更好的人工智能合规方法++A+Better+Approach++to+AI+for+Regulatory++Compliance

Copyright©2022InMoment,Inc.Allrightsreserved.

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ABetterApproach toAIforRegulatory Compliance

PAGE02

ABetterApproachtoAIfor

RegulatoryCompliance

Companieswithregulatorycomplianceburdensareflockingtoartificial

intelligence(AI)fortime-savingsand

costreductions.Themoneyinvolvedis

staggering:In2021,HealthcareAIfundingreached$8.5billionacross366dealsatanaverageof$30millioneach.1

Thereasonsfortheseinvestments?AI

candelivertheglobalhealthcaresystemsandservicesupto$906billionofvalueannually,2andAIcoulddeliverthe

globalbankingindustryupto$1trillion

additionalvalueannually.3AndPwC

predictsthatAIcouldcontribute$15.7

trillion4totheglobaleconomy.

Butthesebignumbersdon’teliminatethefactthateverymonthbringsnewarticlesandthink-piecesaboutburstingtheAI

hypebubble.So,beforeyoupaytoomuchattentiontothosetypesofarticles,letustellyouhowourthoughtsandexperienceswarrantamuchbetterapproachtoAIforregulatorycompliance.

PAGE03

AIforCompliance

RequiresMoreThanAI

BACKGROUND

InMomentacquired

Lexalytics,thecompany

thatwasfirst-to-market

withacommercial

sentimentanalysisengine.

Sincethen,we’vebeen

pushingthelimitsofnaturallanguageprocessing(NLP),machinelearning(ML)andartificialintelligence

Thetruthisthat“artificialintelligence”isjustatool.Itdoesn’treally“do”anything

onitsown.WhatmattersishowyoucombineAIwithothertechnologiesandthe

expertsthatknowyourbusiness.Inafieldlikeregulatorycompliance,forexample,thechallengesinvolvedcanvarywildlybyindustryandcountry.So,inordertoaddress

theseproblems,youneedacombinationofthreetechnologiesandhumanexpertise:

SEMI-

STRUCTURED

DATAPARSING

NATURAL

LANGUAGE

PROCESSING

MACHINE

LEARNING

ANDAI

Thecomplexstructureofregulatoryandlegaldocumentsmeansthateachof

thesetechnologieswillfallshortifit’snotsupportedbytheothertwoandmany

timeswithahelpfulhumaneye.Butmostoff-the-shelfanalyticstoolsandvendorsuseonlyoneortwoofthethree,leavingvaluabledatabehindoroverlooking

criticalcontext.InMoment,ontheotherhand,hasdevelopedallthreetoolsintoacomprehensiveplatformandhasateamofhighlytrainedexperts.Webuildsemi-customapplicationsthatsolvespecific

compliancechallengesforourclients.

Therestofthispaperwillexplain:

1.WhyMany“AIforCompliance”

SolutionsFallShort

2.WhatYouNeedtoKnowtoBuild“AI

forCompliance”

3.ThreeReal-worldExamplesofEffectiveAIforCompliance

PAGE04

WhyAIOftenFallsShortin

RegulatoryCompliance

Akeyfactortothesuccess

ofAIforcompliance

ishavingtheright

technologiesinplaceto

extractdatafromlegal

documentsthatarecomplex

andhardtoanalyze

Everyorganizationissubjecttosomeregulation.Healthcareproviders,

pharmaceuticalcompanies,andfinancialservicesfirmsfaceparticularlyheavy

burdens.Butdespitemassiveinvestmentandclearmarketopportunities,

technologysolutionsforregulatory

complianceareprovingdifficultto

develop.Why?

Inshort:Becausethecomplexstructureofthedocumentsinvolvedmeansthat

traditionaldataanalyticstechniquesaren’tabletoextractandunderstandallofthedatathatcompliance

professionalsrelyon.

Legaldocumentsarefullofboth

structuredelements(suchastablesandsubheaders)andunstructuredelements(free-standingtextsections,descriptivelists,orcommentaryoninformation

withintables).Twodocumentsmay

shareaformat,suchasacontract

template.Buttheunstructuredtext

sectionsarenotstandardized,and

datamaydifferwildlyevenwithinthestructuredelements.

