Revolutionizing the Finance World: AI in Accounting and its Impact

Paulina Lewandowska

11 Apr 2023
Revolutionizing the Finance World: AI in Accounting and its Impact

Introduction

The world of finance is ever-evolving, and technology has always been at the forefront of this transformation. One of the most exciting advancements in recent years is the growing use of artificial intelligence (AI) in various aspects of the finance industry, including accounting. AI is revolutionizing traditional practices, resulting in improved efficiency and accuracy while minimizing human error. Let's take a closer look at how AI is redefining accounting and its far-reaching impact on the finance world.

AI in Accounting Use Cases

A significant aspect of an accountant's job involves handling routine tasks, such as data entry, reconciliations, and report generation. AI-powered systems can efficiently deal with these repetitive duties, freeing up accountants to focus on more strategic responsibilities. Automating these mundane tasks not only saves valuable time but also reduces the risk of errors that come from manual input.

  • Enhanced Fraud Detection

Fraud in the financial sector is a persistent challenge, with businesses continuously seeking ways to combat it. Machine learning – a subset of AI – detects inconsistencies and anomalies within large data sets, making it highly effective for fraud detection. With AI capabilities, accounting systems can now identify irregular patterns or transactions in real-time, alerting businesses to potential fraudulent activities and minimizing losses.

  • Better Financial Forecasting

Predictive analytics is another area where AI proves instrumental for accounting professionals. By analyzing historical patterns, alongside external factors such as economic indicators and market trends, AI-driven algorithms can provide accountants with valuable insights into future financial performance. With more accurate forecasting information at their fingertips, businesses can make informed strategic decisions and better plan for future growth.

  • Improved Audit Process

Traditional audit methods rely on sampling techniques, which often consist of taking a subset of a company's transactions to assess compliance with regulations or internal policies. However, AI enables auditors to analyze entire transaction histories using intelligent algorithms designed to identify errors, anomalies, or signs of fraud. This comprehensive analysis guarantees a more thorough audit process and accuracy, allowing businesses to identify and address issues more effectively.

  • Personalized Financial Advisory Services

With the combination of AI and big data, accountants can provide tailor-made financial advisory services to their clients. By tapping into vast amounts of data from diverse sources, AI enables professionals to better understand their clients' financial needs, behavior, and goals. With these insights at hand, they can offer customized recommendations and strategies to help individuals or businesses achieve their financial aspirations.

Benefits of AI Accounting

Improved accuracy
One of the main advantages of using AI in accounting is the increased accuracy it brings to the table. Manual data entry and calculations can lead to errors, potentially costing businesses a significant amount of money. AI systems, on the other hand, minimize these mistakes by automating processes and cross-checking data for consistency.

Time savings
By automating manual tasks like data entry, categorization, and reconciliations, AI accounting tools free up time for accountants to focus on more strategic initiatives. This not only boosts productivity but also adds value to the services offered by accounting professionals.

Enhanced decision-making capabilities
AI technology can analyze large sets of financial data quickly and efficiently, identifying patterns and trends that may not be immediately apparent to human analysts. This enables accountants and business owners to make better-informed decisions based on real-time insights.

Fraud detection
With cybercrime being a prevalent issue in today's business world, AI-powered tools can help detect any suspicious behavior or anomalies in accounting records early on. This allows organizations to mitigate potential risks associated with fraud or financial mismanagement.

Cost savings
By automating routine tasks and reducing the need for manual intervention, AI accounting software helps businesses cut down on labor costs without sacrificing quality or accuracy.

Top AI-Driven Accounting Software & Tools for Streamlined Financial Management

In today's rapidly advancing technological landscape, artificial intelligence (AI) is revolutionizing the world of accounting and finance. The top AI-driven accounting software and tools offer exceptional solutions to facilitate streamlined financial management, enhancing efficiency, accuracy, and overall productivity. Stay ahead of the curve and transform your financial operations with these cutting-edge tools that are setting new standards for the industry.

Xero

Xero's AI-enhanced capabilities include automated bank feeds and invoice generation, which greatly simplify bookkeeping tasks and reduce human errors. The platform's intelligent algorithms allow for smooth integration with various banking institutions, providing real-time updates that make financial management more efficient for businesses of all sizes.

Sage Intacct

Sage Intacct employs state-of-the-art AI technology to automate financial tracking, ensuring consistent data across multiple business activities. This sophisticated software boosts overall financial accuracy and control, granting companies enhanced visibility into their financial performance and enabling better decision-making processes.

Botkeeper

Botkeeper combines innovative AI technology with certified accountants to provide precise bookkeeping services and real-time insights into a business's financial health. This cutting-edge approach empowers businesses to refine their financial management strategies while reducing the reliance on labor-intensive manual tasks.

