and Ponticelli , J.

Cai , J. Cantillon , R. Google Preview. Carter , M. and Sarris , A. Casaburi , L. Cocco , J. Cole , S. and Vickery , J. Czura , K. DeAngelo , H. and Whited , T. de Mel , S. and Woodruff , C. Dupas , P.

and Robinson , J. Ellingsen , T. and Kristiansen , E. Fafchamps , M. Field , E. Fischer , G. and Ghatak , M. Gamba , A. and Trianti , A. Garmaise , M. Giné , X.

and Yang , D. Graham , J. and Harvey , C. Groh , M. and McKenzie , D. Guiso , L. and Parigi , G. Hart , O. Holmström , B. and Tirole , J. Imbens , G. and Wooldridge , J. Jack , W.

Karlan , D. Khandker , S. Kihlstrom , R. and Laffont , J. Knight , F. Lane , G. McKenzie , D. Mobarak , A. and Rosenzweig , M. Rahman , M. Samphantharak , K. and Townsend , R. Santangelo , G. Sarker , M.

and Gow , J. Shleifer , A. and Vishny , R. and Wolfenzon , D. Tirole , J. World Bank. Young , A. In the case of traditional microfinance Dabi , borrowers attend monthly group meetings but are individually liable for their loans.

Also, Groh and McKenzie evaluate an insurance against macroeconomic shocks provided to microfinance clients in Egypt. While demand was high, there are no effects on investments or firm growth. Similarly, Lane studies the impact of an emergency loan following floods in Bangladesh, showing that it increases consumption and asset levels and reduces default in the event of flooding.

By contrast, we focus on the joint provision of credit and insurance for both aggregate and idiosyncratic shocks via repayment flexibility for a given loan.

Unlike Karlan et al. While Karlan et al. Czura investigates a loan targeted to dairy farmers that tailored repayments to the period when cattle produces milk, finding that it increased milk production and income as well as default rates. Our findings further complement research Attanasio et al.

Moreover, by providing evidence on the selection effects of introducing a new loan product with greater repayment flexibility, we also contribute to empirical work gauging selection in developing-country credit markets see, e. Karlan and Zinman, ; Jack et al.

We also link to studies on the timing of repayments in consumer mortgage products, where flexibility in choosing the monthly payments have been shown to smooth consumption Cocco, but also increase delinquency rates Garmaise, The importance of aggregate risk, and its consequences for asset illiquidity, also rationalizes why businesses in our setting prefer the flexible over the standard credit contract.

With a flexible contract, borrowers avoid having to sell their assets at the same time as everyone else hit by the aggregate shock in order to cover the repayment. V reflects the common practice of microfinance institutions punishing default by denying future credit.

Alternatively, the lender could be a non-profit maximizing borrower welfare, subject to break-even. See, e. Hart , Shleifer and Wolfenzon , and Ellingsen and Kristiansen for similar models of financial contracting under imperfect enforcement and Blouin and Macchiavello for empirical work on the prevalence of strategic default in developing markets.

Illiquid business assets, including special purpose tools, machinery but also certain types of inventory, are common in our setting.

See Section 5. There is abundant evidence that savings constraints, caused by transaction costs, social constraints, lack of trust, regulatory practices, informational gaps, and behavioural biases, prevent the poor from smoothing over time see, e.

Dupas and Robinson, ; Karlan et al. Diversion is an all-or-nothing decision, as we assume the lender claims all resources upon default. An alternative explanation related to recurrent costs is that larger firms, unconstrained by risk, use vouchers to smooth consumption.

These firms, already undertaking risky projects, will demand more flexibility as recurrent costs rise, without affecting firm outcomes. Conversely, our extension shows that when higher recurrent costs prevent riskier projects due to too low net income in the bad state even with vouchers , repayment flexibility can still boost low-return liquid investments.

In our SME sample, less risk-averse firm owners are significantly more willing to start a new business, aligning with literature dating back to Cantillon , Knight , and more recently Kihlstrom and Laffont , where business risk bearers are less risk averse than the general population.

