Finance & Accounting
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- 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
- Century of Enslavement - The History of The Federal Reserve | James Corbett
- 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.
- I pitted ChatGPT against a real financial advisor to help me save for retirement—and the winner is clear | Coryanne Hicks - Fortune ... I think the question is not “ChatGPT versus a human advisor,” but rather how to optimize “ChatGPT with a human advisor.”
Contents
Digital Evolution: Financial Planning & Analysis (FP&A)
Financial Planning & Analysis is an umbrella term that describes the methodologies, metrics, processes, and systems used to monitor and manage the business performance of an enterprise. FP&A solutions are designed to help organizations align their strategies and goals to their plans and executions to control the success of the organization. FP&A software includes forecasting, budgeting, and planning functions, as well as graphical scorecards and dashboards to display and deliver corporate information. FP&A must be supported by a suite of analytical applications that provide the functionality to support these processes, methodologies, and metrics. Some of the different strategic frameworks and management methods used in FP&A include the balanced scorecard, Six Sigma, and the European Foundation for Quality Management (EFQM) excellence model. FP&A solutions can streamline data integration across organizations while giving administrators and managers the power to define workflows to optimize efficiency. FP&A solutions can help organizations ensure that all financial needs for optimal business operation are met, involving financial budgeting, planning, modeling, data congregating, and more.
Applications
FP&A Genius | Datarails
Datarails offers an AI-powered chat service called FP&A Genius. It provides generative AI answers based on complete and consolidated finance data from across a company. The chat function allows CFOs and finance teams to get instant insights about budgets, forecasts, variance, and spend. The tool provides quick answers to business-critical questions about budgets, forecasts, variance, and spend. FP&A Genius can help automate many ad hoc reports, eliminating the massive amount of time wasted on one-time tasks. The tool can generate answers and charts instantly based on the precise turn a board meeting takes or the latest pressing request from a department. Datarails is a financial planning and analysis platform that empowers finance teams to transform their Excel into a lean, mean FP&A machine. The platform allows users to keep using their own Excel financial models and spreadsheets while automating repetitive processes. Datarails integrates with the most popular accounting software, ERPs, and CRMs, so all data can be consolidated in one place. The platform provides intuitive workflows for version control and collaboration across the company, improves data integrity and visibility with comprehensive records and audit trail, and houses the latest version of data in one place, with full control over how it’s structured. FP&A Genius is the world's first generative AI tool for FP&A that offers unprecedented instant insights about budgets, forecasts, variance, and spend.
FP&A Genius uses AI to provide instant financial insights based on complete and consolidated finance data from across an organization. Here are some ways in which FP&A Genius uses AI to provide insights:
- Generative AI: FP&A Genius uses open source generative AI and NLP technologies to generate answers to complex financial questions in seconds.
- Natural Language Processing (NLP): The tool uses NLP to understand the intent behind the user's question and provide relevant answers.
- Visualization: FP&A Genius leverages AI to create and visualize financial information in seconds.
- Automation: The tool automates many ad hoc reports, eliminating the massive amount of time wasted on one-time tasks.
OneStream
OneStream provides machine learning (ML) and artificial intelligence (AI) capabilities that can help improve productivity and financial performance. OneStream's built-in AI and ML capabilities can make intelligent decisions and automate processes, such as financial consolidation, planning, reporting, and analytics. OneStream's Sensible ML is a time series ML solution that integrates with other systems, such as ERP and CRM, to provide real-time insights into financial performance. OneStream's AI and ML tools can also help improve data quality, reduce errors, and increase efficiency. OneStream's FP&A solution is designed to automate the annual close and quarterly financial reporting processes, improve financial data quality, and provide real-time visibility into financial performance. The solution can help DoD and other government agencies to improve their financial reporting, budgeting, planning, and forecasting processes. OneStream's FP&A solution is also FedRAMP compliant, which means that it meets the rigorous security and compliance requirements of the Federal Risk and Authorization Management Program (FedRAMP); making it a suitable solution for government agencies that need to comply with FedRAMP requirements.
OneStream offers several AI and ML capabilities that can help improve productivity, financial performance, and data quality. These capabilities include:
- Built-in AI and ML capabilities: make intelligent decisions and automate processes, such as financial consolidation, planning, reporting, and analytics.
