Finance needs extra care, as even a small mistake can lead to a big loss. For example, a simple program like Excel can be confusing with a single human error. The finance workforce feels around-the-clock pressure to meet job-related deadlines. They need to work on the massive volume of data, and here, advanced financial AI solutions become a requirement. Like other industries, Finance also needs workflow automation to make things easier, more accurate, and error-free.
If you run a financial company or work for an organisation and struggle with regular manual processes and basic human typing or reporting errors, make your business advanced with smarter solutions.
Vidya Peters, the CEO of DataSnipper, an intellectual automation platform, noted that data management with traditional manual processes is becoming difficult for the finance teams of companies. She stated:
“Over 70% of finance leaders cite inefficiency as a key barrier to productivity, and human error accounts for up to 40% of financial restatements. This creates strong demand for DataSnipper, which automates data extraction, matching, and analysis. Enterprise demand is driven by the need to improve accuracy, streamline workflows, and shift teams away from administrative tasks toward higher-value insights”.
She added:
“Automation is the only way teams can keep pace, ensure consistency and quality, and meaningfully reduce risk at scale.”
AI Integration With Excel
People use DataSnipper for Excel Online to extract information directly from the source documents in the workbook. This platform also offer AI capability in the cloud which helps in the automation integrate with the company’s existing technological infrastructure.
She remarked:
“The future of enterprise automation is hybrid. It involves a mix of integrated AI in existing tools like Excel, ERP, audit platforms, as well as cloud-based solutions that offer scalability.”
The users are more interested to know how AI can enhance tools like Excel, that they are already using. AI integration is working to meet the growing demand for local control with cloud scalability. She believes that the DataSnipper is able to automate directly within Excel and enable financial teams to observe instant efficiency advancements without disruption of their existing workflow.
Hybrid solutions are appealing because, in the end, the choice of where AI processing occurs depends on a combination of security requirements, data sensitivity, IT architecture, and legal considerations. Peters mentioned:
“Hybrid lets enterprises move fast with AI while staying in control of their data and infrastructure”.
Deployment Difficulty
The core challenge in the deployment of AI in finance or other regulated industries is maintaining accuracy and transparency. The DataSnipper tool addresses this isse with its ability to trace. Peters stated:
“Unlike black-box models, DataSnipper’s AI provides assistive automation while keeping auditors in control, aligning with strict regulatory standards in audit and finance.”
The fact that different locations have different AI regulations presents another difficulty, necessitating that DataSnipper maintain flexibility in its data strategy. Peters noted:
“Europe’s evolving AI Act and strict data privacy rules require very deliberate implementation, while in the United States, firms are more focused on audit defensibility and SEC expectations. Our approach is to build adaptable AI that aligns with regulatory frameworks, while helping them stay ahead of what’s coming next.”
AI and Finance: Integrated Future
Peter said that the Asian companies should also pay attention to regulatory and cultural differences. She mentioned:
“This allows us to adapt fully to local requirements, different decision-making structures, and business cultures, while also ensuring that AI and automation align with regional expectations in a sector where trust is a cornerstone principle. It’s why we are making such a large investment in the region with local teams that can serve our customers in their language and time zones”.
As per her, AI will continue automating the most difficult portions of the finance and audit workflows in the coming years, while not replacing the auditor. The goal is to empower users with more than just productivity, according to DataSnipper CEO.