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10 nzira Predictive Analytics inogona kubatsira iyo Banking chikamu

predictive analytics

Munyika yanhasi yemakwikwi, kukura kwevatengi nekuvagutsa kunoonekwa sebasa rakaomesesa. Ivo vanoraira pakubatwa sevanhu vamwe nevamwe uye kwete seyakajairika yakawanda. Kuti uwane pamusoro peizvi, mabhanga anga achishandisa maturusi akasiyana siyana nekufamba kwenguva. Asi nyaya dzakakosha sekuona kuvimbika kwenguva refu kubva kune vatengi vane hushamwari hwepamusoro, kuchengetedza nekukwezva mhando dzakasiyana dzevatengi kana kutengesa-kwazvino zvigadzirwa izvo chaizvo kune avo, kubiridzira kuona, kuongorora application, chikwereti uye kuunganidza kwagara kuri nzvimbo yekunetsekana. Kufanotaura analytics inouya mumufananidzo pano. Inobatsira mabhangi kutora data rakakodzera revatengi, kuona zviitiko zvekunyepedzera, kubatsira mukuongorora mashandisirwo, kutora hukama pakati pezvakafanotaurwa uye zvinotsanangurwa zvakasiyana kubva pane zvakaitika zvekare uye kurishandisa kufanotaura zvichaitika mune ramangwana.

Hedzino nzira gumi umo predictive analytics iri kubatsira chikamu chebhangi.

1. Kubiridzira

Kubiridzira kuri kuve nzvimbo yekunetsekana kukuru kune ese chikamu uye kumabhangi uye emari mafemu, zvinogona kuita mari yakawanda kwavari. Kune vamwe vanhu, zvinotonyanya kutyisa nekuti vari panjodzi yekurasikirwa nehunhu hwavo pakutanga. Digitization yakagadzira nzira yekuti matsotsi emakomputa aite chitsotsi. Nekudaro mabhangi anoda masisitimu akangwara uye maturusi ekugadzirisa iwo. Kufanotaura analytics, Machine pakudzidza, Big data, Data mining and Stream computing are few tools that help in catching these frauds. Analytics can be used to recognize frauds that are not very obvious and then predictive analytics inogona kuitwa pavari kuti vaiongorore zvakare. Kubatanidzwa kwedata, uchishandisa isina kurongeka data uye machine learning matekiniki senge anotarisirwa uye asina kudzidziswa kudzidza anogona kubatsira kuona kubiridzira mhaka ne kutevera muenzaniso.

2. Kushandisa kuongorora

Kufungidzira kuongororwa mubhangi kunogona kubatsira kugadzirisa huwandu hwakawanda hwezvishandiso, pasina kusanganisa zvakakosha, pasina kunonoka kana kukanganisa, pasina kuneta- zvese pamwe nekugara uye kugadzikana. Mhedzisiro yacho yakanyatsojeka uye ndeyechokwadi kushandiswa. Saka pakupedzisira hapafanire kuve nekufananidza pakati petsika kana manyore kuongorora uye analytics.

3. Kuwana kwevatengi & kuchengetedza

Kufanotaura analytics batsira mukugadzirisa kwekutarisa kwakanangidzirwa, zvichiita kuti zvive nyore kumabhangi kuti ione pakarepo zvikamu zvevatengi zvine mutengo wakanyanya kupindura. Nzvimbo yevatengi inogona kuwedzera kuwedzera nekuwana iyo chaiyo mhando yevatengi. Kubva pamushumo, zvakaonekwa mabhangi ayo akagamuchira predictive analytics yakave nekuwedzera kweinenge gumi muzana mumikana mitsva yevatengi kwegore.

wo predictive analytics helps banks and financial institutions retain their customers. It:

  • Inozivisa vatengi vangangoita kukanganisa vasati vapedza hukama hwavo.
  • Inochengetedza vatengi chaivo kwenguva refu.
  • Anofanotaura zviito zvichawana kuvimbika kwavo.

Kushandisa tekinoroji iyi zvakare kunobatsira kuwana iwo maitiro ehurombo uye kugadzira maprofiles evashandisi vakasiya, kuti vawane nzwisiso yekuti sei vasiya uye vawane mazano ekuti vagare vakagutsikana.

