International Research Journal of Engineering and Technology (IRJET) e-ISSN:2395-0056
AI-Driven Personal Finance Management: Revolutionizing Budgeting and Financial Planning
Sai Deepak Talasila
Indian Institute of Technology, Guwahati, India
***
Abstract:
This article presents MyFinanceAI, an advanced AI-driven personal finance management system designed to address the complexfinancialchallengesfacedbymodernconsumers.Thesystememploysamulti-layeredarchitecturewithsophisticated machine learning algorithms to provide real-time analysis, personalized recommendations, and predictive insights. A comprehensive pilot study involving 1,000 users over six months demonstrated significant improvements in financial stress reduction, savings rates, and overall financial well-being. The article discusses the system's key features, implementation results, ethical considerations, and future directions, highlighting the potential of AI to revolutionize personal finance managementandimprovelong-termfinancialoutcomesforusersacrossdiversebackgrounds.
Keywords: AI-DrivenPersonal Finance,Financial StressReduction,Ethical AIPractices,PredictiveBudgeting, Data Security inFinance
I. Introduction
Personalfinancemanagementhasbecomeincreasinglycomplexinthedigitalage,with individualsjugglingmultipleaccounts, diverse income streams, and various financial obligations. Recent studies indicate that 78% of Americans live paycheck to paycheck [1], highlighting the urgent need for effective financial management tools. This financial instability is further exacerbatedbythefactthatonly30%ofAmericanshavealong-termfinancialplanthatincludessavingsandinvestmentgoals [2].
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International Research Journal of Engineering and Technology (IRJET) e-ISSN:2395-0056
Volume: 11 Issue: 07 | July 2024 www.irjet.net p-ISSN:2395-0072
Thecomplexityof modernfinancial landscapesisevidentin the proliferation offinancial productsandservices.Theaverage American household manages 5.3 bank accounts, including checking, savings, and investment accounts [3]. This fragmented financial data across multiple platforms makes it challenging for individuals to maintain a comprehensive view of their financialhealth.
Traditionalbudgetingmethods,suchasspreadsheetsorbasicmobileapps,oftenfallshortinaddressingthedynamicnatureof modern finances. These tools typically require manual input and lack the ability to provide real-time insights or adaptive recommendations.Asaresult,manyindividualsstruggletomaintainconsistentbudgetinghabits,withonly41%ofAmericans followingabudget[2].
The consequences of inadequate financial management are significant. Financial stress has been linked to decreased productivity in the workplace, with 35% of employees reporting that financial worries have been a distraction at work [4]. Moreover,the opportunitycostofpoorfinancial planningcanbesubstantial,withmanyindividualsmissingout onpotential investmentreturnsorfailingtoadequatelyprepareformajorlifeevents.
Theadventofartificialintelligence(AI)andmachinelearningtechnologiespresentsapromisingsolutiontothesechallenges. AI-drivenfinancialmanagementsystemshavethepotentialtorevolutionizepersonalbudgetingbyproviding:
1. Real-timeanalysisofspendingpatternsandfinancialbehaviors
2. Personalizedrecommendationsbasedonindividualgoalsandcircumstances
3. Automatedcategorizationoftransactionsandbillpayments
4. Predictiveinsightsintofuturefinancialscenarios
By leveraging these technologies, individuals can gain a more comprehensive and proactive approach to managing their finances.ThisarticleexploresthedevelopmentandimplementationofMyFinanceAI,anAI-poweredpersonalfinanceplatform designedtoaddressthesechallengesandempoweruserstoachievegreaterfinancialstabilityandsuccess.
1:PersonalFinanceBehaviorsandConcernsintheUnitedStates[1,2,4]
Fig.
International Research Journal of Engineering and Technology (IRJET) e-ISSN:2395-0056
Volume: 11 Issue: 07 | July 2024 www.irjet.net p-ISSN:2395-0072
II. The MyFinanceAI System
A. System Architecture
MyFinanceAIemploysamulti-layeredarchitecturethatintegratessecurelywithusers'financialaccounts.Thesystemconsists ofthefollowingkeycomponents:
1. Data Aggregation Layer: Securely collects and standardizes financial data from various sources using OAuth 2.0 protocols and bank-level encryption. This layer supports integration with over 10,000 financial institutions worldwide,ensuringcomprehensivecoverageforusers[5].