- Auto AI and ML capabilities: unified approach in delivering capabilities to its users
- Sensible ML: AI-enabled solution designed to productize time-series Machine Learning (ML) modeling for FP&A processes; integrates with other systems, such as ERP and CRM, to provide real-time insights into financial performance
- Generative AI: advancing generative AI to improve productivity
OneStream's AI and ML capabilities can provide advanced financial forecasting that analyzes vast amounts of data generated from internal sources such as ERP, CRM, and Supply Chain systems as well as external sources such as weather and other macro-economic data, building thousands of ML models in parallel. OneStream's Sensible ML solution can increase forecast agility and accuracy for financial and operational planning by applying time-series forecasting techniques. OneStream's AI and ML capabilities can make intelligent forecasting accessible to finance and operations teams, expanding use cases.
OneStream's Sensible ML utilizes time-series forecasting techniques for financial and operational planning. Time-series forecasting models are statistical models that analyze trends and patterns in historical data points arranged in chronological order to make predictions about future values. Some common time-series forecasting machine learning models include:
- Autoregressive (AR) model: This model predicts future values based on past values in a time series, taking into account the relationship between an observation and a number of lagged observations
- Moving Average (MA) model: This model predicts future values based on the average of past observations in a time series, with the average calculated over a specific window of time.
- Autoregressive Integrated Moving Average (ARIMA) model: This model combines the autoregressive and moving average components to predict future values, taking into account both the trend and seasonality in the data.
- Exponential Smoothing (ES) model: This model predicts future values based on the weighted average of past observations, with more recent observations given higher weights.
These time-series forecasting models can be applied by OneStream's Sensible ML solution to analyze historical financial and operational data and generate accurate forecasts for planning purposes. By leveraging these techniques, Sensible ML can enhance forecast agility and accuracy for financial and operational planning processes.
FloQast
an AI-powered spend management platform that helps organizations to optimize their spending. FloQast uses machine learning to identify and analyze patterns in spending data. This allows organizations to identify opportunities to save money, such as by negotiating better contracts or consolidating vendors. One specific application of AI at FloQast is in their AutoRec feature, which leverages AI to automate the account reconciliation process. In the context of budgets, FloQast's AI capabilities can be used to automate FP&A (Financial Planning and Analysis) workflows. By connecting data from the monthly close process, ERP systems, and other crucial systems, FloQast's AI can provide more transparent and accurate forecasts, as well as defensible budgets. While FloQast's AI capabilities are not explicitly marketed as customizable for specific industries or company sizes, their AI tools can be applied to various accounting and finance workflows.
- AutoRec: FloQast's AutoRec feature leverages AI to automate the account reconciliation process, matching banking transactions to GL transactions faster and helping to close the books sooner.
- Machine Learning (ML): FloQast employs machine learning to automate tedious tasks for accountants, allowing them to focus on more valuable projects.
- Generative AI: FloQast's generative AI algorithms can analyze large data sets and quickly identify patterns and anomalies to improve accounting workflows, including budgeting and financial planning and analysis.
Oracle Financial Services Cloud
An AI-powered financial management platform that helps organizations to automate their financial processes. Oracle Financial Services Cloud (formerly RightNow) uses machine learning to identify and automate tasks such as invoice processing, reconciliation, and budgeting. This frees up human resources to focus on more strategic activities, such as financial planning and analysis. Oracle Service Cloud, part of the Oracle CX Cloud Suite, is a cloud-based, omnichannel solution that captures a 360-degree view of every customer in a dynamic and unified agent desktop. Oracle Service Cloud’s innovative approach is driven by knowledge, automation, and evolving customer interaction channels, simplifying every service experience for service administrators and customers alike. By helping to differentiate your organization's service experience, Oracle Service Cloud delivers measurable business impacts across all industries.
Oracle's AI strategy includes infrastructure, development, and management tools, prebuilt cognitive services, and AI cloud services.
- Oracle Cloud Infrastructure (OCI) AI Services: is a collection of services that provide prebuilt Machine Learning (ML) models, making it easier for developers to apply AI in their applications.
- AI-powered apps for ERP:, including finance and procurement, which help improve performance, optimize working capital, and increase automation across various financial processes
- Oracle's Generative AI: capabilities, which involve cloud infrastructure and tooling for model deployment and training.
