Please use this form to submit your study for inclusion into our database. It will be checked by a member of the Innovation Growth Lab team, who may be in contact to ask for more information. Your email address * Your name * Title * The name of the study Short summary This experiment provides direct evidence on how information technologies can lead to the decentralisation of decision-making processes within organisations, and how IT solutions may represent an effective and low-cost alternative to steepening or increasing monetary incentives. Providing credit scores increased the effort committees put into solving more difficult problems, increased committees' overall output, and reduced the need for higher-level manager involvement in the decision-making process. A brief description of the project's goals and its current state Abstract <p>We distinguish the impact of information technology adoption on information processing costs and agency costs by conducting a randomized control trial with a bank that adopts a new credit-scoring tool. The availability of scores significantly increases credit committees' effort and output on difficult- to-evaluate loan applications. Output increases almost as much in a treatment where the committee receives no new information, but anticipates the score becoming available after it evaluates an application, which suggests that scores reduce incentive problems inside the credit committee. We also show that scores improve efficiency by decentralizing decision-making and equalizing marginal returns across loans.</p> The full abstract of the study, if available Links http://www.nber.org/papers/w19303 Links to any published papers and related discussions Authors * Affiliations Academic and other institutes that the authors of the study are members of Delivery partner Organisations involved in delivering the trial, if appropriate Year Year Year199419951996199719981999200020012002200320042005200620072008200920102011201220132014201520162017201820192020202120222023202420252026 Month MonthJanFebMarAprMayJunJulAugSepOctNovDec Day Day12345678910111213141516171819202122232425262728293031 Journal Journal publishing the study, if available Publication stage * Working Paper Published Ongoing Research Forthcoming Discussion Paper Research theme * Entrepreneurship Innovation Business Growth Country Country or countries where this study took place. Topics What sort of topics does the study cover? Sample attributes Hypotheses / research question How does IT adoption affect productivity? The researchers attempt to answer this question using evidence from an RCT to identify the effect of a particular IT implementation. Sample Trial population and sample selection Implement a 4-month pilot program in 8 BancaMia branches. Treatment applications allowed the committee to see the score of applicants and were randomly selected for each branch. Randomisation was done in real time, when the committee began discussing an application. Number of treatment groups Size of treatment groups Group 1: 563 applications; Group 2: 523 applications Size of control group Unit of analysis Clustered? Yes No Cluster details Trial attributes Treatment description Treatment 1: the committee receives the score before evaluating the application (allows measurement of overall effect of scores on committee effort, output and productivity). Treatment 2: committee evaluates the application and chooses an interim action before receiving the score, receives the score after taking the interim actions, and then may revise the choice when deciding a final action (allows measurement of committee behaviour changes when informational asymmetry is expected to decline) Rounds of data collection Baseline data collection and method BancaMia's information database which includes detailed information on all loans from application to repayment/default Data collection method and data collected Evaluation Outcome variables <p>Committee Actions: Committee approves/rejects. Committee Effort: Evaluation time. Loan Outcomes: whether or not the loan was approved, amount approved and whether it matched the application amount, maturity approved and whether it matched the application maturity, disbursed amount, default after 6 months, default after 12 months, defaulted amount at 6 months and 12 months. Loan Prospecting and Branch Output: number of loans, amount of loans, fraction of defaults, fraction of amount that defaults.</p> Results <p>Committee Actions: When scores are added as an input in the decision process, the number of cases in which committees cannot decide is reduced by 41.8%. The difference is positive but not significant. Observing a score decreases the probability of referring the application to the manager by 2.3 percentage points, a 48% decline reduction. Scores reduce the probability of collecting additional information by 1.7 percentage points, a 27% decline relative to the baseline. Committee Effort: Committees spend on average 16.2% more time per application when scores are available. Yet scores do not shift the entire distribution of evaluation times; credit scores increase the evaluation time on applications that take longer than the median time to evaluate. Put together, scores reduce the cost of deciding for any given default probability, and the reduction is larger for larger loan amounts, where the committee members have more at stake. Loan Outcomes: The effect of scores on the probability that the loan is issued is close to zero and not statistically significant. This implies that the addition of scores to the loan production process does not affect the overall extensive margin of lending. Scores don't have a significant effect on the average level of any of the measured outputs relating to loans - loan size, probability that loan amount and application are different, absolute value of the loan amount adjustment and default probability. Loan Prospecting and branch output: No statistically significant change in the score or requested loan amount of approved loans. Overall, scores do not affect total output in the short-run.</p> Intervention costs Not available. Cost benefit ratio Reference Paravisini, D., Schoar, A., 2013. 'The Incentive Effect of IT: Randomized Evidence from Credit Committees'. NBER Working Paper No. w19303. Citation for use in academic references