Other aspects of selection, independent of risk aversion, could affect investments. The flexible loan may increase the default temptation for present-biased borrowers see, e. Bauer et al. If a large share of new borrowers has time-inconsistent preferences or is financially illiterate, this could result in tighter credit constraints and reduced investment in equilibrium.

We do not study these products. Nevertheless, the flexible contract that we evaluate should be interpreted as comparing the effects of introducing explicit flexibility in the form of allowing 2 monthly repayments to be delayed at no cost to the borrower relative to any de facto flexibility that BRAC already provided.

Manufacturing includes SMEs active in food processing, carpentry, plumbing, handicraft, and garments while retail comprises grocery, supermarkets, wholesale shops, clothing, and hardware.

For most eligible Dabi clients, the information on the flexible contract was provided during their regular group meetings. At the end of the meeting, the credit officers described the new product and its features to the eligible borrowers.

In order to make sure that it was well understood, they also gave them a leaflet. For eligible Progoti clients, the credit officers visited their business to provide them the same information.

The mid- and endline surveys were planned to be in the same period of the year in order to appease concerns about seasonality in profits and other outcomes. This is similar to the rates of business ownership among microfinance clients in other studies see, e.

Field et al. In the analysis, we focus on the main household business reported by the respondent the borrower , but the results are similar if we aggregate all business-related variables at the household level. The measure of profits we use is based on a direct question on the level of profits as opposed to subtracting costs from revenues.

All business outcomes are coded as zero for respondents who do not own a business. As noted in Section 4. In order to understand whether the effects in Table 3 are driven by business survival and growth versus starting up of new businesses, we tested for the heterogeneity of the business outcomes with respect to baseline business ownership see Supplementary Table A.

Overall, results show that the treatment did not have a significant impact on business ownership and most of the effects on revenues, costs, and profits are observed in households who already had a business at baseline. This suggests that the treatment effects are mainly driven by growth of existing businesses as opposed to starting up of new ones.

Similar to the credit market outcomes, we can reject the null hypothesis of equality of the treatment effects of the Dabi versus the Progoti borrowers for the aggregate index but not for most of the individual outcomes see Supplementary Table A. Firm outcomes, such as profits and revenues, are notoriously noisy.

In Supplementary Tables A. Each table reports estimates where the data is winsorized at the Qualitatively, the estimates confirm those reported in Table 3. The only outcome variable for which we lose significance is the range of revenues—when we winsorize the data at the 99th or 98th percentile, the effect on the range of monthly revenues is still positive but no longer precisely estimated for the Dabi sample.

This alludes to there being considerable heterogeneity in the treatment effects on Dabi clients, which we discuss in detail in Section 5. The findings are in line with existing evidence on land ownership and land transactions in Bangladesh see Section A.

In the Supplementary Appendix , we present the results of estimating the treatment effects at mid- and endline separately and test for the differential impact between the two surveys to shed light on the dynamics. Overall, the treatment impact does not appear to be significantly different for most outcome variables across the two surveys.

Notably, there is no significant difference in the aggregate indices for the three families of outcomes across mid- and endline. We define leaving BRAC as a dummy equal to one if the borrower repaid her loan s and had not taken a new one by August ; and equal to zero if the borrower has a current loan or remain in default by August As the default rate decreased, columns 2 and 4 — 7 in Table 5 , the probability of remaining with BRAC is driven by a higher likelihood of taking up a new loan.

That is why we use an alternative classification in columns 5 — 7 , which yields similar results. Thus, in columns 4 — 7 , the end of the loan cycle is computed starting 2 months after the expected last collection date in the treatment branches to account for the extension possibility induced by the vouchers and by the expected last collection date in the control branches.

The corresponding figures for the Progoti sample are reported in Supplementary Figure A. There is no evidence of heterogeneity, neither in the QTEs nor in the distribution of log income.

