Credit score speeds up the PROCESS Sig­nif­i­cantly t

The Gulf Today - Business - - Saturday Interview11 -

or­gan­i­sa­tions where de­ci­sions are driven by data and ac­tions are op­ti­mised for the great­est re­turn us­ing pre­dic­tive an­a­lyt­ics.

Our sub­ject mat­ter ex­per­tise spans Strat­egy, Pric­ing, Credit Risk Man­age­ment, Mar­ket­ing and Sales An­a­lyt­ics. By har­ness­ing the power of pro­pri­etary credit bu­reau data, Qarar has built a tan­gi­ble ad­van­tage and of­fers a suite of in­dus­try lead­ing tech­ni­cal so­lu­tions that can un­lock the true value and power of in­for­ma­tion. can make rapid and re­li­able de­ci­sions. Credit scores can also help con­sumers to un­der­stand where they stand fi­nan­cially in sev­eral ways.

As times change, newer meth­ods of credit scor­ing have emerged, for ex­am­ple so­cial me­dia scor­ing. These al­ter­na­tive meth­ods of­fer par­tic­u­lar ben­e­fits to con­sumers in­clud­ing un­der-banked, thin­ner­file in­di­vid­u­als, or those liv­ing in coun­tries with lim­ited credit bu­reau data. As credit scor­ing evolves, loans are be­com­ing eas­ier for con­sumers across the world to ac­cess, as while also pos­ing less of a risk for banks and lend­ing in­sti­tu­tions.

A: So­cial me­dia profiling is paving the way for al­ter­na­tive credit scor­ing data, and can be ap­plied to cus­tomers of all types, in­clud­ing both older and younger clients. To­day, loan ap­pli­ca­tions and credit card en­quiries es­sen­tially hinge on one thing: a credit score. Tra­di­tion­ally, in­sti­tu­tions have as­serted that an in­di­vid­ual’s fi­nan­cial his­tory, which pri­mar­ily in­cludes their pay­ment his­tory, cur­rent debt pro­file, and length of credit his­tory, in­forms fu­ture be­hav­iour and there­fore should dic­tate the de­ci­sion over whether to of­fer credit to po­ten­tial bor­row­ers and at what rate. This frame­work makes sense when the nec­es­sary in­for­ma­tion is avail­able, but what about when it is not? In cases where a pay­ment his­tory is lack­ing banks do not have enough in­for­ma­tion on which to base credit scores. As a re­sult, tak­ing out a loan is vir­tu­ally im­pos­si­ble for con­sumers, which puts them at a se­vere dis­ad­van­tage.

Len­ders need a way to ver­ify cred­it­wor­thy in­di­vid­u­als when they do not have ac­cess to lo­calised credit his­to­ries. This is par­tic­u­larly true in GCC coun­tries like the UAE and Saudi Ara­bia, where vast por­tions of the pop­u­la­tion are highly tran­sient or ex­pats, and would oth­er­wise never have ac­cess to fi­nan­cial ser­vices due to lim­ited credit bu­reau data. In this sit­u­a­tion, big data credit scor­ing like so­cial me­dia profiling can as­sess bor­rower risk and de­fault prob­a­bil­ity.

Al­ter­na­tive ap­proaches to tra­di­tional credit scor­ing can also be used to as­sess thin­ner-file bor­row­ers such as stu­dents, for­eign na­tion­als, and pop­u­la­tions of un­der-banked in­di­vid­u­als. This big data scor­ing in­cludes data from so­cial me­dia, bank trans­ac­tion data, cell­phone data, mo­bile data, bank and lender data if avail­able, as well as third party data hubs of per­son­alised, in­ter­na­tion­ally stan­dard­ised and ver­i­fi­able data that can be eas­ily pack­aged for len­ders. The anal­y­sis of this data helps len­ders to in­crease ap­proval and con­ver­sion rates, and of­fers bor­row­ers bet­ter ac­cess to fi­nanc­ing. It also al­lows len­ders to per­form user-per­mis­sioned checks on bor­row­ers based on so­cial me­dia and on­line foot­prints, IP ver­i­fi­ca­tion, and brows­ing his­tory anal­y­sis.

Cus­tomer data has al­ways been a cen­tral de­ci­sion-mak­ing fac­tor for fi­nan­cial in­sti­tu­tions, be­cause bankers make lend­ing de­ci­sions based on credit scores while in­sur­ers might look at driv­ing records or re­quire health checks be­fore is­su­ing poli­cies. But as peo­ple and their de­vices be­come more in­ter­con­nected, new streams of gran­u­lar, real-time data are emerg­ing, and with them in­no­va­tors who use that data to sup­port fi­nan­cial de­ci­sion-mak­ing. Your so­cial me­dia pro­file speaks vol­umes about your life­style and cred­it­wor­thi­ness. Friendlyscore, for ex­am­ple, con­ducts in-depth analy­ses of peo­ples’ so­cial net­work­ing pat­terns to pro­vide an ad­di­tional layer of data for len­ders try­ing to an­a­lyse the credit-wor­thi­ness of a bor­rower.

A: Risk man­age­ment in bank­ing has been trans­formed over the past decade, largely in re­sponse to reg­u­la­tions that have emerged fol­low­ing the global fi­nan­cial cri­sis and the fines levied in its wake. Im­por­tant trends are afoot that sug­gest risk man­age­ment will ex­pe­ri­ence even more sweep­ing change over the next decade. The change ex­pected in the risk func­tion’s op­er­at­ing model il­lus­trates the mag­ni­tude of what lies ahead. To­day, about 50 per­cent of the func­tion’s staff is ded­i­cated to riskre­lated op­er­a­tional pro­cesses such as credit ad­min­is­tra­tion, while 15 per­cent work in an­a­lyt­ics. Mckin­sey re­search sug­gests that by 2025, these num­bers will be closer to 25 and 40 per­cent, re­spec­tively.

The fun­da­men­tal trends do per­mit a broad sketch of what will be re­quired of the risk func­tion of the fu­ture. The trends fur­ther­more sug­gest that banks can take some ini­tia­tives now to de­liver short-term re­sults while pre­par­ing for the com­ing changes. By act­ing now, banks will help risk func­tions avoid be­ing over­whelmed by the new de­mands.

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