Zoho Books

Zoho Books leverages artificial intelligence in its automated bank reconciliation feature, effectively eliminating the need for manual efforts by business owners in managing their finances. This capability allows them to closely monitor their financial status and ensure efficient allocation of funds throughout all aspects of their operations, ultimately contributing to sustained growth and success.

Conclusion

In conclusion, the integration of AI in accounting is revolutionizing the finance world and profoundly impacting the way businesses and individuals manage their financial activities. This technological transformation has the potential to increase efficiency, reduce errors, provide actionable insights, and enhance decision-making processes. As AI continues to mature and develop, its influence on accounting can only expand further, ensuring a more streamlined, accurate, and sophisticated future for the financial sector. Embracing these innovations will be crucial for organizations to stay competitive and adaptive in an ever-evolving landscape.

Tagi

Most viewed


Never miss a story

Stay updated about Nextrope news as it happens.

You are subscribed

Quadratic Voting in Web3

Kajetan Olas

04 Dec 2024
Quadratic Voting in Web3

Decentralized systems are reshaping how we interact, conduct transactions, and govern online communities. As Web3 continues to advance, the necessity for effective and fair voting mechanisms becomes apparent. Traditional voting systems, such as the one-token-one-vote model, often fall short in capturing the intensity of individual preferences, which can result in centralization. Quadratic Voting (QV) addresses this challenge by enabling individuals to express not only their choices but also the strength of their preferences.

In QV, voters are allocated a budget of credits that they can spend to cast votes on various issues. The cost of casting multiple votes on a single issue increases quadratically, meaning that each additional vote costs more than the last. This system allows for a more precise expression of preferences, as individuals can invest more heavily in issues they care deeply about while conserving credits on matters of lesser importance.

Understanding Quadratic Voting

Quadratic Voting (QV) is a voting system designed to capture not only the choices of individuals but also the strength of their preferences. In most DAO voting mechanisms, each person typically has one vote per token, which limits the ability to express how strongly they feel about a particular matter. Furthermore, QV limits the power of whales and founding team who typically have large token allocations. These problems are adressed by making the cost of each additional vote increase quadratically.

In QV, each voter is given a budget of credits or tokens that they can spend to cast votes on various issues. The key principle is that the cost to cast n votes on a single issue is proportional to the square of n. This quadratic cost function ensures that while voters can express stronger preferences, doing so requires a disproportionately higher expenditure of their voting credits. This mechanism discourages voters from concentrating all their influence on a single issue unless they feel very strongly about it. In the context of DAOs, it means that large holders will have a hard-time pushing through with a proposal if they'll try to do it on their own.

Practical Example

Consider a voter who has been allocated 25 voting credits to spend on several proposals. The voter has varying degrees of interest in three proposals: Proposal A, Proposal B, and Proposal C.

  • Proposal A: High interest.
  • Proposal B: Moderate interest.
  • Proposal C: Low interest.

The voter might allocate their credits as follows:

Proposal A:

  • Votes cast: 3
  • Cost: 9 delegated tokens

Proposal B:

  • Votes cast: 2
  • Cost: 4 delegated tokens

Proposal C:

  • Votes cast: 1
  • Cost: 1 delegated token

Total delegated tokens: 14
Remaining tokens: 11

With the remaining tokens, the voter can choose to allocate additional votes to the proposals based on their preferences or save for future proposals. If they feel particularly strong about Proposal A, they might decide to cast one more vote:

Additional vote on Proposal A:

  • New total votes: 4
  • New cost: 16 delegated tokens
  • Additional cost: 16−9 = 7 delegated tokens

Updated total delegated tokens: 14+7 = 21

Updated remaining tokens: 25−21 = 425 - 21 = 4

This additional vote on Proposal A costs 7 credits, significantly more than the previous vote, illustrating how the quadratic cost discourages excessive influence on a single issue without strong conviction.

Benefits of Implementing Quadratic Voting

Key Characteristics of the Quadratic Cost Function

  • Marginal Cost Increases Linearly: The marginal cost of each additional vote increases linearly. The cost difference between casting n and n−1 votes is 2n−1.
  • Total Cost Increases Quadratically: The total cost to cast multiple votes rises steeply, discouraging voters from concentrating too many votes on a single issue without significant reason.
  • Promotes Egalitarian Voting: Small voters are encouraged to participate, because relatively they have a much higher impact.

Advantages Over Traditional Voting Systems

Quadratic Voting offers several benefits compared to traditional one-person-one-vote systems:

  • Captures Preference Intensity: By allowing voters to express how strongly they feel about an issue, QV leads to outcomes that better reflect the collective welfare.
  • Reduces Majority Domination: The quadratic cost makes it costly for majority groups to overpower minority interests on every issue.
  • Encourages Honest Voting: Voters are incentivized to allocate votes in proportion to their true preferences, reducing manipulation.

By understanding the foundation of Quadratic Voting, stakeholders in Web3 communities can appreciate how this system supports more representative governance.

