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Making Credit Decisions Using Credit Reports. George Akello Regional Credit Officer, Africa Standard Chartered Bank. Discussion points. Getting to the destination model Creating efficiency and scale Essential elements – Industry wide Essential elements – bank wide.
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Making Credit Decisions Using Credit Reports George Akello Regional Credit Officer, Africa Standard Chartered Bank
Discussion points • Getting to the destination model • Creating efficiency and scale • Essential elements – Industry wide • Essential elements – bank wide
Getting to the destination model.. Bureau Type (Information Depth) Information details Countries No Bureau No information Negative Information Information about loan defaults / write offs only Kenya, Zimbabwe, Botswana Negative Information + Positive Information Information about exposure level as well as loan defaults / write offs Nigeria, Tanzania, Ghana, Uganda, Zambia Negative Information + Positive Information + Historical Trend Information about exposure level and delinquency / defaults / write offs; with history of last 1-5 years No markets in Africa Negative Information + Positive Information + Historical Trend + Credit score In addition to the above, a credit score based on full bureau data No market in Africa All of the above+ Non Financial Industry Data In addition to the above, data from other industries such as telecom operators, utility companies No market in Africa The destination model will be the last, most advanced stage as shown above. However markets may chose to reach there though an evolution process, starting from the basics
Creating efficiency and scale … Bureau Type (Information Depth) Information details Countries No Bureau No information Manual interface Manual search by the banks from a data base. Usually the results are in PDF / non machine readable format • Kenya, Zimbabwe, Botswana, Nigeria, Tanzania, Ghana, Uganda, Zambia Automatic interface Bureau is linked directly with banks’ front end systems. Results extracted automatically while application decision making. Usually the results are in machine readable format. No market in Africa Automatic interface with scrub facility In addition to above, the bureau offers full portfolio scrub facility to banks in order to view risk profile and migration of portfolio on periodic basis Further value added features include: Bureau score Default triggers No market in Africa To reach the final “destination” stage, a few key measures are necessary both at the industry end and banks end. These are outlined in the next two slides.
Essential elements (industry wide) • Coverage • For a bureau to be successful, it needs to cover most (if not 100%) of the financial industry. If some key banks / financial institutes are not covered, the value of information (specially exposure levels, but also defaults) becomes limited & uncertain • Ideally: Markets should have a mandatory bureau participation for all banks • Accuracy • A bureau is as good as the accuracy of the data in it. Markets should have a mechanism to ensure faultless submission by all banks, both in terms of timing and data correctness • Ideally: Bureau or regulator should conduct independent audits of each bank in terms of data being submitted. • Consistency • In many markets, the definition of “default” or “delinquent” etc. varies from bank to bank. A bureau needs to define these terms to maintain consistency across the board. • Ideally: All banks should participate in this process to answer key questions, e.g. How to calculate days-past-due, how to treat / tag DRPs (debt relief programs) etc. • Responsiveness • Bureaus should have a mechanism to correct mistakes when they are made. E.g. If wrong data is submitted by a bank, it should be immediately rectified once highlighted, in order to minimize customer impact • Ideally: Industry wide forums should be in place for customers to challenge their bureau reports, if they believe these are misreported. • Responsibility • Bureau should ensure that customer privacy is protected all the time. • Ideally: There should be a data-protection regulation covering both data storage and data transfer security: • Reach ability • While the bureau service has its cost, the pricing of these services should be managed to ensure that its not too high for bank’s to consider bureau participation unviable. Nor it should be too low for bureau to be unable to sustain itself. • Ideally: Industry should jointly determine the optimal pricing level for bureau services, acceptable by all stake holders
Essential elements (bank wide) • Awareness • Banks should make sure that their customers are aware of dynamics of the bureau, and the fact that their information will be shared. If mandated by regulator, customer consent before information sharing is essential. • Ideally: Before participating in a bureau, banks should run a customer, as well as staff, awareness campaign on above lines • Data Accuracy • Banks should make a concrete effort to make sure their data (including historical delinquency info) is accurate. This also includes consistency of definitions with industry & bureau • Ideally: Before participating in bureau, a data clean up exercise should be done • Data Security • Technology should be in place to ensure transfer and storage of data is secure and fool proof. • Ideally: Bank’s tech team should be in the loop to ensure latest security mechanism is in place • Resources & Funding • Every bank participating in the bureau needs to have dedicated resources including staff who will report to the bureau, or extract bureau info, as well as technology to transmit the data to and from the bureau. • Ideally: Technology team should be in the loop at all stages of bureau participation. • Policy Changes • Once credit information sharing becomes a norm, and bureau is fully operational, the banks should have robust policies in place to benefit from these elements. These may include • DBR policies capturing full industry exposure • Bureau score usage for TTD as well as portfolio actions • Proactive line management actions in the event of off-us performance deterioration • Incorporating bureau variables in in-house scoring models, • Verification process based on customer contact details given in the bureau