Kuchengetwa kwevatengi ndeimwe nzvimbo iyo mabhanga anoda kutarisisa zvakanyanya nhasi kuitira kudzora vatengi sapping. Vakavimbika vatengi vanoda kupihwa mubairo uye kukwezva kwevatengi kunoda kudzikiswa. Dzimwe nguva zvinononoka kuchengetedza mutengi nekuti ivo vanowanzo kuve nevazhinji vatengi uye nekudaro vanorasikirwa navo. Zviri nyore kutarisa mutengi mutsva asi izvo zvekare zvinogara zvichikosha. Kufungidzira kufungidzira kunobatsira kuona kuti ndevapi vatengi vari kuda kuchinjira kune chero rimwe bhangi uye chikonzero chiri shure kwesarudzo yavo. Inoongorora mashandiro evatengi, mashandisiro, sevhisi yapfuura uye mamwe maitiro ehunhu kufanotaura mukana wemutengi anoda kumisa masevhisi ake chero nguva munguva inotevera.

4. Kuziva tsika dzekutenga kwevatengi

Kunangisa chakakodzera chigadzirwa uye kuteedzera kushandiswa kwevatengi is a challenge before banks which they independently and in conjunction with retailers are trying to curb. With predictive analytics, banks can rapidly segregate various customer segments and replace it with highly relevant, individualized messages tailored to each customer’s profile, resulting in a higher response rate. This ultimately helps deliver the right product to the right person. As in if someone who has a history of buying gadgets then the sale of high-end gadgets can be targeted at him and in fact he would be happy to get such updates.

5. Kutengesa muchinjikwa

Kushanda-kutengesa muchinjikwa kwezvigadzirwa kunogona kuitika nekuongorora maitiro aripo evatengi kunzvimbo dzinopihwa zvigadzirwa zvakawanda. Ndezvipi zvigadzirwa zvinofanirwa kutengeswa kune avo nekudaro kufanotaura mhedzisiro kunoitwa nevanobudirira vatengesi. Uye zvese izvi zvinoguma nekubudirira mukutengesa muchinjikwa nokudaro kunowedzera purofiti nekusimbisa hukama hwevatengi. Nhasi, kuchengetedza mutengi mumwe anobatsira ibasa rakakura kumabhangi, nekudaro kutengesa-chimwe chigadzirwa kune mutengi aripo kunobatsira zvakanyanya.

Kufanotaura analytics helps examine customers’ usage, spending, and other behavior and leads to effective cross-selling of the right product at the right time. 

6. Unganidzo

Banks have a mix of customers who always pay on time and those who lag. It is a tricky task to keep a track and maintain records of all individuals and differentiate who to focus more. Kufanotaura analytics offers clear benefits in this area.  Banks can attain a better understanding of their portfolio risk and thus improve the productiveness of the collections process. Most importantly analytics helps identify the customers who would be at risk in the future and what actions banks should take to achieve positive results.

7. Zvirinani mari / kuronga kwemari

Kufanotaura analytics can help banks track the past usage patterns and the daily coordination between the in- and out-payments at their branches and ATM’s, hence predicting the future needs of their potential customers. Optimal management of liquid assets can result in their extra income and a proper analytics plan can help obtain an overview of future changes in inivhesitimendi and liquidity options.

8. Kushambadzira kugadzirisa

Kufanotaura analytics help marketers to plan marketing campaigns and programs and monitor the results closely. By providing an insight into customer behavior and attitudes, and a complete, current view of your customers, analytics help your marketing team deliver the right message at the right time to the right customers.

9.Kutenga Kweupenyu Hwekukosha (LTV)

Kukosha kwevatengi kwehupenyu hwevatengi ndiko kwenguva yakareba sei masangano ari kukwanisa kuchengetedza vatengi vavo. Kuziva kuti ndiani akanakisa vatengi, achivaita vari nani munzira dzakasiyana, uye kana iwe uchinge waakunda, kuwana kuvimbika kwavo, inzvimbo shoma dziri kumabhangi dziri kutarisa.

Kufanotaura analytics inobatsira:

  • Ziva kuti ndeapi vatengi anofanirwa kuve anotarisisa ezvekutsva zvevatengi zvekuita.
  • Ziva izvo zvakapfuura zvinhu zvakawedzera kudzoka pane zvinoitwa nevatengi munguva yakapfuura.
  • Shandisa iro ruzivo kuti unzwisise kuti sei vatengi vakapindura kune mamwe mameseji uye kukwidziridzwa.

10. Mhinduro dzemhinduro

Feedback management is really important. Kufanotaura analytics allows banks and financial firms to keep up their relationship with the customers by giving them the right services and products for their need and matching individual preferences in the most sorted way.

NewGenApps yanga ichipa Big Data nezvimwe data science masevhisi ekutanga-kumusoro uye mabhizinesi mumatanho akasiyana siyana, kusanganisira emabhengi & emari masangano. Kana uchida kunzwisisa sei predictive analytics inogona kubatsira kukura bhizinesi rako, bata.

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