Conclusion

Quadratic voting is a novel voting system that may be used within DAOs to foster decentralization. The key idea is to make the cost of voting on a certain issue increase quadratically. The leading player that makes use of this mechanism is Optimism. If you're pondering about the design of your DAO, we highly recommend taking a look at their research on quadratic funding.

If you're looking to create a robust governance model and go through institutional-grade testing please reach out to contact@nextrope.com. Our team is ready to help you with the token engineering process and ensure that your DAO will stand out as a beacon of innovation and resilience in the long term.

Aethir Tokenomics – Case Study

Kajetan Olas

22 Nov 2024
Aethir Tokenomics – Case Study

Authors of the contents are not affiliated to the reviewed project in any way and none of the information presented should be taken as financial advice.

In this article we analyze tokenomics of Aethir - a project providing on-demand cloud compute resources for the AI, Gaming, and virtualized compute sectors.
Aethir aims to aggregate enterprise-grade GPUs from multiple providers into a DePIN (Decentralized Physical Infrastructure Network). Its competitive edge comes from utlizing the GPUs for very specific use-cases, such as low-latency rendering for online games.
Due to decentralized nature of its infrastructure Aethir can meet the demands of online-gaming in any region. This is especially important for some gamer-abundant regions in Asia with underdeveloped cloud infrastructure that causes high latency ("lags").
We will analyze Aethir's tokenomics, give our opinion on what was done well, and provide specific recommendations on how to improve it.

Evaluation Summary

Aethir Tokenomics Structure

The total supply of ATH tokens is capped at 42 billion ATH. This fixed cap provides a predictable supply environment, and the complete emissions schedule is listed here. As of November 2024 there are approximately 5.2 Billion ATH in circulation. In a year from now (November 2025), the circulating supply will almost triple, and will amount to approximately 15 Billion ATH. By November 2028, today's circulating supply will be diluted by around 86%.

From an investor standpoint the rational decision would be to stake their tokens and hope for rewards that will balance the inflation. Currently the estimated APR for 3-year staking is 195% and for 4-year staking APR is 261%. The rewards are paid out weekly. Furthermore, stakers can expect to get additional rewards from partnered AI projects.

Staking Incentives

Rewards are calculated based on the staking duration and staked amount. These factors are equally important and they linearly influence weekly rewards. This means that someone who stakes 100 ATH for 2 weeks will have the same weekly rewards as someone who stakes 200 ATH for 1 week. This mechanism greatly emphasizes long-term holding. That's because holding a token makes sense only if you go for long-term staking. E.g. a whale staking $200k with 1 week lockup. will have the same weekly rewards as person staking $1k with 4 year lockup. Furthermore the ATH staking rewards are fixed and divided among stakers. Therefore Increase of user base is likely to come with decrease in rewards.
We believe the main weak-point of Aethirs staking is the lack of equivalency between rewards paid out to the users and value generated for the protocol as a result of staking.

Token Distribution

The token distribution of $ATH is well designed and comes with long vesting time-frames. 18-month cliff and 36-moths subsequent linear vesting is applied to team's allocation. This is higher than industry standard and is a sign of long-term commitment.

  • Checkers and Compute Providers: 50%
  • Ecosystem: 15%
  • Team: 12.5%
  • Investors: 11.5%
  • Airdrop: 6%
  • Advisors: 5%

Aethir's airdrop is divided into 3 phases to ensure that only loyal users get rewarded. This mechanism is very-well thought and we rate it highly. It fosters high community engagement within the first months of the project and sets the ground for potentially giving more-control to the DAO.

Governance and Community-Led Development

Aethir’s governance model promotes community-led decision-making in a very practical way. Instead of rushing with creation of a DAO for PR and marketing purposes Aethir is trying to make it the right way. They support projects building on their infrastructure and regularly share updates with their community in the most professional manner.

We believe Aethir would benefit from implementing reputation boosted voting. An example of such system is described here. The core assumption is to abandon the simplistic: 1 token = 1 vote and go towards: Votes = tokens * reputation_based_multiplication_factor.

In the attached example, reputation_based_multiplication_factor rises exponentially with the number of standard deviations above norm, with regard to user's rating. For compute compute providers at Aethir, user's rating could be replaced by provider's uptime.

Perspectives for the future

While it's important to analyze aspects such as supply-side tokenomics, or governance, we must keep in mind that 95% of project's success depends on demand-side. In this regard the outlook for Aethir may be very bright. The project declares $36M annual reccuring revenue. Revenue like this is very rare in the web3 space. Many projects are not able to generate any revenue after succesfull ICO event, due to lack fo product-market-fit.

If you're looking to create a robust tokenomics model and go through institutional-grade testing please reach out to contact@nextrope.com. Our team is ready to help you with the token engineering process and ensure your project’s resilience in the long term.