Thisdistributionofdatamakesitverydifficulttocreateasinglepieceof

softwarethatcanautomaticallyidentify

andextracteverythingofvalue.Most

existingsystemsuseoneortwoofthe

threetechnologies:semi-structureddataparsing,naturallanguageprocessing,andmachinelearningandAI.

Butthetruthisthatnoneofthesecandotheentirejobonitsown:

•Acommercialsemi-structureddata

parserwon’tunderstandthemeaningofthetextitextracts

•Anopen-sourceNLPengine

won’tunderstandhowstructuredelementsfitin

•AnAItrainedonregulatorydocu-mentscanchokewhenpresentedwithnewcontenttoanalyze

Toclarifythislastpoint:AIrelieson

learningfromexamples.Butregulatorycomplianceoftendealswithdocumentswheretheformatchangesbutthe

informationwithinremainsconsistent.Inthesecases,anAIsystemmaystumble

becausetheinformationit’saskedto

processlooksverydifferentfromthedataitwastrainedon.

PAGE05

TheKeytoBuilding anEffectiveAIfor

RegulatoryCompliance

Aswediscussedearlier,large-scale

AIsystemsthatpromisetoreplace

humansareturningouttobeunreliableordownrightdangerous.Thereal

opportunityhereistocreatetechnologysolutionsthathelphumansdotheirjobsbetterandfasterbyalleviatingtedious,repetitivetasks.

TobuildanAIsolutionthatactuallyhelpshumanswithregulatorycompliancetasks,youneedtounderstandthreepoints:

1.Regulatorycomplianceisvery

complex,butgenerallymeans

confirmingsomething:whethera

particulardocumentiscompliantor

thatyourorganizationisproperly

trackingandadheringtoshifting

regulatoryupdates

2.Legal,medical,andfinancial

documentshaveimportant

informationcontainedwithinboth

structuredelements(tablesandlists)andunstructuredtext

3.Traditionaldataanalyticstechniques

fallshortinregulatorycompliance

becauseidentifyingandextracting

allofthedatafromalegaldocumentrequiresmorethanAI

e

InMomentisoneofahandfulofcompa-nieswhohasboththetechnologystackandexperiencerequiredhere.Muchliketailoringanoff-the-racksuit,weuseAItocustomizeourprovenNLPplatformtomeetourclients’uniquerequire-

ments.Wedon’tbelieveinreplacing

humansor“solving”anentireindustry.Instead,wehelpourclientsdotheir

workbetterandfaster.

We’vebuiltAIapplicationsto:

•Helpmedicalcodingteamskeepup

withmonthlyMedicaidupdatesby

extracting,structuring,andinserting

diagnosticandprocedurecodesinto

anEHR

•Acceleratemedicalinformation

officesbyguidingsupportagentsto

therightanswers

•Reducenon-complianceriskby

It’snotAIorhumans,it’sAIfor

humanstohelpbusinesseswork

ensuringthatfinancialadvisorsmake

requireddisclosuresandappropriate

betterandfaster

recommendations

T

u

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codersstruggletokeepup.NBCNews

foundmedicalclaimerrorratesrangingfrom7%to75%.6Medicaidhasimproved

its2010errorrateof42%,7buttheystill$31.6billiontocodingerrorsin2018,morethan$230billionovera6year

lostand

period.8Atonepoint,Medicaidsued

UnitedHealthGroup,9alleginghundredsof

millionsofdollarsinover-billing.

Fully-automated

medicalcodingsolutions

facemajorhurdlesandmayneverbe

viable.Instead,thisisaperfectexampleofwheretechnologycanhelphumans,not

easingworkloads

and

replacethem,by

errorrates.

reducing

EXAMPLE1

HelpingMedicalCodingTeamsKeepUp

WithMedicaidUpdates

Healthcareorganizationsemployteams

ofprofessionalmedicalcoders(Glassdooraveragesalaryof$37,000)5toread

monthlyMedicaidupdatesandmanuallyenterthenewinformationintoEHRsandotherdatabases.Thesedocumentsmaybedozensofpageslongandeachstate’s

THECOMPLEXITIESOF

MEDICALCODINGCANCREATE

HURDLESFORAISYSTEMS

Theprocessesanddocumentsinvolved

inmedicalcodingcreatebighurdlesforanyAIsystem.AsdemonstratedinFigure

Justlikeahumancoder,anyAIsystem

mustidentifyandextractallofthis

informationandthenrelateeachdata

pointtotheothers(whichtreatmentcodegoeswithwhichdiagnosiscodes).In

addition,anyautomatedsystemmustbeabletoidentifyfootnotesandaddendums

Medicaidsystemdistributesitsownuniqueguidelines.

