How Can Banks De­rive Value from An­a­lyt­ics in a Mo­bile-First World?

Due to the sheer num­ber of mo­bile de­vices in use, big data can tap mo­bile data an­a­lyt­ics to bet­ter understand trends across vast pop­u­la­tions and sub-seg­ments of users. When an­a­lyzed ef­fec­tively, this data can help banks gain ac­cess to busi­ness­crit­i­cal ins

Voice&Data - - CONTENT - Kis­han Venkat Narasiah & Viros Sharma (The au­thors are Con­sult­ing Lead DWBI & An­a­lyt­ics and VP & Global Prac­tice Head DWBI & An­a­lyt­ics, ITC In­fotech) vndedit@cy­ber­me­

Rapidly evolv­ing tech­nol­ogy has led to far reach­ing con­se­quences for the world of busi­ness and the bank­ing sec­tor is no ex­cep­tion. Due to change in cus­tomer us­age pat­terns and oper­a­tions cost, even banks have started dis­cour­ag­ing in- per­son in­ter­ac­tions. The dawn of the In­ter­net gave rise to net bank­ing which made life con­ve­nient. To­day, the ar­rival of so­phis­ti­cated smart­phones in the mar­ket and the mo­bile bank­ing ca­pa­bil­ity has com­pletely trans­formed the way peo­ple are en­gaged in bank­ing trans­ac­tions.

The con­cep­tu­al­iza­tion of mo­bile bank­ing started when banks ad­justed the net bank­ing ap­pli­ca­tions, orig­i­nally de­signed for desk­tops/lap­tops to fit mo­bile screens. Some of the emerg­ing economies like In­dia have suc­cess­fully skipped some stages of dig­i­tal evo­lu­tion and have straight away adopted mo­bile ser­vices.

To­day’s bank­ing web pages are sen­si­tive to de­vices. Mo­bile apps de­vel­oped by banks can be eas­ily down­loaded to en­sure more re­spon­sive vi­su­al­iza­tion ex­pe­ri­ence for the user and they in turn pro­vide valu­able per­sonal in­for­ma­tion about the user to banks.

Ex­plo­sive data growth

In ad­di­tion to offering users a great vis­ual ex­pe­ri­ence, smart­phones also gen­er­ate data through mo­bile apps. At present, there are over 2 bn smart­phone users around the world. This num­ber is go­ing to in­crease over the next few years and so is the data gen­er­a­tion. The use of so­cial me­dia also gives a great op­por­tu­nity to consolidate the data with the ex­ist­ing in­for­ma­tion that is cap­tured.

The vol­ume of mo­bile data and the speed at which it is cre­ated is only go­ing to in­crease with the global pop­u­la­tion growth, mo­bile de­vice us­age rate, and the use of so­cial me­dia. Be­hind those ex­ceed­ingly large vol­umes of data is the real busi­ness value. The ac­tual busi­ness in­sights could be de­rived through a proper an­a­lyt­ics pro­gram that has the abil­ity, di­rec­tion, and ca­pa­bil­ity to understand the busi­ness and the rel­e­vant in­for­ma­tion. The ques­tion is: How can you make sense of all this data in or­der to make it ac­tion­able, and avoid the chal­lenges it presents?

Data An­a­lyt­ics and In­sights

Col­lec­tion of large datasets does not really mean bet­ter busi­ness in­sights. The col­lected data needs to be an­a­lyzed on var­i­ous busi­ness mod­els to de­rive op­ti­mal value. Of­ten this leads to con­sider big data as ‘dream’ so­lu­tion for all the needs. But does big data really cre­ate value or is it some­thing that needs to be an­a­lyzed thor­oughly be­fore em­bark­ing on the jour­ney? The ideal ap­proach would be to iden­tify the right use case for big data that can pro­vide the re­quired busi­ness in­sights. This ap­proach would help banks to em­bark on the big data jour­ney that help them achieve the busi­ness ob­jec­tives and RoI.

Most large banks now have a wellor­ga­nized en­ter­prise-wide data ware­house that in­te­grates the ex­ist­ing bank­ing ap­pli­ca­tions to cater to the op­er­a­tional and an­a­lyt­i­cal needs. How­ever, with the in­tro­duc­tion of un­struc­tured data from apps, third-party data sources like weather, eco­nomic in­di­ca­tors and so­cial me­dia, it be­comes in­creas­ingly dif­fi­cult to uti­lize the ex­ist­ing tech­nolo­gies. The cost of stor­ing and pro­cess­ing vo­lu­mi­nous amount of struc­tured, semi-struc­tured, and un­struc­tured data has also in­creased ex­po­nen­tially. The ex­ist­ing tech­nolo­gies may find it tough to keep up with the real-time stream­ing and analy­ses.

This is where tech­nolo­gies like big data can play a greater role in aug­ment­ing the ex­ist­ing en­ter­prise data ware­house land­scape to gain an in-depth un­der­stand­ing. With cloud ser­vices rapidly en­ter­ing the mar­ket, com­pa­nies can make use of ser­vices like Ama­zon Web Ser­vices, Mi­crosoft Azure, etc, to min­i­mize their ini­tial in­vest­ment to de­rive proof of value be­fore em­bark­ing on a big­ger ex­er­cise.

Due to the sheer num­ber of mo­bile de­vices in use, big data can tap mo­bile data an­a­lyt­ics to bet­ter understand trends across vast pop­u­la­tions and sub­seg­ments of users. This will help im­prove en­gage­ment tac­tics and op­ti­mize the de­liv­ery of ser­vices. When an­a­lyzed ef­fec­tively, this data can pro­vide in­sights on user sen­ti­ment, be­hav­ior, and even phys­i­cal move­ment pat­terns.

Mo­bile de­vice data be­comes par­tic­u­larly use­ful for an­a­lyt­ics pur­poses when cou­pled with out­side data sources, such as weather and eco­nomic data, which al­lows the cor­re­la­tion of macrolevel trends to tar­geted sub-seg­ments of users.

An­a­lyz­ing mo­bile de­vice data is just a part of the equa­tion, how­ever big data prac­ti­tion­ers should also lever­age the mo­bile de­vices to de­liver rel­e­vant prod­ucts and ser­vices to users based on learn­ings from anal­y­sis of mo­bile de­vice data, which should also in­clude non-mo­bile de­vice data sources for ad­di­tional con­text. The anal­y­sis of be­hav­ioral pat­terns in­clud­ing search and lo­ca­tion con­texts re­quire the use of big stream­ing tech­nol­ogy to trig­ger ap­pro­pri­ate ac­tions in near-real time.

In the years to come, it would be in­ter­est­ing to see how the dig­i­tal tech­nolo­gies would take over the way we think, act, and re­spond.

Iden­tify the right use case for big data to em­bark on the big data jour­ney that helps banks achieve the busi­ness ob­jec­tives and RoI.

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