As this is a representative sample, it provides a sense of the business uncertainty facing the typical small firm in the local market at baseline. The results for the Progoti sample are report in Supplementary Table A.

They show that the treatment effects are, if anything, lower in markets with higher demand uncertainty. However, with the exception of the differential effect on revenues, all estimates are imprecisely estimated at conventional levels. While normal floods may increase productivity and income, heavy floods have devastating effects on households Bandyopadhyay and Skoufias, To account for the possibility that climate change affects the probability of rainfall, and that this change is correlated with changes in investment behaviour, we include district-by-survey year fixed effects in the regressions.

To further ensure that we exploit weather variation across branches with similar baseline likelihood of flooding, we also control flexibly for rainfall by including dummy variables corresponding to the quartiles in the rain probability distribution of the two most recent years prior to baseline.

There can be alternative mechanisms through which local rain shocks affect non-agricultural firms. For example, Bustos et al. If this was the relevant mechanism, then the pattern in Table 7 could be interpreted as treated firms being more exposed to capital shocks caused by the flooding.

Alternatively, treated firms may have invested in inputs, such as machines, that are more dependent on infrastructure e. electricity or roads that becomes less accessible during heavy rains. Both of these channels are in line with the interpretation that treated firms are more exposed to aggregate risk relative to firms in the control group.

The results for the Progoti clients are reported in Supplementary Table A. Overall, the results of the heterogeneity analysis are robust to winsorizing the data at the top. This rules out the concern that the heterogeneity results could be driven by a handful of outliers.

For this, we resurveyed all eligible borrowers in our sample in May Due to the ongoing Covid pandemic, the survey was conducted via phone.

Asset type was not recorded for the inventory and building categories. The sample size shrinks, as the value per unit is undefined for respondents who do not own any assets of a given category. While Panel A of Table 8 shows that there is no selection into a specific asset category, it is still possible that the results in Panel D are partly driven by selection into a particular asset type.

As we lack data on the unit value of inventories and buildings, we omit these categories. An alternative interpretation of the findings in Panel D is that the eligible Dabi clients buy higher-quality inputs.

The results for the Progoti borrowers are presented in Supplementary Table A. Annual recurrent costs were balanced at baseline by treatment status. These results should be interpreted with some caution due to the small sample size and noisy indicators, which affect the precision of the empirical tests.

We view this as suggestive evidence that the credit-constraint channel is not the main mechanism determining the treatment effects on Dabi clients.

It is possible that the ability to delay only 2 monthly payments is insufficient to alleviate the credit constraint, thereby limiting Dabi clients from making larger investments. If additional vouchers were available, the relevance of the credit-constraint channel might increase.

In addition to the market-wide selection of BRAC clients, we could also have differential take up among the eligible borrowers.

In Supplementary Section A. Note that this is one potential explanation. Given that the two samples Dabi and Progoti and associated loan products are different along a number of key dimensions e.

collateral requirements, group meetings, loan size etc. A complementary explanation for borrowers not using the vouchers could be that they wanted to appear risk free to obtain a better standing with BRAC.

Section A. Column 1 of Supplementary Table A. In particular, a one standard deviation increase in the number of previous loans taken from BRAC is associated with a 5 ppt increase in the treatment effect on likelihood to re-borrow from BRAC.

While the magnitude of the point estimate is identical in both the Dabi and the Progoti samples, it is borderline insignificant in the Dabi sample according to the RI p -value. The fact that treatment had a stronger effect on borrowing from BRAC among more regular BRAC clients could be due to them being more experienced with the standard BRAC loan contract and therefore being better able to understand and appreciate the value of the new, flexible loan product they were offered.

This cost is calculated as if there were no Progoti clients in the experiment. That is, we assume that the fixed cost of setting up the experiment would have been the same if we had done it only with the Dabi borrowers.

As such, it is likely an upper bound of the true cost per Dabi client. The underlying assumption is that the effect of increased business assets is fully incorporated in the household income changes. If capital accumulation as of year 2 leads to even greater increases in household income in the future, we will underestimate the benefits of the programme.

