
International Research Journal of Engineering and Technology (IRJET) e-ISSN:2395-0056
Volume: 11 Issue: 05 | May 2024 www.irjet.net p-ISSN:2395-0072
International Research Journal of Engineering and Technology (IRJET) e-ISSN:2395-0056
Volume: 11 Issue: 05 | May 2024 www.irjet.net p-ISSN:2395-0072
Akshay Sekar Chandrasekaran
Texas A&M University, USA ***
ABSTRACT:
TheareaofcybersecurityischangingquicklyasGenerativeArtificialIntelligence(GenAI)isbeingusedinsecurityengineering and architecture, especially in Governance, Risk Management, and Compliance (GRC). This paper talks about how GenAI technologies can be used to make GRC processes more effective and efficient. It also talks about how this new way of doing things is changing how companies handle possible security risks. GenAI systems use advanced machine learning and AI algorithms to offer automated policy enforcement, predictive risk management, and real-time tracking of compliance. The paperuses real-lifeexamplesanddata toshowhowGenAIcanhelp withGRC.Italsotalksabout whatthis technologycould meanforbuildingsecuresystemsthatareresilientandadaptableinthefuture.
Keywords: GenerativeArtificialIntelligence(GenAI),Governance,RiskManagement,Compliance,PredictiveAnalytics
Recently, Generative Artificial Intelligence (GenAI) hasmade a lot of progress, which has led to new ways to improve safety, especially in the areas of Governance, Risk Management, and Compliance (GRC) [1]. A lot of companies are using GenAI technologies, which are driven by advanced machine learning and AI algorithms, to make GRC processes easier and help companies better predict, reduce, and handle possible security risks [2]. 85% of companies plan to invest in AI-driven GRC solutionsby2025,showingthatmoreandmorepeoplearebecomingawareofGenAI'spromiseinthisarea[3].
International Research Journal of Engineering and Technology (IRJET) e-ISSN:2395-0056
Volume: 11 Issue: 05 | May 2024 www.irjet.net p-ISSN:2395-0072
The global market for GRC solutions powered by AI is projected to grow at a rate of 22.3% per year from 2020 to 2027, reaching $7.2 billion [4]. Risk assessment needs to happen in real-time, compliance processes need to be automated, and onlinethreatsaregettingmorecomplicated.78%ofleaderssurveyedbyDeloittesaidthattheircompanieshavealreadyused AI-basedGRCsolutionsorplantousethemwithinthenext12months[5].
GenAI'sabilitytolookthroughhugeamountsofdatafromdifferentsources,likenetworklogs,securityalerts,andcompliance reports, to find possible risks and strange behavior is one of its best features in GRC [6]. GenAI systems can pull out useful data, find trends, and give security teams useful insights by using natural language processing (NLP) and machine learning algorithms[7].Thisletsbusinessesdealwithpossiblethreatsaheadoftimeandkeeptheirsecuritystrong.
GenAI can also make compliance management a lot better by automating the reporting and tracking of regulatory requirements.DataprivacylawsliketheGeneralDataProtectionRegulation(GDPR)andtheCaliforniaConsumerPrivacyAct (CCPA) are getting harder for businesses to follow because they are so complicated [8]. GenAI-powered solutions can constantly watch how data flows, find possible gaps in compliance, and make reports to show that regulatory standards are beingmet.Thislowerstheriskoffinesanddamagetothecompany'simage[9].
However,theuseofGenAIinGRCalsobringsupworriesabouthowopen,comprehensible,andaccountableAI-baseddecisionmaking processes are [10]. As GenAI systems get smarter, it is very important to make sure that their results can be understoodandareinlinewithcompanypolicies andmoralconcerns.GenAIsystemsneedtobemoreopenandaccountable. To do this, researchers and practitioners are working on things like creating frameworks for AI that can be explained and puttinginplacestrongcontrolsystems[11].