Thetaskismonumentalandhuman

1,relevantdiagnosticandprocedural

codesandupdatesarecontainedwithinamixofstructuredelements(tables)andunstructuredelements(plaintext).

thatclarifyspecialcasesandexceptions,

andthenconnectthemtotherelated

diagnosticorproceduralcodes.

2.2.25TOTALPARENTERALNUTRITION(TPN)SOLUTIONS

PAGE07

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processingtoanalyzetheunstructuredtext,andmachinelearningtounderstand

broughttogethertherighttechnology

andtoolstohelphumanmedicalcoders

HOWAIHELPS:

Buildinganartificialintelligence

systemtodirectlyanswerpatient

questionswouldbeaherculeantask,

evenwithoutthethreatoflawsuits

whenitgotthingswrong.

Instead,AIcansupportmedical

informationofficesbyhelping

humanagentsanswerquestions

fasterandmorereliably.

EXAMPLE2

HelpingMedicalInformationOfficesAnswerPatientQuestionsFaster–SavingThousandsofPeopleHours

MedicalInformationOffices(MIO)are

responsibleforsettingupasystemto

fieldandrespondtopatientquestions

aboutdrugs,bothduringtestingand

afterrelease.Giventhatpeople’slives

maybeatstake,it’simperativethatevery

Oursemi-customapplicationisbuilton

ourplatformandleveragesAItrained

withourPharmaceuticalIndustryPack.

Oursystemcanimmediatelyunderstandwhatconditions,drugs,ailments,orissuesacustomeriscallingaboutanddeliver

OurAIhelpsmedicalinformationoffices

savethousandsofpeople-hoursand

dollars,allwhilereducingnon-compliancerisk.Andwhilethissystemwasdevelopedforacall-centerenvironment,italso

showsgreatpromiseforuseatallpatient

questionbeansweredinaconsistentandcorrectmannereachtimeit’sasked.

Toensurecompliance,MIOsdrawup

detailedFrequentlyAskedQuestions

(FAQ)files.Patientquestionsareroutedtoacallcenter,sometimesoutsourced,

whereagentsreferencetheFAQto

answereachquestion.ButthecomplexityoftheseFAQsmeansthateachagent

cantakemanyminutestoanswerasinglequestion,evenwhenthesamequestiongetsaskedmanytimesaday.Inone

ofourdatasets,80%ofdrug-related

medicalinformationquestionsrelatetojust20%oftheFAQ.

Buildinganartificialintelligenceto

directlyanswerpatientquestionswouldbeaherculeantask,evenwithoutthe

threatoflawsuitswhenitgotthings

wrong.Instead,AIcansupportmedicalinformationofficesbyhelpinghumanagentsanswerquestionsfasterand

morereliably.

touchpoints,includingemails,socialmediacomments,chatbots,orevenaphysician’sdesknotes.

acorrectresponsefortheoperator,all

duringthecall.

Forexample,apatientmightcallin

asking,“Howmuchofthispainkiller

shouldItake?I’ma180-poundguy.”

Oursystemcantearthisdownto

understandthatthequestionrelates

todosageofapainkillerforanadult

male.Basedonthisanalysis,wecan

immediatelydirectthehumanagentto

theproperanswer.(Note:thisisamade-

upexampletoillustratehowandwhere

thesystemworks.)

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COMPLIANCESPENDINGINFINANCIALSERVICES

•$270billionindustryspendingoncompliance

•94%increaseincompliancecosts

•10-15%ofworkforcededicatedtogovernance,riskmanagement,andcompliance

•Average10%ofrevenuespentoncomplianceby2022

THECOSTSOFNON-COMPLIANCE

•45xincreaseinregulatoryfinesandsettlementsfrom2009-14

•Upto$19.1millionlostrevenue

•$1.1millionto$20.4millionbusinessdisruption

•Average$3.7millioninproductivityloss

PAGE10

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Manyfirmsrelyonspot-checks

andkeywordsearchestoconfirm

compliance.Butlookingforindividual

productivitylossandpenalties.