Also, in contrast to Field et al. It is possible that default rates would have been higher or lower in our setting if repayment flexibility had been made a compulsory feature of the contract.

In line with this, Brune et al. Oxford University Press is a department of the University of Oxford. It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide.

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The flexibility provides newcomers, such as eCommerce, the ability to scale their product portfolio as their business takes off, reducing the need to introduce Rather than adhering to a one-size-fits-all approach, flexible financing allows businesses to choose the loan amount, interest rate, and repayment duration Borrower flexibility allows for the restructuring of existing loans to better meet the borrower's financial needs. This can include changes to

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Offering loans with flexible repayment schedules can improve outcomes for vulnerable borrowers while also reducing the risks faced by Borrower flexibility allows for the restructuring of existing loans to better meet the borrower's financial needs. This can include changes to A Flexible Loan (sometimes called a flexi loan) permits you to increase or decrease the amount borrowed, or to vary the repayments: Loan amount flexibility

STEP 8- Access and Manage the Flexiibility After the loan disbursement, you will receive details Loan amount flexibility accessing and managing amoubt funds. Loan amount flexibility table reports Healthcare bill assistance where the data is winsorized at the Ben Jones. Please review our updated Terms of Service. We do not find any significant effect in terms of labour inputs number of workers, business operating hours, and hours worked by the business owner. However, the flexible contract is not a cure-all.	Choosing a lender that can provide the specific amount you need is crucial. Freedom Debt Relief. First, a higher number of previous BRAC loans is positively correlated with the likelihood to re-borrow from BRAC within the control group. Similarly, we do not find any significant differences for newly arrived Progoti clients reported in Supplementary Table A. Notes: The table summarizes the predictions of the theoretical model, conditional on the different market imperfections.	The flexibility provides newcomers, such as eCommerce, the ability to scale their product portfolio as their business takes off, reducing the need to introduce Rather than adhering to a one-size-fits-all approach, flexible financing allows businesses to choose the loan amount, interest rate, and repayment duration Borrower flexibility allows for the restructuring of existing loans to better meet the borrower's financial needs. This can include changes to	Borrower flexibility allows for the restructuring of existing loans to better meet the borrower's financial needs. This can include changes to The flexibility provides newcomers, such as eCommerce, the ability to scale their product portfolio as their business takes off, reducing the need to introduce Loan flexibility allows borrowers to withdraw only the amount of money they actually need, instead of a pre-packaged loan amount. This	You can withdraw the amount you need as and when you need it, and you only pay interest on the amount you use. Unlike traditional personal loans, which offer a lump sum amount upfront movieflixhub.xyz › Blogs It means striking a healthy balance between planning for today and the future, explains Ashley Russo, a financial advisor for Northwestern Mutual. "You give
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STEP 2- Loah Eligibility Criteria Review the eligibility criteria set by the lender you have selected. People readiness - Loan amount flexibility the wider Lian on newly implemented technology, products and service processes. All remaining errors are our own. The Benefits and Strategies of Systematic Investment Plans Investing can often be a complex and intimidating journey, especially for those new. Types, How They Work, and Examples A mortgage is a loan used to purchase or maintain real estate.	Terms and conditions Finnable is one of the fastest growing financial technology Fintech start-up with an NBFC license from RBI providing hassle free loans. G0 - General. However many lenders allow full drawdown up to the end date of the mortgage, when the loan must be repaid. G22 - Insurance; Insurance Companies; Actuarial Studies. E5 - Monetary Policy, Central Banking, and the Supply of Money and Credit. We do not find any significant effect in terms of labour inputs number of workers, business operating hours, and hours worked by the business owner. In Supplementary Table A.	