RISK MANAGEMENT INFORMATION SYSTEM. Nicola King, Software Product Services Ltd.

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1 RISK MANAGEMENT INFORMATION SYSTEM Nicola King, Software Product Services Ltd. Abstract Many organisations have a specialist statistical unit to provide management information for the purpose of reviewing existing business and assisting with making key decisions for the future. In a Finance House, one of the responsibilities of such a unit is to monitor the quality and performance of its new and existing business. When an individual applies for credit, data is collected from the application form and possibly a credit bureau. Throughout the life of the loan information is gathered on the payment profile of the loan. A SAS/AF Application was implemented to extract this information from extensive Corporate Databases and to present it to the managers of a Risk Unit. Information was required in a user friendly and manageable environment. Detailed knowledge of the data was not available before commencing the project. Reports were developed on an ad-hoc basis in response to specific requests from the user community, and when tried and tested, were then incorporated into the system. This paper demonstrates the suitability of the SAS Information Delivery System to this type of development as well as the flexibility and power of the SAS Frame environment for presenting information. Introduction To a lending company, 'Risk Management' is all about balancing the potential profits one could make from supplying credit with the risk that one takes in doing so. The basis for successful Risk Management is information. At the time of application for a loan, current information about a customer is used to predict the probability that the customer will repay the loan, and thus prompt the decision to accept or reject the application. After a loan has been accepted, information about the payment profile can be used to monitor the effectiveness of the selection process and also to exploit the relationship with 'good' customers by for example offering them more credit. Information about 'bad' customers can be used to determine how to best recover the debt. This paper covers the development of a number of analysis and reporting techniques for the purpose of supplying Risk Management information for a large Finance House. The techniques were developed and implemented using the SAS Information System. This paper will demonstrate how well suited the SAS Information System is to interrogating the large volumes of data associated with credit applications, but at the same time

2 providing tools for generating and analysing smaller volumes of summary management information. It will also show how the SAS information system allows a system to be developed over time, using batch and interactive processing, in the both the mainframe and PC environment, without the full scope of the project being defined before the first modules are implemented. The credit scoring technique Firstly one needs to understand the concepts of 'credit scoring', a statistical technique used by the lending company to process loan applications. When an individual or company applies for credit, various application details and/or bureau information is passed through a specially developed scorecard and a score is returned. This score on its own or together with a set of policy rules is used by the underwriters to decide whether to accept or reject the application. The process of building a scorecard relies on the assumption that the future will be like the past. It uses past information about application details, the decision to grant credit and the outcome of loans, to determine which characteristics known at the time of application would have been the best to predict the successful repayment of the loan. These same characteristics are then used in a scorecard to filter future applications. Using the extensive statistical capabilities, the SAS System has successfully been used to develop scorecards. However this paper assumes that one or more scorecards are already in place and looks in more detail at the process of monitoring the use and performance of the scorecards. An initial cut-off score is chosen to achieve the correct trade-off between quality and quantity. The effects of choosing the initial cut-off are closely monitored Phase one of the monitoring system The monitoring system evolved over time. The first request was to set up a process for storing historic information regarding the payment profile or performance history of a loan. This data would be used to produce a number of standard performance reports for example Rollrate Analysis, Dynamic Delinquency Report.

3 Rollrate Analysis January 1996 February 1996 Up to Date 1 Mnth New this month % 5.59% Up to Date % 1.81% 1 Mnth % 23.41% 2 Mnths Mnths 8.47% % 6.31% % 2 Mnths % % % 3+ Mnths On a monthly basis, an extract was taken from the accounting system. This extract typically contained information about the current status of a loan and summarised data about the past status. However, in order to produce the above mentioned reports it is necessary to collect more complete information about the status of all loans on a month by month basis. The information kept included the number of days and amount of money still outstanding. The process involved writing a SAS program that updated the history file using information from the current month file. This program was developed interactively in the program editor using SAS 6.07 on the MVS. Once the program was tested and accepted it was moved to the Windows environment on the PC. A point and click screen allowed the user to initiate the batch process for updating this file. Reporting from this SAS data set involved summarising a very large number of observations. To increase flexibility and improve performance a number of commonly used sub-populations were selected. For example, scorecards, splits of scored characteristics etc. The data was held in a pre-summarised form, but the system also allowed any other view of the data to be analysed by returning to the raw data. The summarised data in this case was held locally for quick response times but the raw data remained on the mainframe. A front end was developed on the PC to select specific subpopulations and groups of sub-populations.