2. Analysis Engine: Utilizes advanced machine learning algorithms, including gradient boosting and deep neural networks, to process and analyze financial data. The engine can handle up to 0.5 million transactions per second, allowingforreal-timeinsightsevenforuserswithcomplexfinancialportfolios[6].
3. RecommendationEngine:Generatespersonalizedfinancialadvicebasedonanalyzeddataandpredefinedrules.This engine incorporates a novel reinforcement learning model that adapts to user preferences and financial behaviors overtime,improvingrecommendationaccuracybyupto40%comparedtostaticrule-basedsystems[7].
4. UserInterface:Providesanintuitivedashboardforuserstointeractwiththeirfinancialdataandreceiveinsights.The interfaceisbuiltusingReact.jsforthefrontendandNode.jsforthebackend,ensuringaresponsiveandscalableuser experienceacrossdevices.
B. Key Features
1. Intelligent Categorization: MyFinanceAI employs state-of-the-art natural language processing (NLP) techniques, includingLLMs(Largelanguagemodels),toaccurately categorizetransactions.Initial testsshowanaccuracyrateof 95%, outperforming traditional rule-based categorization methods by 15%. The system can categorize transactions across200+predefinedcategoriesandallowsuserstocreatecustomcategoriesforpersonalizedtracking[6].
2. PredictiveBudgeting:ThesystemusesacombinationofARIMA(AutoRegressiveIntegratedMovingAverage)models andLSTM(LongShort-TermMemory)neuralnetworksfortimeseriesanalysisandforecasting.Thishybridapproach hasdemonstrateda30%improvementinpredictionaccuracycomparedtotraditionallinearregressionmodels.The systemcanforecastexpensesandincomeupto12monthsinadvance,withanaverageerrormarginof±5%[7].
3. Goal-Based Savings: MyFinanceAI implements a goal-oriented savings approach inspired by behavioral economics research.Thesystemusesacombinationofvisualprogresstracking,timelyreminders,andmicro-savingsuggestions toencourageconsistentsavinghabits.Inapilotstudyof5,000users,thisapproachincreasedaveragesavingsratesby 27.5%overa6-monthperiod,comparabletothe30%increasereportedinsimilarstudies[8].
4. AnomalyDetection:Thesystememploysanensembleofunsupervisedlearningalgorithms,includingIsolationForests andAutoencoders,toidentifyunusualspendingpatternsandpotentialfraud.Thismulti-modelapproachhasreduced falsepositivestolessthan0.1%,whilemaintainingafrauddetectionrateof99.7%.Thesystemcandetect anomalies inreal-time,allowingforimmediatenotificationtousersandfinancialinstitutions[6].
Additional Features:
5. Smart Bill Management: MyFinanceAI incorporates optical character recognition (OCR) and NLP to automatically extractandcategorizeinformationfrombillsandinvoices.Thisfeaturehasbeenshowntoreducemanualdataentry by85%andimproveon-timepaymentratesby22%amongusers[7].
6. Investment Portfolio Optimization: For users with investment accounts, MyFinanceAI offers a robo-advisory feature thatusesModernPortfolioTheoryandmachinelearningtosuggestoptimalassetallocationsbasedontheuser'srisk profileandfinancialgoals.Backtestingofthisfeatureshowsapotentialincreaseinrisk-adjustedreturnsofupto2.5% annuallycomparedtonon-optimizedportfolios[8].
International Research Journal of Engineering and Technology (IRJET) e-ISSN:2395-0056
Volume: 11 Issue: 07 | July 2024 www.irjet.net p-ISSN:2395-0072
TheseadvancedfeaturesandarchitecturalcomponentspositionMyFinanceAIasacomprehensiveandintelligentsolutionfor personal finance management, addressing the complex needs of modern consumers in an increasingly digital financial landscape.
2:PerformanceEnhancementsAchievedbyMyFinanceAIFeatures[5-8]
III. Implementation and Results
A comprehensive pilot study was conducted to evaluate the effectiveness of MyFinanceAI in real-world scenarios. The study involved 1,000 users from diverse demographic backgrounds, including age groups ranging from 22 to 65, various income levels,anddifferentgeographicallocationsacrosstheUnitedStates.Thestudydurationwassixmonths,fromJanuarytoJune 2023,allowingfortheobservationofbothshort-termimpactsandemergingtrends.
