Le de s ca ow use co ve satio al p ompts to que y a p op ieta y isk data moat built f om mo e tha 340 millio loa applicatio s a d mo e tha 600 billio att ibutes to ide tify “headli e” po tfolio isk, spot eme gi g patte s of f aud ac oss the i dust y a d u Age tic Fo e sic F aud Reviews o a y o all loa files
SAN DIEGO, Oct. 16, 2026 (GLOBE NEWSWIRE) — Poi t P edictive today lau ched P edicto Age ts™, a Deep I tellige ce AI f aud tool that gives le de s th ee ew ways to ma age f aud befo e fu di g a d du i g se vici g, cove i g the applicatio s they eceive a d, fo auto le de s, the deale s who se d them.
P edicto Age ts d aw o data f om mo e tha 650 co so tium le de s, i cludi g mo e tha 340 millio applicatio s a d $6.0 t illio i isk-assessed loa s.
P edicto Age ts wa le de s about f aud schemes befo e they ca damage a le de ’s eputatio , let executives que y the applicatio histo ies, loa pe fo ma ce, egative files a d f aud patte s ac oss the e ti e co so tium to optimize po tfolio a d deale ma ageme t, a d tu a fo e sic f aud eview that o ce took up to a hou i to o e that takes seco ds.
Le de s usi g P edicto Age ts get th ee immediate be efits:
Detecti g f aud i gs befo e they make headli e ews Plai -la guage a swe s o loa pe fo ma ce, egative files, f aud t e ds a d deale isk Age tic Fo e sic F aud Reviews i seco ds
Ba ks, c edit u io s a d fi a ce compa ies ca use the solutio to automate the ide tificatio of f aud i gs a d f aud patte s ac oss the i dust y, deeply esea ch thei deale s’ activity ac oss the co so tium a d supe cha ge thei ma ual f aud eview teams to cove mo e loa s.
The losses that hu t most a e ofte the o es that e d up i the ews. A deale pushi g falsified paystubs th ough doze s of deals, a i g of sy thetic ide tities buildi g c edit fo a bust-out, o a st aw bo owe scheme sp ead ac oss seve al le de s ca cost millio s a d d aw atte tio f om egulato s a d epo te s.
P edicto Age ts eview eve y co so tium applicatio i eal time fo ide tity, i come, employme t, deale isk, st aw bo owi g, c edit washi g a d bust-out activity. Whe they fi d applicatio s f om a si gle le de o f om multiple co so tium membe s that should be u elated but a e tied togethe by a commo th ead (such as pho e umbe , employe , add ess o deale ), they flag the patte so the le de ca act befo e the mo ey goes out.
“The f aud that e ds up i a headli e usually leaves a t ail mo ths ea lie ,” said F a k McKe a, Co-Fou de a d Chief I ovatio Office at Poi t P edictive. “P edicto Age ts show the u de w ite that t ail while the patte is still developi g, ot afte the losses pile up.”
Sco es a d ale ts desc ibe o e applicatio at a time. P edicto Age ts give isk a d f aud teams di ect access to que y data eposito y i tellige ce, which cove s applicatio histo ies, loa pe fo ma ce, egative files a d f aud patte s f om mo e tha 650 le de s, alo g with thei ow co t ibuted loa s. Teams ca ask questio s about thei whole po tfolio i plai la guage a d get a swe s immediately so they ca take actio .
A chief le di g office ca use P edicto Age ts to tu e u de w iti g st ategies a d ules to bette ta get ea ly payme t default isk. Fo example, the executive ca ask which pa ts of the book a e p oduci g loa s that default i the fi st six to 12 mo ths, the tighte ules o those segme ts without slowi g dow good bo owe s.
Auto le de s ca also esea ch deale activity i depth to make mo e i fo med decisio s o how to ma age each deale . A a alyst ca ask how a deale ’s applicatio s pe fo m ac oss the e ti e co so tium a d whethe the same employe s, pho e umbe s o add esses keep appea i g, the decide whethe to add eviews, cha ge te ms o g ow the elatio ship.
Be chma ki g is built i as well. A c edit u io ca compa e its ea ly payme t default a d f aud ates agai st a simila coho t of co so tium le de s to see whe e its membe s’ loa s pe fo m bette o wo se tha the ma ket, a d whe e the gap is widest.
A full ma ual fo e sic eview of o e loa file ca take a expe ie ced a alyst 20 mi utes to a hou . Age tic Fo e sic F aud Reviews f om P edicto Age ts p oduce the same ki d of epo t i seco ds, givi g a small f aud team the each of a much la ge o e.
Behi d each eview a e the P edicto Age ts, specialists t ai ed by the Poi t P edictive f aud team o t illio s i isk-assessed loa s. Each age t applies what the team has lea ed f om those loa s to its ow a ea, such as ide tity, i come a d employme t, deale isk, st aw bo owi g, c edit washi g a d bust-out activity.
Eve y epo t lays out the age ts’ fi di gs by eview a ea, the suppo ti g evide ce a d what to do ext. If a file eeds a close look, the epo t spells out what to ve ify befo e fu di g, a d if the file checks out, it explai s why the loa ca move ahead.
“Le de s have always ma aged isk with o ly the data i side thei ow walls,” said Tim G ace, Co-Fou de a d CEO of Poi t P edictive. “P edicto Age ts put the la gest f aud co so tium i the wo ld behi d this ew class of Deep I tellige ce AI we have c eated, a d this will t a sfo m how f aud is ma aged ac oss the i dust y. We’ e p oud to lau ch this g ou db eaki g ew f aud ma ageme t app oach.”
Fo mo e i fo matio , co tact i fo@poi tp edictive.com.
Poi t P edictive powe s a ew level of le di g co fide ce a d speed th ough a tificial i tellige ce, powe ful data i sight f om ou p op ieta y data eposito y, a d decades of isk ma ageme t expe tise. The compa y’s data a d tech ology solutio s quickly a d accu ately ide tify t uthful a d u t uthful disclosu es o loa applicatio s. As a esult, le de s ca fu d the majo ity of loa s without equi i g o e ous docume tatio , such as paystubs, utility bills, o ba k stateme ts, imp ovi g fu di g ates while educi g ea ly payme t default losses. Subseque tly, bo owe s get loa s faste , a d le de s ealize a mo e p ofitable bottom li e. Fo mo e i fo matio , please visit poi tp edictive.com.
Media Co tact: Jo da Za e, Jza e@Poi tP edictive.com