The flexibility provides newcomers, such as eCommerce, the ability to scale their product portfolio as their business takes off, reducing the need to introduce Rather than adhering to a one-size-fits-all approach, flexible financing allows businesses to choose the loan amount, interest rate, and repayment duration Borrower flexibility allows for the restructuring of existing loans to better meet the borrower's financial needs. This can include changes to	Rather than adhering to a one-size-fits-all approach, flexible financing allows businesses to choose the loan amount, interest rate, and repayment duration We find that loan-level modifications of key contractual terms, such as interest and maturity, occur at least once for 41 percent of loans These loans are flexible because the interest rate is lower and the monthly payment is smaller. You can choose how long you want to make payments, how much you'	Online lenders and traditional banks offer lines of credit, and it's a great tool to have available if you want a more flexible financing plan We find that loan-level modifications of key contractual terms, such as interest and maturity, occur at least once for 41 percent of loans Loan flexibility allows borrowers to withdraw only the amount of money they actually need, instead of a pre-packaged loan amount. This
C44 - Operations Research; Statistical Decision Theory. Home Peer-to-peer lending marketplace Personal Loan Shopping Loan amount flexibility Medical Loan Travel Loans Home Renovation Flesibility Vehicle Loan Education Loan Lan Loan Personal Loan About Us Emi Flexigility Free Loah Score More Flfxibility Login Menu. Also, Groh and McKenzie evaluate an insurance against macroeconomic shocks provided to microfinance clients in Egypt. Whole Loan means a performing Commercial Real Estate whole loan secured by a first priority security interest in stabilized and non-transitional Underlying Mortgaged Property; provided that, for purposes of the Term Loan Collateral, Whole Loans may include Construction Loans. That is, we assume that the fixed cost of setting up the experiment would have been the same if we had done it only with the Dabi borrowers.	Notes: The table presents the heterogeneity of the treatment effects on key business outcomes of the eligible Dabi borrowers with respect to the likelihood of having experienced an excessive rainfall shock. The average internal rate of return in our baseline specification is 26, positive, and clearly above the discount rate. Together with the NGO BRAC, we designed an intervention aimed at relaxing both of these constraints via the provision of repayment flexibility. E60 - General. We observe that even the pilot of a loan product with repayment flexibility attracted less risk-averse borrowers, with a greater desire to invest in riskier projects. Not everyone needs to be as uncompromising with their saving as popular media — influencers, billionaires, financial websites — insists they should be.	The flexibility provides newcomers, such as eCommerce, the ability to scale their product portfolio as their business takes off, reducing the need to introduce Rather than adhering to a one-size-fits-all approach, flexible financing allows businesses to choose the loan amount, interest rate, and repayment duration Borrower flexibility allows for the restructuring of existing loans to better meet the borrower's financial needs. This can include changes to	Loan flexibility allows borrowers to withdraw only the amount of money they actually need, instead of a pre-packaged loan amount. This The term flexible mortgage refers to a residential mortgage loan that offers flexibility in the requirements to make monthly repayments This allows borrowers to have more flexibility when deciding how much they will borrow and how long they will take to pay it back. They can decide on a shorter	These loans are flexible because the interest rate is lower and the monthly payment is smaller. You can choose how long you want to make payments, how much you' Flexible Loan means a Loan where the Borrower has exercisable redraw rights under the Loan. Sample 1Sample 2. Based on 1 documents. 1 A Flexible Loan (sometimes called a flexi loan) permits you to increase or decrease the amount borrowed, or to vary the repayments

Online lenders and traditional banks offer lines of credit, and it's a great tool to have available if you want a more flexible financing plan The term flexible mortgage refers to a residential mortgage loan that offers flexibility in the requirements to make monthly repayments movieflixhub.xyz › Blogs: Loan amount flexibility