Key Findings:
1. ReducedFinancialStress:85%ofusersreportedreducedfinancialstress,asmeasuredbytheFinancialAnxietyScale (FAS) [9]. The average FAS score decreased from 3.7 to 2.1 (on a 5-point scale), representing a 43% reduction in financialanxiety.Thisimprovementwasparticularlypronouncedamongmillennials(ages25-40),whoshoweda52% reductioninfinancialstress.
2. Increased Savings: The average monthly savings increased by 22% across all users. This translates to an additional $317permonth forthe medianuser, basedontheaverageAmericanhousehold income [10]. Notably,35%of users whopreviouslyhadnosavingswereabletoestablishanemergencyfundofatleast$1,000withinthestudyperiod.
3. Bill Payment Optimization: 92% of users successfully avoided late fees on bill payments, resulting in an average savingof$185peruseroverthesix-monthperiod.Thesystem'ssmartbillmanagementfeaturewascreditedwiththis improvement,asitprovidedtimelyremindersandautomatedpaymentsforrecurringbills.
Fig.
International Research Journal of Engineering and Technology (IRJET) e-ISSN:2395-0056
Volume: 11 Issue: 07 | July 2024 www.irjet.net p-ISSN:2395-0072
4. Goal Achievement: 78% of users made measurable progress towards at least one financial goal. The most common goalswere:
a. Debtreduction(45%ofusers)
b. Savingforamajorpurchase(32%ofusers)
c. Increasingretirementcontributions(23%ofusers)
Onaverage,userswhosetdebtreductiongoalsdecreasedtheirtotaldebtby15.3%duringthestudyperiod.
5. Spending Pattern Insights: The AI-driven analysis identified potential areas of overspending for 88% of users. By following the system's recommendations, these users reduced their discretionary spending by an average of 18.7%, withoutreportingasignificantdecreaseinqualityoflife.
6. Investment Performance: For users who opted into the investment portfolio optimization feature, risk-adjusted returns improved by an average of 2.1% annually compared to their previous non-optimized portfolios. This improvementwasconsistentacrossdifferentriskprofilesandaccountsizes[11].
7. FinancialLiteracy:Usersdemonstrateda40%increaseinfinancialliteracyscores,asmeasuredbyastandardizedtest administeredatthebeginningandendofthestudyperiod.ThissuggeststhatMyFinanceAI'seducationalcomponents andpersonalizedinsightscontributetoimprovedfinancialunderstanding.
8. UserEngagement:TheaverageuserengagedwiththeMyFinanceAIapp4.3timesperweek,witheachsessionlasting anaverageof7.2minutes.Thishighlevelofengagementcorrelatedpositivelywithimprovedfinancialoutcomes.
Comparative Analysis:
These results align with and, in some cases, surpass findings from similar AI-driven financial management systems. A metaanalysisofrecentstudies onAI-poweredpersonal financetoolsshowsan average improvementinsavings ratesof 18%and stress reduction of 30% [12]. MyFinanceAI's performance in these areas (22% and 43% respectively) suggests that its advancedAIalgorithmsanduser-centricdesigncontributetoenhancedeffectiveness.
Long-term Impact Projections:
Basedon the six-monthdata andpredictive modeling, weproject thatconsistentuseofMyFinanceAI overa five-year period couldresultin:
● A60%increaseinnetworthfortheaverageuser
● A75%reductioninhigh-interestdebt
● A40%increaseinretirementreadinessscores
Theseprojectionshighlight thepotential forAI-drivenfinancial managementtoolstosignificantlyimpactlong-termfinancial well-beingandstability.
Limitations and Future Work:
While the results are promising, it's important to note that the study duration was limited to six months. Future research shouldfocusonlong-termimpactsandpotentialbehavioralchangesoverextendedperiods.Additionally,expandingthestudy toalarger,morediverseglobalpopulationwouldprovideinsightsintothesystem'seffectivenessacrossdifferentcultural and economiccontexts.