Statistical Analysis System (SAS) Business Intelligence
an AI-powered financial management platform that helps organizations to automate their financial processes. Oracle Financial Services Cloud (formerly RightNow) uses machine learning to identify and automate tasks such as invoice processing, reconciliation, and budgeting. This frees up human resources to focus on more strategic activities, such as financial planning and analysis. Oracle Service Cloud, part of the Oracle CX Cloud Suite, is a cloud-based, omnichannel solution that captures a 360-degree view of every customer in a dynamic and unified agent desktop. Oracle Service Cloud’s innovative approach is driven by knowledge, automation, and evolving customer interaction channels, simplifying every service experience for service administrators and customers alike. By helping to differentiate your organization's service experience, Oracle Service Cloud delivers measurable business impacts across all industries.
- Automating tasks: AI can be used to automate tasks such as data extraction, analysis, and reporting. This frees up human resources to focus on more strategic activities, such as identifying trends and making informed decisions.
- Identifying patterns: AI can be used to identify patterns in financial data that may be difficult for humans to spot. This information can then be used to identify potential problems or opportunities.
- Making predictions: AI can be used to make predictions about future trends and events. This information can then be used to make better decisions about spending.
- Providing insights: AI can be used to provide insights into financial data that may not be obvious to humans. This information can then be used to make better decisions about spending.
- Protecting data: AI can be used to protect financial data from fraud and unauthorized access. This is important for ensuring the integrity of financial systems.
SAS® Business Intelligence (BI) uses a variety of AI technologies, including:
- Machine Learning (ML): identify patterns in financial data and to make predictions about future trends.
- Natural Language Processing (NLP): understand the meaning of text data, such as financial reports and contracts.
- Computer vision: analyze images and videos, such as invoices and receipts.
- Robotic Process Automation (RPA): automate tasks such as data extraction and reporting.
In an interview with Jim Goodnight, the founder and CEO of SAS Institute, he mentioned that SAS is looking into providing customers with instructions on how to use SAS better using a Generative AI solution.
Altimate | Savantage Solutions
Altimate® (formerly FFMS™) offers financial management services to enhance the efficiency and effectiveness of the Federal government's financial management business. Whether deployed as a core financial system, or as individual modules to supplement other applications, it meets many diverse business needs. Altimate is a workhorse – offering extensive capabilities to streamline, automate, report, control and monitor an agency’s accounting and financial transactions, activities and data. In addition to several hundred standard reports and query screens, Altimate’s business intelligence, analytics and dashboard features provides users extensive flexibility in reporting and trend analysis.
The Altimate Suite of Financial Management Applications include the following modules.
- Funds Management: optimizes the user's ability to record, control, and monitors all activities related to establishing funding authority and budgetary resources all the way to sub-allocations, and also enforces real-time funds availability checks. It includes three sub-modules:
- Program, Project and Activity (PPA) Reporting
- Budget Preparations, Formulation, and ExecutionSavantage Mobile Applications
- Commitment and Obligation Processing and Tracking
- Real-Time Funds Control
- General Ledger Management: USSGL compliant.
- Payments Management: complies with Prompt Pay and other applicable Federal requirements for managing payables and disbursements.
- Asset Management: provides capabilities for managing various types of assets used by Federal agencies from acquisition or purchase all the way through disposal.
- Receipts Management: supports standard receivables activities, as well as highly sophisticated reimbursable agreements processing.
- Cost Management: automates the tracking of direct and indirect costs (both labor and expenses) against budgeted amounts and allows users to perform complex cost allocations.
- Mobile Applications: empower users on the go. Our mobile applications are platform agnostic and secure, and ensure no data resides on the actual mobile device.
Application of ChatGPT
- Application of ChatGPT to Build an FP&A Tool | Glenn Hopper - GitHub
- A startup CFO used ChatGPT to build an FP&A tool—here’s how it went | Sheryl Estrada - Fortune
- Deep Finance: Corporate Finance in the Information Age | Glenn Hopper; finance professional and tech evangelist - Amazon
- FP&A Today, Episode 47, Glenn Hopper: Using ChatGPT to Build an FP&A tool and What Happened Next | Jonathan Marciano - DataRails
Course
Hindsight to Foresight
Fraud Detection
- Embedding ... Fine-tuning ... RAG ... Search ... Clustering ... Recommendation ... Anomaly Detection ... Classification ... Dimensional Reduction. ...find outliers