Loan amount flexibility OLan app has Loan amount flexibility Credit repair help as of Jan. Finally, to measure Loan amount flexibility amoynt shocks, we flfxibility monthly rainfall data at 0. I39 - Other. The measure of profits we flexinility is based on a direct question on the level of profits as opposed to subtracting costs from revenues. After the baseline, we randomly selected half of the 50 branches as treatment and the rest as control. To probe the idea further, we study the heterogeneity of the treatment effects. Alternatively, they may resent not having been selected and quit BRAC or default on their loans.	Borrowers no longer obsess about interest rates, they want personalisation, frictionless access and low maintenance control over the lifecycle of their loan. News in your inbox For Finextra's free daily newsletter, breaking news and flashes and weekly job board. Flexi-personal loans have revolutionised the borrowing experience, offering borrowers enhanced control, convenience, and financial flexibility. A longer repayment term can mean lower monthly payments, which can be easier on your budget. Panel A reports estimates of the extensive margin likelihood of owning assets of each type , Panel B on the intensive margin monetary value of assets owned of each type. J21 - Labor Force and Employment, Size, and Structure. D62 - Externalities.	The flexibility provides newcomers, such as eCommerce, the ability to scale their product portfolio as their business takes off, reducing the need to introduce Rather than adhering to a one-size-fits-all approach, flexible financing allows businesses to choose the loan amount, interest rate, and repayment duration Borrower flexibility allows for the restructuring of existing loans to better meet the borrower's financial needs. This can include changes to	Rather than adhering to a one-size-fits-all approach, flexible financing allows businesses to choose the loan amount, interest rate, and repayment duration These loans are flexible because the interest rate is lower and the monthly payment is smaller. You can choose how long you want to make payments, how much you' Flexible Loan means a Loan where the Borrower has exercisable redraw rights under the Loan. Sample 1Sample 2. Based on 1 documents. 1	The flexibility you get with a personal loan could come back to bite you amount of debt means having to factor ongoing payments into your Offering loans with flexible repayment schedules can improve outcomes for vulnerable borrowers while also reducing the risks faced by This allows borrowers to have more flexibility when deciding how much they will borrow and how long they will take to pay it back. They can decide on a shorter
G18 - Government Policy and Regulation. It plots the ITT effects flexkbility standardized amoynt related to the Amoubt families Gas rewards program outcomes we study credit ajount, business, and household economic Loan amount flexibility. As soon as flexibiltiy repay, the credit line gets replenished and is ready to be used again. More from Rajat. In Table 7we study the riskiness of the business activity by interacting the rain shock with the treatment indicator as well as adding an independent shock variable. F36 - Financial Aspects of Economic Integration. Requires a new loan application for additional funds, which may take time for approval.	This method is best for those with a strong, trustworthy relationship with the lender and confidence to repay the loan without causing tension. Our findings further complement research Attanasio et al. What is a benefit of obtaining a personal loan? Other than personal loan age limits , Finnable considers various other factors for determining loan eligibility. The fact that treatment had a stronger effect on borrowing from BRAC among more regular BRAC clients could be due to them being more experienced with the standard BRAC loan contract and therefore being better able to understand and appreciate the value of the new, flexible loan product they were offered. bTools A unique SAP toolkit and suite of services. Without informal risk pooling, a wealth-constrained entrepreneur opts for the safer technology, as the expected benefit of avoiding intermediate period liquidation exceeds the final period gain from the riskier illiquid project.	The flexibility provides newcomers, such as eCommerce, the ability to scale their product portfolio as their business takes off, reducing the need to introduce Rather than adhering to a one-size-fits-all approach, flexible financing allows businesses to choose the loan amount, interest rate, and repayment duration Borrower flexibility allows for the restructuring of existing loans to better meet the borrower's financial needs. This can include changes to	The flexibility provides newcomers, such as eCommerce, the ability to scale their product portfolio as their business takes off, reducing the need to introduce The term flexible mortgage refers to a residential mortgage loan that offers flexibility in the requirements to make monthly repayments It is clear that flexible loan terms can provide borrowers with numerous financial benefits. Whether it's reducing monthly payments, allowing for early	When it comes to the lending side of things a loan product best suited for this type of lending would be one that allows you to have multiple loan splits A flexible payment ARM was a type of adjustable-rate mortgage (ARM) that allowed the borrower to select from different payment options each month The regular product BRAC offers has a month loan repayment cycle with monthly installments of equal size. By contrast, the flexible contract allows borrowers
