We live in an age where technology has transformed virtually every industry, from transportation to healthcare to commerce. Yet finance, the lifeblood of the global economy, has remained stubbornly manual, relying on antiquated processes that are slow, error-prone and frustratingly inefficient. But change is afoot. Artificial intelligence (AI) and automation are poised to revolutionize financial reporting as we know it.
So what exactly is financial automation? And how can AI solutions like Kudra help finance teams streamline their operations while unlocking game-changing insights? Let’s explore the tremendous potential of automated finance.
What is Financial Automation?
In a nutshell, financial automation refers to the use of advanced technologies like robotic process automation (RPA), machine learning (ML) and AI to automate repetitive, manual financial procedures. This includes everything from processing invoices and financial statements to reconciling accounts and generating reports.
The unique capabilities of AI allow systems like Kudra to go far beyond basic automation. Kudra’s computer vision and natural language processing algorithms can intelligently parse unstructured documents like contracts and bank statements to automatically extract key data points. This structured data can then be exported to various endpoints to eliminate tedious manual data entry.
Kudra also enables users to set up custom AI workflows tailored to their specific reporting needs. Whether you want to analyze profit margins across business units, track accounts receivable aging or generate weekly cash flow forecasts, Kudra makes it possible to automate these processes with pinpoint accuracy.
The Advantages of Financial Automation
It’s easy to see why financial automation is creating so much buzz. AI-powered solutions promise tremendous benefits across the board:
1. Increased efficiency and productivity
Automating repetitive, low-value tasks allows finance teams to reduce manual work by up to 90% according to Deloitte. This frees up their capacity to focus on high-value activities like data analysis and strategy.
2. Improved reporting speed and agility
Instead of waiting days or weeks to collect and process data for financial reports, AI systems like Kudra generate insights in real-time. This enables much more nimble and data-driven decision making.
3. Enhanced data accuracy
AI is exceptionally precise, with some solutions achieving over 99% data accuracy. This minimizes costly errors that often occur with manual data entry and analysis.
4. Reduced costs
Automation yields considerable cost savings from lower headcount needs to reduced outsourcing fees. McKinsey estimates that intelligent process automation can deliver cost reductions of 25-50%.
These impressive benefits explain why 87% of CFOs expect to adopt some form of finance automation technology by 2025 according to Gartner. The finance function of the future will rely heavily on AI; so the ultimate question here is: ” How to speed up the interpretation of financial statements ? “
Setting up Financial Automation
Transitioning to automated financial reporting delivers tremendous upside. But it also represents a major change that requires careful planning and execution. Here are the key steps to ensure a smooth and successful implementation:
1. Assess processes for automation viability
The first step is to objectively evaluate existing financial processes to identify those best suited for automation based on factors like repetitiveness, time consumption and data quality/consistency. Common candidates include invoice processing, general ledger reconciliation and management reporting.
2. Select the right software
With the rise of financial automation, countless platforms now exist to choose from. Conduct thorough due diligence to select the best fit solution for your needs based on capabilities, ease of use, security features, scalability and total cost of ownership. Kudra stands out with its user-friendly visual workflow builder, library of pre-trained AI templates and advanced natural language processing capabilities.
3. Clean up existing data
Legacy financial data is often fragmented across various systems and may lack consistency. To train machine learning algorithms effectively, historical data must be consolidated, formatted properly and cleansed of errors. This is one of the most tedious but critical steps that pays dividends later.
4. Set up integrations
The key to impactful automation is integrating new systems like Kudra with your existing tech stack to seamlessly share data. Prioritize connecting Kudra to core platforms like your ERP, general ledger, bank feeds and business intelligence tools. APIs and pre-built connectors streamline this process.
5. Migrate and test transactional data
Once all the connections are set up, transactional data like invoices and journal entries can start flowing automatically from source systems into your automation platform. Rigorously test accuracy and functionality using real-world documents and data sets from different business areas. Identify and promptly address any issues before go-live.
6. Train AI algorithms
Machine learning algorithms “learn” by analyzing large volumes of high-quality, labeled data. Work closely with end users across finance and accounting to gather representative samples of financial documents and manually label the data you want the algorithms to extract. This training data is the fuel that makes Kudra’s AI so powerful.
7. Deploy automation in stages
Big bang automation deployments are high risk. Adopt a phased rollout plan starting with a limited scope, focused on streamlining a few specific processes for one business unit. Learn from this initial deployment and gather feedback to refine your approach before expanding automation more broadly.
Overcoming Implementation Challenges
While tremendously promising, finance automation also raises understandable concerns that must be addressed:
1. High costs
Automation requires upfront software investments and ongoing expenses for maintenance, support and cloud infrastructure. Focus on quantifying expected returns through cost and time savings. Cloud-based solutions like Kudra minimize infrastructure requirements for a faster breakeven point.
2. Integration complexity
Connecting new document processing technology like Kudra to multiple existing systems can seem daunting. Simplify integration by selecting automation tools with pre-built connectors, open APIs and support for modern data transfer protocols.
3. Information security
Any time you introduce new systems handling sensitive financial data, security risks increase. Mitigate this by only selecting automation platforms like Kudra with robust encryption, access controls and data protection capabilities that either match or exceed your own IT standards.
4. Resistance to change
Major process changes inevitably create anxiety and skepticism among stakeholders. Proactively communicate the compelling benefits of automation early and often. Involve key users in solution design and testing to build organizational alignment and excitement.
The Future of Finance with Automation
As AI and automation transform finance operations, the function will focus far less on manual data gathering and number crunching. Technology will handle these tedious responsibilities instead. This leaves finance leaders free to provide more strategic guidance, leveraging instant insights unlocked by automation.
Forward-thinking CFOs recognize the monumental impact AI innovation can have according to PWC research showing that finance executives view AI as a business advantage rather than a threat. And solutions like Kudra sit at the forefront of this digital finance revolution.
Kudra’s intelligent document processing capabilities directly address one of the biggest pain points holding back finance teams today – the frustrating inefficiency of manual document and data handling. By intelligently automating these cumbersome processes, Kudra delivers the speed, agility and actionable insights modern businesses expect from finance.
The future for finance is automation. AI propels accurate, real-time reporting so leaders can course correct quickly. Technology handles the drudgery so people can focus on high-value analysis and decision support. And innovation platforms like Kudra make this future achievable for enterprises worldwide. The intelligent finance function is now. Are you ready to join the revolution?