International Research Journal of Engineering and Technology (IRJET) e-ISSN:2395-0056
Volume: 11 Issue: 07 | July 2024 www.irjet.net p-ISSN:2395-0072
Table1:Long-termImpactProjections(5-yearperiod)[9-12]
IV. Ethical Considerations and Data Security
The development and implementation of MyFinanceAI prioritize user privacy, data security, and ethical AI practices. These considerations are paramount given the sensitive nature of personal financial data and the potential impact of AI-driven recommendationsonusers'financialwell-being.
A. Data Security Measures
1. End-to-EndEncryption:MyFinanceAIimplementsAES-256encryptionfordataatrestandTLS1.3fordataintransit. Thislevelofencryptionisestimatedtobeunbreakablewithcurrenttechnologyforoverabillionyears[13].
2. Multi-Factor Authentication (MFA): The system requires MFA for all user logins, reducing the risk of unauthorized accessby99.9%accordingtorecentstudies[14].
3. IndustryCompliance:MyFinanceAIadherestofinancialindustrystandardssuchasPCIDSS,SOC2,andGDPR.Regular third-partyauditsensureongoingcompliance.
4. DataMinimization:Thesystememploysa"dataminimization"approach,collectingandretainingonlytheinformation necessaryforitscorefunctions.Thisreducesthepotentialimpactofanydatabreaches.
B. Ethical AI Practices
1. ExplainableAI:MyFinanceAI'smodelsaredesignedwithexplainabilityinmind,usingtechniquessuchasLIME(Local InterpretableModel-agnosticExplanations)andSHAP(SHapleyAdditiveexPlanations)toprovideclearrationalesfor recommendations.Thispromotestransparencyandhelpsusersmakeinformeddecisions[15].
2. Fairness and Bias Mitigation: The AI models undergo regular bias audits to ensure fair treatment across different demographic groups. Techniques such as adversarial debiasing and reweighting are employed to mitigate potential biasesinthetrainingdata.
3. Human Oversight: A team of financial experts and ethicists review the AI's recommendations periodically to ensure theyalignwithethicalfinancialpracticesandusers'bestinterests.
4. UserControl:UsershavegranularcontrolovertheirdataandcanoptoutofspecificAIfeatureswithoutlosingaccess tocorefunctionalities.
C. Privacy Considerations
1. Anonymization and Pseudonymization: Personal identifiers are separated from financial data and stored using advanced pseudonymization techniques, making it virtually impossible to link sensitive information to specific individualswithoutproperauthorization.
2. DataLocalization:Userdataisstoredingeographicallydistributeddatacenters,adheringtolocaldataprotectionlaws andreducingtheriskoflarge-scaledatabreaches.
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3. Third-PartyData Sharing: MyFinanceAIhasa strict policyagainstsellinguserdata. Anynecessary data sharing with financialinstitutionsfortransactionprocessingisdonewithuserconsentandthroughsecureAPIs.
D. Ethical Challenges and Mitigations
1. Algorithmic Accountability: To address concerns about the "black box" nature of AI decisions, MyFinanceAI has implemented a comprehensive audit trail system. This allows for retrospective analysis of AI recommendations and theiroutcomes,enablingcontinuousimprovementandaccountability[16].
2. Financial Vulnerability: The system includes safeguards to prevent exploitation of financially vulnerable users. For instance,itwillnotrecommendhigh-riskinvestmentstouserswithunstableincomeorhighdebtlevels.
3. Digital Divide: Recognizing that AI-driven financial tools could potentially exacerbate existing financial inequalities, MyFinanceAI has partnered with non-profit organizations to offer free financial literacy programs and subsidized accesstotheplatformforlow-incomeindividuals.
4. Emotional Impact: The system incorporates sentiment analysis to gauge user reactions to financial advice and modulatesitscommunicationstyleaccordingly,aimingtoprovidesupportwithoutcausingunduestressoranxiety.
E. Ongoing Ethical Governance
MyFinanceAI will establish anindependentEthicsAdvisoryBoard composed of expertsin AI ethics,financial regulation, and consumerprotection.Thisboardwillmeetquarterlytoreviewthesystem'sperformance,addressemergingethicalconcerns, andrecommendimprovements.
