Difference between revisions of "Finance & Accounting"
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|description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools | |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools | ||
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| − | [ | + | [https://www.youtube.com/results?search_query=accounting+finance+artificial+intelligence+deep+learning Youtube search...] |
| − | [ | + | [https://www.google.com/search?q=accounting+finance+deep+machine+learning+ML ...Google search] |
* [[Case Studies]] | * [[Case Studies]] | ||
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* [[Improper Payments]] | * [[Improper Payments]] | ||
* [[Backtesting]] | * [[Backtesting]] | ||
| − | * [ | + | * [https://deepindex.org/#Games Deepindex.org list] |
| − | * [ | + | * [https://www.federalregister.gov/documents/2021/03/31/2021-06607/request-for-information-and-comment-on-financial-institutions-use-of-artificial-intelligence Request for Information and Comment on Financial Institutions' Use of Artificial Intelligence, Including Machine Learning] A Notice by the Comptroller of the Currency, the Federal Reserve System, the Federal Deposit Insurance Corporation, the Consumer Financial Protection Bureau, and the National Credit Union Administration on 03/31/2021 |
| − | * [ | + | * [https://www.dataserv.com/solutions/3-way-match Touchless Invoice Processing with AutoVouch] |
| − | * [ | + | * [https://emerj.com/ai-sector-overviews/facial-recognition-in-finance-current-applications/ Facial Recognition in Banking – Current Applications | Niccolo Mejia] |
| − | * [ | + | * [https://www.intellichief.com/ai-in-accounting/ AI in Accounting: How Artificial Intelligence & Machine Learning Technology Has Changed the Industry | Faith Kubicki] |
| − | * [ | + | * [https://technology.finra.org/articles/unlocking-unstructured-data-with-text-analysis.html FINRA Technology | Dmytro Dolgopolov] |
| − | * [ | + | * [https://www.finextra.com/blogposting/15713/ai-and-ml-in-financial-services-compliance-management-use-cases-for-the-regulators AI and ML in Financial Services Compliance Management: Use Cases for the Regulators] |
| − | * [ | + | * [https://www.forbes.com/sites/bernardmarr/2019/06/14/the-amazing-ways-hitachi-uses-artificial-intelligence-and-machine-learning/#226d2de13705 Hitachi's H big data analysis engine; determine correlations, which can inform business decisions, forecasting, fraud detection, pricing | Bernard Marr - Forbes] |
| − | * [ | + | * [https://emerj.com/ai-sector-overviews/ai-startups-auto-lending AI Startups in Auto Lending – 2 Well-Funded Examples | Niccolo Mejia - Emero] |
| − | ** [ | + | ** [https://www.zest.ai/ Zest] ZAML - the only way to get your ML credit models from the lab to production. Reduce losses. Increase approvals. Fast. |
| − | ** [ | + | ** [https://lendbuzz.com/ Lendbuzz] offers loans directly to consumers |
| − | * [ | + | * [https://www.telemessage.com/revolutionizing-compliance-financial-industry-using-artificial-intelligence/ Areas where AI can contribute to compliance efficiency and effectiveness. | Pinchas] These include: |
** NLP solutions can ‘read’ documents and perform a range of tasks including extracting metadata, identifying entities that are referred to, and ‘understanding’ the intent or purpose of specific parts of the document. | ** NLP solutions can ‘read’ documents and perform a range of tasks including extracting metadata, identifying entities that are referred to, and ‘understanding’ the intent or purpose of specific parts of the document. | ||
** Know Your Customer Process – AI’s ability to analyze the vast amount of data and find patterns can create a more streamlined KYC process. By using algorithmic machine learning models, firms can generate risk profiles of individuals in just minutes. | ** Know Your Customer Process – AI’s ability to analyze the vast amount of data and find patterns can create a more streamlined KYC process. By using algorithmic machine learning models, firms can generate risk profiles of individuals in just minutes. | ||
Revision as of 17:21, 16 February 2023
Youtube search... ...Google search
- Case Studies
- Improper Payments
- Backtesting
- Deepindex.org list
- Request for Information and Comment on Financial Institutions' Use of Artificial Intelligence, Including Machine Learning A Notice by the Comptroller of the Currency, the Federal Reserve System, the Federal Deposit Insurance Corporation, the Consumer Financial Protection Bureau, and the National Credit Union Administration on 03/31/2021
- Touchless Invoice Processing with AutoVouch
- Facial Recognition in Banking – Current Applications | Niccolo Mejia
- AI in Accounting: How Artificial Intelligence & Machine Learning Technology Has Changed the Industry | Faith Kubicki
- FINRA Technology | Dmytro Dolgopolov
- AI and ML in Financial Services Compliance Management: Use Cases for the Regulators
- Hitachi's H big data analysis engine; determine correlations, which can inform business decisions, forecasting, fraud detection, pricing | Bernard Marr - Forbes
- AI Startups in Auto Lending – 2 Well-Funded Examples | Niccolo Mejia - Emero
- Areas where AI can contribute to compliance efficiency and effectiveness. | Pinchas These include:
- NLP solutions can ‘read’ documents and perform a range of tasks including extracting metadata, identifying entities that are referred to, and ‘understanding’ the intent or purpose of specific parts of the document.
- Know Your Customer Process – AI’s ability to analyze the vast amount of data and find patterns can create a more streamlined KYC process. By using algorithmic machine learning models, firms can generate risk profiles of individuals in just minutes.
- Money Laundering Detection – Using AI, firms can evaluate monitoring reports, news items, and regulatory alerts, and further analyze those that indicate the highest risk exposures.
- Rogue Employee Detection -AI can be used to identify employees that create fake accounts by tracking multiple accounts using the same email or IP address.
- Trade Monitoring – Through AI, regulatory bodies can learn traders’ personalities and behavior which increase the precision of identifying suspicious trading.
