1 / 5

How Kissht Uses Analytics to Drive Better Lending Decisions

At Kissht, analytics play a pivotal role in ensuring that lending decisions are accurate, fair, and aligned with the companyu2019s goal of providing accessible credit to a wider range of customers. By harnessing the power of advanced analytics, Kissht is transforming how lending decisions are madeu2014resulting in quicker approvals, better risk assessment, and a more personalized customer experience.

Download Presentation

How Kissht Uses Analytics to Drive Better Lending Decisions

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. DATA-DRIVENCUSTOMERINSIGHTS AttheheartofKissht'slendingprocessisits abilitytoanalyzevastcustomerdatato generateactionableinsights.Ratherthan relyingsolelyontraditionalcreditscores,Kisshtgathersdatafromavarietyofsources, includingcustomerfinancialpatterns.This holisticviewofcustomerbehaviorallowsKisshttooffercreditsolutions thataremorealigned withtheborrower’sfinancialprofile.

  2. STREAMLINEDLOANAPPROVAL PROCESS Withanalyticsdrivingthedecision-making process,Kisshthasbeenabletodrastically reducethetimeittakestoapproveloans. Traditionalbanksoftentakedaysoreven weekstoprocessloanapplications,largelydue tomanualchecksandverificationprocesses. Kissht’sautomatedsystemsanalyzedatain real-time,allowingforfasterloanapprovals withoutcompromisingaccuracy.

  3. CONTINUOUSLEARNINGAND ADAPTATION Thefintechlandscapeisconstantlyevolving,and customerbehaviorschangeovertime.Kisshtuses machinelearningalgorithmstocontinuouslyimprove itslendingmodels.Asmoredataiscollected,the systemadapts,learningfrompastdecisionstomake moreaccuratepredictionsinthefuture.Thisensures thatKissht’slendingpracticesstayrelevantand effective,evenasmarketconditionsshiftornew types ofcustomersareintroduced.

  4. IMPROVINGCUSTOMERRETENTION Dataanalyticsnotonlyhelpwiththeinitiallendingdecisionbutalsoplayakeyrole incustomerretention.Byanalyzingcustomerdataovertime,Kisshtcanidentify whichcustomersarelikelytorequirefutureloansorneedassistancewithrepayment. PredictivemodelsallowKisshttoproactivelyoffersolutions,suchasloan restructuringorrepaymentflexibilitybeforecustomersfallbehind.Thisproactive approachhelpsmaintainstrongrelationshipswithborrowersandreducesthe likelihoodofdefaults.

More Related