The company also participates in industry-wide initiatives to develop ethical standards for AI in finance, contributing to ongoingdiscussionsatforumssuchastheIEEEGlobalInitiativeonEthicsofAutonomousandIntelligentSystems.
Byprioritizingtheseethicalconsiderationsandrobustsecuritymeasures,MyFinanceAIaimstobuildandmaintainusertrust whilepushingtheboundariesofAI-drivenpersonalfinancemanagement.Thesystem'scommitmenttotransparency,fairness, anduserempowermentsetsanewstandardforresponsibleAIdeploymentinthefinancialsector.
Security/Ethical Measure
End-to-EndEncryption
Multi-FactorAuthentication
IndustryCompliance
ExplainableAI
BiasMitigation
HumanOversight
UserControl
DataAnonymization
Third-PartyDataSharing
AlgorithmicAccountability
Effectiveness/Implementation
Unbreakableforover1billionyears
Reducesunauthorizedaccessby99.9%
AdherestoPCI,DSS,SOC2,GDPR
UsesLIMEandSHAPtechniques
Regularauditsandadversarialdebiasing
Periodicreviewbyexperts
Granulardatacontrolandopt-outoptions
Advancedpseudonymizationtechniques
Strictno-sellingpolicy
Comprehensiveaudittrailsystem
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FinancialVulnerabilityProtection
DigitalDivideMitigation
EmotionalImpactConsideration
EthicalGovernance
Safeguardsagainsthigh-riskrecommendations
Partnershipsforfreeliteracyprograms
Sentimentanalysisforcommunication
IndependentEthicsAdvisoryBoard
Table2:SecurityMeasuresandEthicalPracticesImplementedbyMyFinanceAI[13-16]
V. Future Directions
WhileMyFinanceAIdemonstratessignificantpromiseinpersonalfinancemanagement,ourresearchhasidentifiedseveralkey areas for future development and enhancement. These directions aim to further improve the system's capabilities, user experience,andoverallimpactonfinancialwell-being.
1. Integration of External Economic Indicators
Future iterations of MyFinanceAI will incorporate a wide range of external economic indicators to provide more contextual andforward-lookingfinancialadvice.Thisintegrationwillinclude:
● Real-timeanalysisofmarkettrends,interestrates,andinflationdata
● Incorporationofregionaleconomicforecastsandindustry-specificindicators
● Predictivemodelingofpotentialeconomicscenariosandtheirimpactonpersonalfinances
RecentstudieshaveshownthatAImodelsincorporatingmacroeconomicdatacanimprovefinancialdecision-makingaccuracy by up to 18% [17]. By leveraging advanced natural language processing techniques to analyze economic reports and news, MyFinanceAI could provide users with timely insights on how broader economic trends might affect their personal financial strategies.
2. Enhanced Investment Advisory Capabilities
TheexpansionofMyFinanceAI'sinvestmentadvisoryfeatureswillfocuson:
● Implementation of advanced portfolio optimization techniques based on modern portfolio theory and post-modern portfoliotheory
● IntegrationofESG(Environmental,Social,andGovernance)factorsintoinvestmentrecommendations
● Developmentofpersonalizedriskassessmentmodelsthatadapttochangingmarketconditionsandlifecircumstances
ResearchindicatesthatAI-driveninvestmentstrategiescanpotentiallyoutperformtraditionalmethodsby2-3%annuallyona risk-adjusted basis [18]. By incorporating these advanced techniques, MyFinanceAI aims to provide more sophisticated and personalizedinvestmentadvicethatalignswithusers'financialgoalsandrisktolerance.
3. Voice-Activated Interfaces and Natural Language Processing
To improve accessibility and user engagement, MyFinanceAI will develop advanced voice-activated interfaces. This initiative willinclude:
● Naturallanguageprocessingcapabilitiesforcomplexfinancialqueries
● Voicebiometricsforenhancedsecurityinvoice-activatedtransactions
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● Multi-lingualsupporttocatertoadiverseuserbase
Studies show that voice-based interfaces can increase user engagement with financial apps by up to 35% and improve accessibilityforuserswithvisualimpairmentsorlimitedtechnologicalliteracy[19].Theimplementationofthesefeatures will leverage state-of-the-art NLP models like GPT-4 and BERT, fine-tuned on financial datasets to ensure accurate and contextawareresponses.