PercentageoforganizationsplanningtoinvestinAIdrivenGRCby2025 85%
Global market for AI-powered GRC solutions in 2027 $7.2billion
CAGR of the global market for AI-powered GRC solutions(2020-2027) 22.3%
Percentage of executivesplanningto implementAIbasedGRCwithin12months(2021) 78%
KeyadvantageofGenAIinGRC
TechnologiesleveragedbyGenAIsystems
Areas where GenAI enhances compliance management
Challenges faced by organizations in ensuring compliance
Analyzingvastamountsofdatatoidentifypotentialrisks
Natural Language Processing (NLP) and Machine Learning(ML)
Automating monitoring and reporting of regulatory requirements
Increasing complexity of data privacy regulations (e.g., GDPR,CCPA)
ConcernsraisedbytheadoptionofGenAIinGRC Transparency, explainability, and accountability of AIdrivendecision-makingprocesses
Methods being explored to enhance transparency andaccountabilityofGenAIsystems
Developing explainable AI frameworks and implementingrobustgovernancemechanisms
Table:KeyMetricsandInsightsontheAdoptionofGenerativeAIinGovernance,RiskManagement,andCompliance[1–11]
International Research Journal of Engineering and Technology (IRJET) e-ISSN:2395-0056
Volume: 11 Issue: 05 | May 2024 www.irjet.net p-ISSN:2395-0072
In the area of Governance, GenAI systems can automatically apply policies and check for compliance with standards. This makessurethatanorganization'sactionsareinlinewithbothinternalandexternalrules[12].Bylookingathugerecords in real-time,GenAIcanfinderrorsorinconsistenciesrightaway,sotheycanbefixed[13].Abigtechcompanydidacasestudy thatshowedusingGenAIingovernancecutincidentsofnon-complianceby70%andincreasedpolicycomplianceby95%[14]. This model of proactive governance not only lowers the risk of non-compliance but also helps people make better decisions [15].
GenAIcancreateandkeeppolicydocumentsup-to-date,andcompletepolicydocuments,whichisoneofitsmostusefuluses in governance. GenAI systems can make policy statements that are clear, concise, and up-to-date by using natural language generation (NLG) methods. This is possible because regulations and organizational needs are always changing [16]. A major professionalservicesfirmdidastudythatshowedcompaniesthatusedGenAItocreatepoliciescouldupdateandsendpolicy documentstoalloftheirbusinessgroupsmorequicklyandcorrectly[17].
In addition, GenAI can improve governance by making training and communication more efficient. GenAI systems can help employees understand and follow governing rules better by creating personalized learning experiences and interactive training material [18]. A well-known professional services company did a pilot project that showed GenAI-powered training programsraisedscoresonhowwellemployeesunderstoodpoliciesby25%andraisedengagementlevelsby30%[19].
GenAIis beingusedingovernment,butitalsobringsproblems, especiallywhenit comestoaccountabilityand moral issues. Since GenAI systems make decisions on their own, it is important to set clear rules and oversight systems to make sure that theiractionsareinlinewithcompanygoalsandsocialnorms[20].ResearchersarelookingintoframeworksforresponsibleAI governance.OneexampleistheIEEEGlobalInitiativeonEthicsofAutonomousandIntelligentSystems,whichgivesguidelines fortheethicalcreationanddeploymentofAIsystems[21].
1:QuantifyingtheBenefitsofGenerativeAIinGovernance:Compliance,PolicyManagement,andTrainingMetrics[12–21]
International Research Journal of Engineering and Technology (IRJET) e-ISSN:2395-0056
Volume: 11 Issue: 05 | May 2024 www.irjet.net p-ISSN:2395-0072
Fromariskmanagementperspective,GenAIchangestheoldwaysofdoingthingsbyusingpredictiveanalyticstofindpossible security vulnerabilities and risks [22]. By looking at past data and current trends, GenAI models can predict possible attack vectors and offer ways to stop these threats before they happen [23]. A major professional services firm's study found that whencompaniesusedGenAIforrisk management,securitybreacheswentdownby 45%andtheaccuracyoffindingthreats went up by 60% [24]. This ability to predict the future lets businesses take a more strategic approach to risk management, puttingmoreresourcesandeffortintofixingthemostimportantweaknesses[25].
OneimportantuseofGenAIinriskmanagementisfindingandstoppinginsiderthreats.Insiderattacks,inwhichemployeesor trustedpeopleinsideacompanydobadthings,arenotoriouslyhardtospotwithnormalsecuritymeasures[26].Ontheother hand, GenAI systems can look for trends in user behavior, network activity, and data access logs to find strange things and possibleinsiderthreatsrightaway[27].AbigtechcompanydidacasestudythatshowedusingGenAItofindinsiderthreats cutthetimeittooktofindandstopeventsby80%whilereducingthenumberoffalsepositives[28].
Another way GenAI can improve risk assessment is by automatically finding and ranking weaknesses in an organization's infrastructure. By looking at network configurations, software inventories, and threat intelligence feeds, GenAI systems can make thorough risk profiles and suggest ways to fix issues [29]. A major professional services firm did a study that showed thatwhencompaniesusedGenAIforriskassessment,ittookthemhalfaslongtodothoroughriskanalyses,andtheaccuracy andconsistencyoftheirriskscoresimproved[30].
GenAIisused for risk management,whichbrings new problems, especiallywhen it comesto data safetyandsecurity.GenAI systems need to see private information to evaluate risks and predict threats, so it is important to put in place strong data security measures and follow all the rules [31]. Furthermore, the fact that bad people could attack GenAI models using techniques like data poisoning or model inversion shows how important it is to keep studying safe and reliable AI systems [32].
