100-mem­ber CUG helps con­tain frauds

Ex­pe­rian Fraud Preven­tion Bureau to­day has 100 mem­bers, who share fraud re­lated in­for­ma­tion. Vaishali Kas­ture, coun­try head, Ex­pe­rian In­dia, pro­vides de­tails:

Banking Frontiers - - Fraud Prevention - Mo­han@bank­ingfron­tiers.com

N. Mo­han: Ex­pe­rian’s Fraud Preven­tion Bureau now has 100 mem­bers. Can you out­line the spe­cific ben­e­fits the plat­form has brought to the mem­bers?

Vaishali Kas­ture: Ex­pe­rian Hunter, our fraud preven­tion tool, de­tects ap­pli­ca­tion fraud by match­ing credit re­quest in­for­ma­tion against mul­ti­ple data sources, in­clud­ing the shared fraud data. It com­prises sev­eral rules that work to­wards iden­ti­fy­ing in­con­sis­ten­cies in credit applications. This ser­vice is built on a ro­bust frame­work that en­sures de­tec­tion of fal­la­cies.

The in­dus­try has the ben­e­fit of screen­ing against a data­base of 80 mil­lion plus unique applications when us­ing Ex­pe­rian Hunter ser­vices. With its use, we have seen a 55% yoy growth in FY17-18, with the number of trans­ac­tions reach­ing 40 mil­lion, bring­ing an over­all sav­ings of `21,000 crore for the BFSI sec­tor in In­dia.

For in­stance, in the se­cured loans space, Hunter could de­tect a po­ten­tial fraud with PAN and date of birth match.

PAN and DOB of prin­ci­pal bor­rower was matched against re­jected ap­pli­ca­tion of an­other bor­rower from a different CUG mem­ber. Also, de­tails with the other CUG bor­rower re­vealed different tele­phone and em­ployer in­for­ma­tion. When this case was ref­er­enced to the field in­ves­ti­ga­tion team, the fol­low­ing re­marks were made: “Em­ployer: In­cor­rect Em­ploy­ment De­tails” & “Con­tact: Fake Con­tact de­tails”. The ap­pli­ca­tion was re­jected lead­ing to a sav­ing of `70,00,000 for the bank.

Can you give an in­dica­tive list of mem­bers of the CUG?

Cur­rently, the plat­form is sup­port­ing around 20 life in­sur­ance companies and 80 banks, HFCs and NBFCs to man­age ap­pli­ca­tion frauds thus com­pris­ing over 60% of the re­tail lend­ing mar­ket in In­dia.

What are the unique fea­tures of the Hunter plat­form, which pow­ers the bureau? 0

Hunter is key in help­ing the In­dian BFSI in­dus­try stay ahead of fraud­sters and in fraud preven­tion through early de­tec­tion of the same. One of its unique fea­tures is the ro­bust frame­work that is has been built around. Through the CUG, we have cre­ated an ecosys­tem that en­ables mem­bers of the group to share data of their re­spec­tive ap­pli­cants in­clu­sive of the ones who have shown signs of be­ing po­ten­tial fraud­sters. Hunter runs this data on its plat­form and alerts the re­spec­tive mem­bers in case of any in­con­sis­ten­cies ob­served, thereby cre­at­ing a re­silient en­vi­ron­ment to fight fraud.

Can you ex­plain the salient as­pects of the tech­nol­ogy be­hind Hunter?

The Hunter plat­form shares data across all the CUG mem­bers mak­ing it the largest fraud re­pos­i­tory in the coun­try. The plat­form uses its unique tech­nol­ogy to high­light 3 types of cases to identify po­ten­tial fraud:

Erst­while applications which have been de­clined for fraud­u­lent rea­sons In­con­sis­tent applications in terms of data be­ing sub­mit­ted

Ve­loc­ity applications de­tect­ing mul­ti­ple applications not just from the same per­son but also with same ad­dresses, con­tact num­bers, bank ac­count de­tails etc

All these helps in iden­ti­fy­ing not just lone op­er­a­tors but also syn­di­cated rings that try and de­fraud the bank­ing sys­tem.

How ef­fec­tive is the in­for­ma­tion shar­ing be­tween the mem­bers of the CUG?

The CUG en­ables mem­bers of the group to share data of their re­spec­tive ap­pli­cants in­clu­sive of the ones who have shown signs of be­ing po­ten­tial fraud­sters. The more the mem­bers in the CUG, we have more data for screen­ing the applications, hence, this makes the plat­form more efficient. In ad­di­tion, var­i­ous fea­tures like rea­sons for de­cline of an ap­pli­ca­tion, help the CUG mem­bers to con­sider fur­ther de­tails of applications while screen­ing them and thus take in­formed de­ci­sions.

Also, we have ‘Hunter Fraud Score’ that mea­sures the prob­a­bil­ity of fraud in a credit ap­pli­ca­tion across the bank­ing and in­sur­ance in­dus­tries. The score helps re­tail finance providers and in­sur­ance companies to sig­nif­i­cantly in­crease their ef­fi­ciency in fraud de­tec­tion. Busi­nesses can identify applications that should be screened for po­ten­tial fraud and pri­or­i­tize those that have a high prob­a­bil­ity of be­ing fraud­u­lent. This en­ables them to po­ten­tially lower their fraud losses and focus on ap­prov­ing applications from gen­uine cus­tomers.

Are there sim­i­lar plat­forms fa­cil­i­tated by Ex­pe­rian in other coun­tries? Can you give de­tails?

The Hunter plat­form is a global prod­uct for Ex­pe­rian and is be­ing used across mul­ti­ple coun­tries. The big mar­kets for this prod­uct apart from In­dia are United King­dom, Brazil, Columbia etc.

Vaishali Kas­ture points out that the CUG has cre­ated an ecosys­tem that en­ables shar­ing data and then de­tect­ing pos­si­ble frauds well in time

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