McKinseyfounda45xincreasein

regulatoryfinesandsettlementsover

5years.

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PA

GE11

UsingAItoImprove

ExistingProcesses

Ratherthantryingtobuildanend-to-end,failure-prone“AIfordisclosure

compliance,”InMomentfocuseson

improvingexistingprocesses.Oursystemempowersfinancialauditorstoreviewalloftheirdocumentsalmostsimultaneously,insteadofspot-checkingahandful.This

substantiallyreducesnon-compliance

riskforfinancialservicesfirmsandbanks.

Wecombineoursemi-structureddata

parserwithtextanalyticstoquickly

analyzelongfinancialdocuments

andextractallofthedata,wherever

it’slocated:legaldisclosures,asset

allocationtables,statementsofadvice,clientroles,andmore.Then,ournaturallanguageprocessingalgorithmsparse

theunderlyingstructureandmeaningof

theinformation.Thisenablesustomakecomplexconnectionsbetweendatapointswherevertheyappearinthedocument.

Finally,weuseartificialintelligenceto

structurethisdataandprepareitfor

furtheranalysis.Thenatureofthisanalysiscanvarybasedonyourgoalsandexistingtechnologystack.Forexample,wecan

exportthisdataintoanExcelspreadsheet.Or,asinFigure3below,wecanjustgiveyouasimpletextfile.

Inthisexample(mockedupfor

demonstrationpurposes),theoutputof

ourapplicationshowsataglancewhetherproperdisclosuresweremade,highlightsown-productrecommendations,andflagssuspectedcasesofpredatorylending

techniquesforfurtherreview.

BALANCEDINVESTMENTOBJECTIVE:

•Youwishtoadoptalimitedportfoliotoprotectyoufrominflationandtax

•Youhavealimitedunderstandingoftheinvestmentmarketsandtheiroperation

•Whenyoumakeafinancialdecision,youaremorefocusedonminimizingpossiblelosses

•Youcanacceptalowlevelofvolatilityinthevalueofyourinvestments

•Youarealowrisktakerandpreferlowlevelsofinvestmentrisk

RECOMMENDEDSTRATEGY(Toaddressyourstatedneeds,goals,andobjectives,werecommendthefollowingstrategytoyou):

Smith,youhaveinformedusthatyouwillreceivean

inheritanceofapproximately$550,000.Duetothis,yourAgePensionwillceaseandthereforeyouneedtoreplacethelossofpensionincomewithadrawdownfromthe

inheritancefunds.Smith,werecommendyouinvestall($550,000)ofavailablefundsfromyourinheritance

throughourHigh-YieldSelf-ManagedTechFund.This

allowsyoutomaximizethereturnonyourinvestmentbyactivelyinvestinginself-selectedtechnology

companiesthatareleadersintheirfields.

Fig.3|UsingInMomenttoflagwherearecommendationgoesagainsttheclient'sorganization

Summary

Regulatorycomplianceisacomplicatedareathatvarieswildlyfromindustry

toindustryandcountrytocountry.

Thenatureofthedocumentsinvolved

meansthattobuildan“AIforregulatorycompliance,”youneedmorethanjustAI.Infact,youneedacombinationofsemi-structureddataparsing,naturallanguageprocessing,andmachinelearningandAI.

Despitemassiveinvestment,many“AIforcompliance”toolsfallshortbecause

ausefulregulatorycompliancesolutionrequiresallthreeofthesetechnologies,notjustoneortwoandadditionalhumanexpertiseandintelligence.

InMomentcombinesthenecessary

technologystackwithanexperienced

professionalservicesstafftobuild

semi-customapplicationsthatsolve

specificregulatorycomplianceproblems

inhealthcare,biotechnology,financial

services,pharmaceuticals,andmore.

SEMI-

STRUCTURED

DATAPARSING

NATURAL

LANGUAGE

PROCESSING

MACHINE

LEARNING

ANDAI

1.

/reports/CB-Insights

_Artificial-Intelligence-Report-Q3-2021.pdf

2.

HYPERLINK"/