Collaborative Credit Risk Management Counters Impact of Bad Loans

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1 Cosultig Collaborative Credit Risk Maagemet Couters Impact of Bad Loas Abstract Though credit ratig agecies provide detailed scores uder the Basel II guidelies, baks have the optio to develop their credit risk models. It is madated by some cetral baks for baks to use their ow credit risk assessmet framework for ledig ad ivestmet decisios, istead of relyig o ratigs assiged by agecies. Baks may, however, have limited access to the data ad aalytical models ecessary to carry out objective credit risk aalysis. Hece a collaborative credit risk maagemet service provided by leadig regulatory or acial bodies would prove bee cial to the ecoomy as well as idividual istitutios.

2 Cosultig Bee ts of a Cetralized Credit Risk Maagemet System As the iterest obtaied from log-term loas is a key source of reveue for baks, their o-repaymet severely impacts pro tability. Large baks typically employ more people ad sophisticated maagemet iformatio systems (MIS) to moitor ad cotai credit risk, whereas smaller istitutios rely more o their i-house experiece to guide loa decisios. Differet istitutios, with varied levels of credit risk maagemet maturity, ca threate the stability of a ecoomy. Govermets ad regulatory bodies have the power to address, ad eve prevet this to a large extet. Although ew regulatios such as the Basel guidelies act as checkpoits for baks worldwide to follow stadard risk maagemetprocedures, the implemetatio of sophisticated credit risk models etails several practical challeges: Prohibitive cost of settig up databases ad aalytical tools eeded to publish the MIS reports required for creditrisk maagemet The failure of Lehma Brothers i 2008 set shock waves through the world, highlightig the deleterious impact of bad loas o atioal ad global ecoomies. Techical ad aalytical skill requiremets to ru sophisticated credit risk assessmet systems Regular updates of models ad methods are eeded to keep pace with ew developmets i credit risk modelig These challeges ca be addressed by a cetralized credit risk maagemet system joitly set up by cetral ad other baks. The system would provide access to eormous historical ad curret data ad curret aalytical tools. As baks o loger operate i silos, the failure of oe ca have devastatig ripple effects o other acial istitutios, which provides the motivatio for baks to cooperate i implemetig a cetralized system.

3 Cosultig I respose to the bakig crisis of 2008, the US Dodd- Frak Wall Street Reform Act has created a Of ce of Fiacial Research (OFR), with the madate to establish a soud data maagemet ifrastructure for systemic risk moitorig. 'Europea Credit RiskOutlook', a study coducted by the acial services orgaizatios, Efma ad FICO, foud that more members of the Europea acial services commuity are turig to data aalytics to ehace their credit risk models, with more tha 40% plaig to ivest i the 1 techology. Compoets of Credit Risk Maagemet Risk maagemet is the bedrock of bakig operatios ad a comprehesive credit risk maagemet system should typically cover risk ratig ad credit portfolio maagemet. Risk ratig icorporates acial aalysis, coverig projectios ad other ecoomic factors, icludig idustrial ad maagemet risks. Fiacial aalysts eed to review reports from the credit risk aalysis models ad adjust ratigs to accout for other relevat factors that caot be modeled. Credit portfolio maagemet ivolves diversi catio to lower the risk of o-repaymet of loas with respect to a etire idustry. Credit risk models are available to examie credit risk exposures across geographies ad product lies i a timely maer. Collaborative risk maagemet system provides several bee ts such as: Access to the borrower's complete credit history ad the experiece of other baks with respect to the potetial borrower Realistic iteral credit risk assessmet apart from the ratig provided by a professioal credit ratig agecy Access to aalysis tools, reports, ad expertise to eable more iformed ledig decisios How Data Affects Risk Moitorig Systemic risk moitorig is complex, requirig iformatio from diverse sources icludig prospectuses, corporate ligs,aual reports, ad research reports to be loaded ito master les ad databases. Raw ad derived data is fed ito pricig models, calculatio egies, ad aalytical processes.lack of cohesive data, due to eormous data volumes, ad cross-istitutioal barriers are key issues that prevet timely risk maagemet. Effective moitorig requires access to all relevat data across istitutios, as well as evolvig data aalytics techology. A collaborative credit risk maagemet system addresses both challeges ad delivers strog riskrecogitio capabilities to the acial system.

4 Cosultig Credit Risk Maagemet as a Service Due to limited resources ad high costs, baks may d it dif cult to build a iformatio maagemet framework thaticorporates the vast amout of data ad acial models that are eeded for credit risk maagemet. Holistically, the same activities are repeated across multiple baks, leadig to ief ciecies across the idustry. A cetral, atioal body ca udertake the resposibility of maitaiig a iformatio database ad makig relevat data, as well as aalytical tools available to all baks. A collaborative credit risk maagemetservice ca be ru i a experimetal maer iitially, before beig deployed o a large scale. The service ca be evisaged as a web portal, backed by data processig ifrastructure. The cetral bak ad other stakeholders cotribute data as well as aalysis tools, ad the credit departmets of subscribig baks access these facilities to empower loa decisios. To improve the currecy ad relevace of the service, it is vital to provide real life data sets for a pilot, idetify regulatory obstacles ad address them i collaboratio with the cetral bak, ad ivest i traied persoel who ca utilize the platform to objectively decide whether to grat or reject loa applicatios. Coclusio Not all baks have access to the data ad aalytical models ecessary to carry out objective credit risk aalysis. Cetral baks ad other acial bodies of atioal importace must take the lead i promotig collaborative credit risk maagemet. They ca work with stakeholders usig the latest risk assessmet data ad methodologies, share their expertise, ad ru pilot schemes followed by wider deploymet to alleviate the burde of moutig bad loas. Summary:Credit risk maagemet is a evolvig eld, ad a collaborative approach holds the key to addressig ad improvig the acial stability of istitutios ad global ecoomies. Refereces [1] FICO ad Efma, Europea Credit Risk Outlook: Results of the Seveth Europea Credit Risk Maagers Agecy (March 2013), Accessed o 18 February 2016, co.com/e/ode/8140? le=5418

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