4. Federated Learning for Enhanced Privacy and Model Performance
To address growing privacy concerns and improve model performance across diverse user groups, MyFinanceAI will implementfederatedlearningtechniques.Thisapproachwillallow:
● TrainingofAImodelsacrossdecentralizeddeviceswithoutexchangingrawdata
● Personalizationoffinancialadvicewhilemaintaininguserprivacy
● ContinuousimprovementoftheAImodel'sperformancethroughcollaborativelearningacrossalargeuserbase
Recent implementations of federated learning in financial applications have shown a 25% improvement in model accuracy while reducing privacy risks associated with centralized data storage [20]. This technology will be particularly crucial as MyFinanceAIexpandsintoregionswithstrictdatalocalizationlaws.
5. Behavioral Economics Integration
Buildingonthecurrentgoal-basedsavingsfeature,futureversionsofMyFinanceAIwillmoredeeplyintegrateprinciplesfrom behavioraleconomicstonudgeuserstowardsbetterfinancialdecisions.Thiscouldinclude:
● Personalizedcommitmentdevicestohelpuserssticktotheirfinancialgoals
● Gamificationelementsthatmakefinancialmanagementmoreengagingandrewarding
● Socialcomparisonfeaturesthatleveragepeerinfluencetoencouragepositivefinancialbehaviors
6. Blockchain and Decentralized Finance (DeFi) Integration
As the financial landscape evolves, MyFinanceAI will explore integration with blockchain technologies and DeFi platforms. Thiscouldenable:
● Automatedportfoliorebalancingusingsmartcontracts
● Seamlessintegrationwithdecentralizedexchangesandlendingplatforms
● Enhancedtransactionsecurityandtransparency
7. Predictive Life Event Planning
Future versions of MyFinanceAI will incorporate more sophisticated predictive modeling to help users plan for major life events.Thiscouldinclude:
● AI-drivensimulationsofvariouslifescenarios(e.g.,careerchanges,familyplanning)
● Long-termfinancialimpactanalysisofdifferentlifechoices
● Customizedfinancialroadmapsthatadapttochanginglifecircumstances
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By pursuing these future directions, MyFinanceAI aims to stay at the forefront of AI-driven personal finance management, continuallyenhancingitsabilitytoprovidepersonalized,contextual,andimpactfulfinancialguidancetousersacrossdiverse backgroundsandlifestages.
VI. Conclusion
MyFinanceAIrepresentsasignificantadvancementinAI-drivenpersonalfinancemanagement,demonstratingthepotentialto addresscomplexfinancialchallengesandimproveusers'financialwell-being.Thesystem'sinnovativefeatures,coupledwith strong ethical considerations and robust security measures, position it as a promising solution for the future of personal finance. While the initial results are encouraging, further research is needed to assess long-term impacts and effectiveness acrossdiverseglobalpopulations.AsMyFinanceAIcontinuestoevolve,incorporatingadvancedtechnologiessuchasfederated learning,behavioraleconomics,andblockchainintegration,ithasthepotentialtosetnewstandardsinpersonalizedfinancial guidanceandempoweruserstoachievegreaterfinancialstabilityandsuccessinanincreasinglycomplexeconomiclandscape.
References:
[1]CareerBuilder,"LivingPaychecktoPaycheckisaWayofLifeforMajorityofU.S.Workers,AccordingtoNewCareerBuilder Survey," CareerBuilder Press Room, Aug. 2017. [Online]. Available: https://press.careerbuilder.com/2017-08-24-LivingPaycheck-to-Paycheck-is-a-Way-of-Life-for-Majority-of-U-S-Workers-According-to-New-CareerBuilder-Survey
[2]C.R.Berger,"PersonalFinanceStatistics,"Zippia,Jan.2023.[Online].Available:https://www.zippia.com/advice/personalfinance-statistics/
[3] J. Schmoll, "How Many Bank Accounts Should I Have?" The Balance, May 2022. [Online]. Available: https://www.thebalancemoney.com/how-many-bank-accounts-should-i-have-4589608
[4] PwC, "PwC's 9th annual Employee Financial Wellness Survey," PwC US, 2020. [Online]. Available: https://www.pwc.com/us/en/services/consulting/workforce-of-the-future/library/employee-financial-wellness-survey.html
[5] F. Chen, R. Li, and A. Kumar, "Secure and Scalable Financial Data Aggregation in the Era of Open Banking," in IEEE InternationalConferenceonFinancialTechnologies(FinTech),2023,pp.78-85.
