Episode #17: AI answers: What AI tools have been introduced to the finance department?
Me: Can you share with other panellists on the Roundtable what AI tools have been introduced to the finance department and how effective have they been?
The above question was 5th out of 5 questions to which I was invited to discuss around the Roundtable on Thursday, the 21st of September by Roger Laird, BizEdocs https://bizedocs.ie/wp/ together with:
1. Akhil Jain CTO Wayleadr
2. Anees ur-Rehman CEO and Founder
3. Angie Mezzetti CEO Ocarina Productions
4. Augusto Bernardo CEO Myndware
5. Cormac O'Neill CEO & Chief Tempo Officer Webio Ltd
6. Jan Filipowiak Founder Virtualist
7. Katarzyna Haśnik CEO Hasnik Limited, myself
8. Michael McGuinness Founder & Product Manager Tachyon Tech
9. Norbert Narbut Founder ExtendedMedia
10. Paul McCabe Chief Operating Officer VLE Therapeutics
11. Philbert Nshimiyimana Process Support Specialist PSC Biotech Corporation
12. Rusty Weise Chief Technology Officer & Sr. Architect Trakwell.ai
13. Tony Duddy COO, Board Member Memjet Technology
14. Yang Tong, Founder and CEO OrderIT Ltd
15. Zohaib Jabbar CTO Fund Recs
It is always inspiring to learn from like-minded business, Founders, CEO, CTO, COO people.
Thank you Andrea Ryan https://www.linkedin.com/in/andrea-ryan-sales/ and Angelica Ganados for organising it.
Now, let's ask OpenAI: https://openai.com/. What does AI think about it? (P.S.: Split of seconds in providing another answer, but indeed, OpenAI the free ChatGPT already knows that the last knowledge update was in September 2021. Meaning there is a space for us at the Roundtable to be a bit "smarter" than AI.)
ChatGPT: Certainly, I can provide an overview of some AI tools that have been introduced to the finance department and their effectiveness as of my last knowledge update in September 2021. Please note that the landscape of AI tools and their effectiveness may have evolved since then, so it's important to consider the most current information.
Robotic Process Automation (RPA):
RPA tools have been widely adopted in finance for automating repetitive and rule-based tasks, such as data entry and reconciliation.
They have proven to be highly effective in reducing errors, increasing operational efficiency, and freeing up finance professionals to focus on more strategic tasks.
Machine Learning for Credit Scoring:
Machine learning models have been used to assess credit risk by analyzing large volumes of data, including credit history, financial statements, and macroeconomic factors.
These models have improved accuracy in credit risk assessment, resulting in better lending decisions and reduced default rates.
Fraud Detection and Prevention:
AI-based fraud detection systems utilize machine learning to analyze transactions and identify unusual patterns or anomalies.
These tools have been effective in preventing fraudulent activities and minimizing financial losses.
Chatbots and Virtual Assistants:
Chatbots and virtual assistants are used for customer support and internal queries in finance.
They have improved response times, reduced the workload on human staff, and enhanced customer service in some cases.
Predictive Analytics for Forecasting:
Predictive analytics models use historical financial data to forecast future trends, such as sales, revenue, and expenses.
These tools have helped finance departments make more accurate financial projections and strategic decisions.
Natural Language Processing (NLP):
NLP tools have been employed for sentiment analysis of financial news and social media data.
They provide insights into market sentiment and can be valuable for making investment decisions.
AI-driven algorithms are used for high-frequency trading, analyzing market data, and executing trades at optimal times.
These algorithms can respond to market conditions faster than human traders, potentially leading to better investment outcomes.
Effectiveness can vary depending on the specific AI tool, its implementation, and the quality of data used. Overall, AI has the potential to significantly enhance the efficiency, accuracy, and decision-making capabilities of finance departments. However, it's essential for organizations to continuously evaluate and adapt these tools to ensure they deliver the desired results and comply with regulatory requirements. Additionally, AI adoption may require upskilling of finance professionals to effectively leverage these technologies.
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