2:EnhancingRiskManagementwithGenerativeAI:QuantifyingtheImpactonSecurity,ThreatDetection,andRisk Assessment[22–32]
International Research Journal of Engineering and Technology (IRJET) e-ISSN:2395-0056
Volume: 11 Issue: 05 | May 2024 www.irjet.net p-ISSN:2395-0072
GenAImakesiteasiertofollowmanydifferentsetsofruleswhenitcomestocompliance[33].GenAIcanunderstandandkeep an eye on changes in regulatory standards across different areas by using natural language processing (NLP) and machine learning [34]. A study by PwC found that compliance systems driven by GenAI were 90% accurate at finding changes to regulations and cut compliance-related mistakes by 75% [35]. This makes sure that efforts to comply are up-to-date and thorough,whichlowersthechanceofgettingfinedorfacingotherlegalproblems[36]
One important way that GenAI is used in compliance is to automate processes for due research. More and more, companies havetodoalotofresearchontheircustomers,sellers,andbusinesspartnerstostopmoneylaundering,fundingforterrorism, and other illegal activities [37]. GenAI systems can look through huge amounts of structured and unstructured data from differentsources,likenewsstories,financialrecords,andsocialmedia,tofindpossibleredflagsandhigh-riskentities[38].An analysisbyKPMGofacasestudyshowedthatusingGenAIinduediligenceprocessescutdownonmanualworkby60%while makingriskratingsmoreaccurateandfaster[39].
GenAI can also make the processes of compliance reports and documentation easier. Regulatory authorities often ask businesses to give thorough reports on their compliance activities, which can take a lot of time and resources [40]. GenAI systems can make compliance reports instantly by pulling relevant data from different sources. This makes sure that all reportingrequirementsaremetconsistentlyandcorrectly[41].AstudybyDeloittefoundthatcompaniesthatusedGenAIfor compliancereportingcutthetimeittooktomakeandsendregulatoryfilingsbyhalfandloweredthechanceofmistakes and missinginformation[42].
However, using GenAI for compliance also makes people worry about how easy it will be to understand and explain the choicesmadebyAI.Becausechoicesaboutcompliancecanhavebiglegalandfinancialeffects,GenAIsystemsmustgiveclear andcheckablereasonsfortheirresults[43].ScientistsarelookingintowaystomakeGenAImodelseasiertounderstand,such as rule-based explanations and attention processes [44]. When it comes to compliance apps, this will help build trust and responsibility.
The accuracy rate of GenAI-powered compliance systems in identifying regulatory changes 90%
Reductionincompliance-relatederrorswithGenAI-poweredcompliancesystems 75%
ReductioninmanualeffortforduediligenceprocesseswithGenAIimplementation 60%
ReductionintimerequiredtoprepareandsubmitregulatoryfilingsusingGenAIfor compliancereporting 50%
Table2:GenerativeAITransformingCompliance:MeasurableImprovementsinRegulatoryChangeIdentification,Error Reduction,DueDiligence,andReportingEfficiency[33–44]
Real-world Applications:
● Financial Sector:
○ A big American multinational investment bank put in place a GenAI system to keep an eye on staff communications.Thiscutdownonfalsepositivesby95%andincreasedthenumberofpossiblecompliance violationsfoundby50%[45].
International Research Journal of Engineering and Technology (IRJET) e-ISSN:2395-0056
Volume: 11 Issue: 05 | May 2024 www.irjet.net p-ISSN:2395-0072
○ GenAI was used to improve the anti-money laundering (AML) processes of a major American multinational investment bank and financial services company. This led to a 75% increase in the detection of suspicious behavioranda40%decreaseinfalsepositives[46].
● Healthcare Industry:
○ A well-known American health insurance company used GenAI to safeguard patient data privacy. The solutionwas90%accurateatfindingandpreventingpossibledatabreaches[47].
○ Awell-knownAmericannon-profitacademicmedicalcenterputinplaceaGenAI-poweredsystemtokeepan eye on and make sure that healthcare rules were followed. This led to a 60% drop in rule violations and a 45%riseinefficiency[48].
● Energy Sector:
○ A large American oil and gas company used GenAI to simplify its environmental, health, and safety (EHS) compliance procedures. As a result, 80% less manual labor was required, and incident response times decreasedby70%[49].
○ A sizable American international energy company used GenAI to keep an eye on its global supply chain in real-time.Thisreducedthird-partyrisksby55%andincreasedsuppliercomplianceby65%[50].
BENEFITS:
● Cost Savings:
○ Following the use of GenAI in GRC, a major research and advisory firm found that compliance costs could dropby30%andriskmanagementcostscoulddropby20%[51].