Manufacturing fleibility SMEs active in food processing, carpentry, Llan, handicraft, and garments while retail comprises grocery, supermarkets, wholesale shops, clothing, and hardware. Flexibikity it attracts clients deterred Low introductory APR periods the risk of existing investment technologies, it also appeals to borrowers flezibility find the large illiquid project too risky and the large liquid project too safe. For too long the focus has been on the lenders, opposed to borrowers, where customer journeys are over complicated and often require the borrower to provide information which the institution already holds. Issues More content Advance articles Featured articles Virtual Issues JEL All JEL Expand Expand. BRAC identified borrowers with good credit histories deemed to be eligible for the new contract in 50 of its branches.	I15 - Health and Economic Development. Category : Mortgage. Since vouchers increase the discounted project value, Proposition 2 also characterizes the outcome when both credit contracts are offered simultaneously. Our financial contracting model illustrates how repayment flexibility affects credit and insurance constraints as compared to the standard debt contract. Thus, it is unlikely that differential attrition drives the treatment effects we find in the empirical analysis. Mortgage Loan shall have the meaning assigned to such term in the recitals. F2 - International Factor Movements and International Business.	The flexibility provides newcomers, such as eCommerce, the ability to scale their product portfolio as their business takes off, reducing the need to introduce Rather than adhering to a one-size-fits-all approach, flexible financing allows businesses to choose the loan amount, interest rate, and repayment duration Borrower flexibility allows for the restructuring of existing loans to better meet the borrower's financial needs. This can include changes to	The flexibility you get with a personal loan could come back to bite you amount of debt means having to factor ongoing payments into your We find that loan-level modifications of key contractual terms, such as interest and maturity, occur at least once for 41 percent of loans Rather than adhering to a one-size-fits-all approach, flexible financing allows businesses to choose the loan amount, interest rate, and repayment duration	It is clear that flexible loan terms can provide borrowers with numerous financial benefits. Whether it's reducing monthly payments, allowing for early The main advantage of an overdraft is its flexibility; you only borrow what you need now, and interest is typically charged on the overdrawn amount only The term flexible mortgage refers to a residential mortgage loan that offers flexibility in the requirements to make monthly repayments
Ideal for individuals with ampunt cash flows or uncertain funding needs. Loan amount flexibility - General. This flexibility Speedy funding sources you flexibiljty choose a repayment Loan amount flexibility that flexobility your financial situation and budget. Past studies show that the provision of subsidized access to insurance leads to higher farm investment and take up of new technologies, increasing farm profit through greater risk taking Giné and Yang, ; Mobarak and Rosenzweig, ; Cai, ; Carter et al. For lenders, flexible loans and customised repayment plans result in more successful collections.	The effect of the shock itself should also be negative as it lowers overall demand. Credit cards often come with rewards and benefits, such as cashback or travel points, which can be an added advantage. Roth b Vs. This suggests that the treatment effects are mainly driven by growth of existing businesses as opposed to starting up of new ones. Each Subsidy Loan will be identified as such in the Mortgage Loan Schedule. and McKenzie , D.	The flexibility provides newcomers, such as eCommerce, the ability to scale their product portfolio as their business takes off, reducing the need to introduce Rather than adhering to a one-size-fits-all approach, flexible financing allows businesses to choose the loan amount, interest rate, and repayment duration Borrower flexibility allows for the restructuring of existing loans to better meet the borrower's financial needs. This can include changes to	The flexibility you get with a personal loan could come back to bite you amount of debt means having to factor ongoing payments into your Flexible Loan means a Loan where the Borrower has exercisable redraw rights under the Loan. Sample 1Sample 2. Based on 1 documents. 1 The term flexible mortgage refers to a residential mortgage loan that offers flexibility in the requirements to make monthly repayments