4 Designing the front end This concept of holding pre-summarised data, triggered the idea of creating generic subpopulations. It was important to be able to analyse the performance of the portfolio from various angles. However, we were aware that the future approach would be different and we would need to be able to include this new approach as soon as it was implemented. Also, although the initial work was carried out on one portfolio, the reports would also be used for other areas. So the choice of sub-populations should be able to extend to cover all these possibilities. Once this was decided upon, most reports and data extracts could be created from the same selection screen. This meant a consistent user interface as well as a compact and easily maintainable SAS/Frame application. Adding new Reports A large number of application reports are common to the credit industry as a whole. A number of these were included as standard reports. It was also necessary to customise a number of these common reports and to add a few new reports to the report suite. The development of all customisations and new reports was carried out on the mainframe using sample SAS data sets. An initial report specification was provided by a credit analyst and in very short space of time a sample report was produced. By studying the actual values in a report it was often realised that the report could be restructured to provide a more informative view of the data. Also, some reports were very interesting for a specific portfolio but showed very little information for another. For example, one useful report for one group of accounts compared the 'through the door' population with those accepted for a loan. This report gives little information to the other group of accounts as the acceptance rate for this population is extremely high. Once the risk management department was satisfied with the structure of the report, it was shown to the other users and their comments incorporated. It was discovered that extracting information from users was difficult when starting with a blank piece of paper. However this iterative process proved to be very effective. The tabulate procedure was used extensively and minor changes to the reports could be actioned immediately. The final step was then to incorporate the new report into the information system. Special options were often added to cope with specific report requirements. These were added as optional frames to be called only by reports requiring the extra parameters. Interactive Analysis Tools As well as preparing reports which could be viewed on the screen or on paper, a facility for homing in on a specific subset of the population was also required. For example, a report might hint at an increase in the bad rate for a specific scorecard. There could well be another report in the report suite which might give more information about this subpopulation. Once the user has established exactly which sub-population appears to be changing, it should be possible to investigate this data on an observation level. A facility was developed to download the observations meeting the required criteria. The user was

5 then taken into SAS/Insight with a number of start-up graphs and tables to allow further investigation and analysis. This facility was extremely important as the information analysed at this level is often completely different from the information provided at the summary levels. Graphical Reporting Tools Once a large section of the information required by the Risk Management team could be extracted, it was possible to concentrate on the graphical presentation of the information. The technique should be used to supplement the information provided in the standard reports. SAS/Graph and SAS/Frame were used for this purpose. It was possible to investigate various ways of presenting the information and once the presentation was accepted it could be incorporated into the Information System. Implementing New Scorecards Using the historical information base, new scorecards were developed which exploited the more recent application and performance information which was now available. The new scorecards would take into account the recent changes in the composition and nature of the population. A number of ad-hoc exploratory analyses were performed at this time to investigate the impact of the new scorecards on the application process. Reports of interest at this level include one for looking at the impact of certain policy rules and another to monitor the time taken for the decision to accept or reject an application to be made. Moving to UNIX A project was initiated to transfer the Corporate Databases to a UNIX environment. The team is currently enhancing the system to adapt to this pending change. The team believes that the process should be simplified by the uniformity of SAS across the various platforms. Conclusion The SAS Information System proved to be a flexible development tool and was easily adapted to provide a complete solution to all the data analysis requirements. As well as storing and managing data effectively, it was successfully used to develop a Management Information System with a GUI front end which provided both tabular and graphical output to meet all the departments reporting requirements.