○ Accordingtoawell-knownprofessionalservicesnetwork,companiesthatusedGenAI-poweredGRCsolutions cuttheircompliance-relatedcostsby25%andtheirriskmanagementcostsby35%,respectively[52]
● Improved Efficiency:
○ Awell-knownmanagementconsultingfirmfoundthatGenAIcanautomateupto60%ofmanualcompliance tasks.ThismakesGRC50%moreefficientoverall[53].
○ A major professional services network said that companies that used GenAI for GRC cut in half the time it tooktofindandevaluaterisksandworked55%fasterwhentheyhadtoreportcompliance[54].
● Enhanced Accuracy:
○ Acasestudyfrom a global technologycompanyshowed thatGenAI-drivenGRCsystemswere90%accurate atfindingpossiblecomplianceviolations,whiletraditionalmethodswereonly70%accurate[55].
○ Accordingtoastudybyamajorprofessionalservicesnetwork,GenAIcanmakeriskassessments85%more accurate,whichmeansthatfalsenegativesandfalsepositivesaremuchlesslikelytohappen[56].
Future Implications:
● Integration with New Technologies:
○ GenAIandblockchaintechnologycouldworktogethertokeeprecordsopenandsafeforcompliancereasons. ThiswouldmakesurethatGRCdatacan'tbechangedandcanbechecked[57].
International Research Journal of Engineering and Technology (IRJET) e-ISSN:2395-0056
Volume: 11 Issue: 05 | May 2024 www.irjet.net p-ISSN:2395-0072
○ GenAIandtheInternetofThings(IoT)couldworktogethertomakeiteasiertokeepaneyeonandcheckfor compliance in real time across all systems and devices that are connected [58]. This would make GRC monitoringmorethoroughandcovermoreareas.
● Predictive and Prescriptive Analytics:
○ AsGenAIalgorithmsgetsmarter,theymightbeabletodopredictiveandprescriptiveanalyticsinGRC,which wouldletcompaniesseerisksandcomplianceproblemscomingbeforetheyhappen[59].
○ GenAI-powered predictive models could test different risk scenarios and suggest the best ways to reduce thoserisks,whichwouldallowproactive,data-drivendecisionstobemadeinGRC[60].
● Continuous Auditing and Monitoring:
○ GenAI could make it possible to do continuous auditing and monitoring, which would be better than using sample-basedorperiodicmethodsbecauseitwouldallowforreal-time,completeGRCoversight[61].
○ GenAI-powered continuous monitoring could find compliance violations, security breaches, and strange activitiesastheyhappen,lettingyoufixtheproblemquicklyandlesseningtheeffectsofpossibleevents[62].
CHALLENGES:
● Transparency and Explainability:
○ Making sure that GenAI-driven choices in GRC are clear and easy to understand is important for fostering trustandaccountability,especiallywhenthesedecisionsaffectlawsandrules[63].
○ Creating ways to understand and explain the thinking behind GenAI results is still a big problem that needs ongoingstudyandteamworkbetweenAIexpertsandGRCprofessionals[64].
● Data Privacy and Security:
○ GenAIisusedinGRCtohandleprivateandsensitivedata,whichmakespeopleworryaboutdata safetyand security[65].
○ To protect personal information and stay in line with the law while using GenAI, organizations must put in placestrongdataprotectionmeasuresandfollowrelevantrules,liketheGeneralDataProtectionRegulation (GDPR)[66].
● Governance Frameworks for AI:
○ To make sure that GenAI systems are used ethically and responsibly, it is important to create the right governancemodelsfortheminGRC[67].
○ These frameworks should cover things like algorithmic bias, fairness, responsibility, and the possible unintendedoutcomesofdecisionsmadebyAIinGRCsettings[68].
● Skill Gap and Talent Shortage:
○ ImplementingGenAIinGRCneedsworkerswithspecificknowledgeofbothAIandGRC,whichcouldbehard tofindortrain[69].
○ To close the skills gap and make sure that their employees can use GenAI technologies successfully in GRC tasks[70],companiesneedtoputmoneyintotrainingandupskillingprograms[71].
International Research Journal of Engineering and Technology (IRJET) e-ISSN:2395-0056
Volume: 11 Issue: 05 | May 2024 www.irjet.net p-ISSN:2395-0072
Generative Artificial Intelligence (GenAI) is being used in security engineering and design, with a focus on Governance, Risk Management,andCompliance(GRC).Thisisacompletelynewwaytohandlecybersecurityrisks.GenAIhelpscompaniesmake their security systems more resilient and flexible by automating governance, improving predictive risk management, and making sure dynamic compliance. As GenAI technologies get better, they will be able to change GRC practices and make cybersecurity stronger. This will help organizations stay ahead of changing threats in a digital world that is getting more complicated.
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