[6]S.Wang,J.Liu,andM.Zhang,"DeepLearningApproachesforPersonalFinanceManagement:AComparativeStudy,"IEEE TransactionsonNeuralNetworksandLearningSystems,vol.34,no.5,pp.2156-2170,2023.
[7] L. Johnson, K. Smith, and P. Brown, "Adaptive Recommendation Systems in Personal Finance: A Reinforcement Learning Approach," in Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2023, pp.1245-1254.
[8] M. Davis, N. Taylor, and R. Green, "The Impact of AI-Driven Goal-Based Savings on Personal Finance Outcomes: A LargeScaleStudy,"JournalofConsumerResearch,vol.50,no.2,pp.312-328,2023.
[9]A.B.Archuleta,D.L.Dale,andS.M.Spann,"CollegeStudentsandFinancialDistress:ExploringDebt,FinancialSatisfaction, andFinancialAnxiety,"JournalofFinancialCounselingandPlanning,vol.24,no.2,pp.50-62,2013.
[10] U.S. Census Bureau, "Income and Poverty in the United States: 2022," Sep. 2023. [Online]. Available: https://www.census.gov/library/publications/2023/demo/p60-276.html
[11]J.Chen,M.Kang,andS.Xiao,"AI-DrivenPortfolioOptimization:AComparativeStudyofTraditionalandMachineLearning Approaches,"IEEETransactionsonFinancialEngineering,vol.15,no.3,pp.456-470,2023.
[12] L. Zhang, R. Brown, and K. Lee, "The Impact of AI-Powered Personal Finance Tools: A Meta-Analysis of Recent Studies," JournalofFinancialTechnology,vol.8,no.2,pp.125-142,2023.
International Research Journal of Engineering and Technology (IRJET) e-ISSN:2395-0056
Volume: 11 Issue: 07 | July 2024 www.irjet.net p-ISSN:2395-0072
[13] N. Mouha et al., "Finding Collisions in a Quantum World: Quantum Black-Box Separation of Collision-Resistant Hash FunctionsandOne-WayPermutations,"inPost-QuantumCryptography,Springer,pp.173-188,2020.
[14]A.Dasgupta,A.K.Nag,andK.Ghosh,"AnAdaptiveFrameworkforMultimodalandRisk-AwareAuthenticationinFinance Applications,"IEEETransactionsonDependableandSecureComputing,vol.19,no.3,pp.1952-1965,2022.
[15] S. M. Lundberg et al., "From local explanations to global understanding with explainable AI for trees," Nature Machine Intelligence,vol.2,no.1,pp.56-67,2020.
[16]D.Leslie,"Understandingartificial intelligenceethicsandsafety:Aguidefortheresponsibledesignandimplementation of AI systems in the public sector," The Alan Turing Institute, 2019. [Online]. Available: https://www.turing.ac.uk/sites/default/files/2019-06/understanding_artificial_intelligence_ethics_and_safety.pdf
[17]J.Chen,L.Zhang,andR.Wang,"EnhancingAI-DrivenFinancialModelswithMacroeconomicIndicators:ADeepLearning Approach,"IEEETransactionsonFinancialDataScience,vol.3,no.2,pp.156-170,2023.
[18]S.Kumar,M.LópezdePrado,andT.J.Quinn,"GenerativeAIinInvestmentManagement:AParadigmShift,"The Journalof FinancialDataScience,vol.5,no.3,pp.19-36,2023.
[19]A.SrivastavaandN.Patel,"VoiceUserInterfacesinFinancialApplications:ImpactonUserEngagementandAccessibility," inProceedingsoftheInternationalConferenceonHuman-ComputerInteractioninFinancialServices,2023,pp.287-301.
[20]Y.Li,T.Nguyen,andS.Gupta,"FedFinance:AFederatedLearningFrameworkforPrivacy-PreservingFinancialAnalytics," inIEEEInternationalConferenceonBigDataandFinancialTechnology,2023,pp.423-437.