Generative AI
The case for AI-driven cost optimisation in finance
Research about the prevalence of AI in business by a top management consulting company has shown that 54% of business leaders are anticipating a cost saving of 10% or above in 2024 through Gen AI for a competitive advantage.
Gen AI automates complex processes, predicts anomalies and fraud, and enhances data categorisation to drive cost savings within financial operations. Businesses can use it to uncover hidden cost optimisation opportunities.
This article discusses the benefits of Gen AI for business and cost savings in its financial operations (FinOps).
Gen AI for spend analysis and cost reduction
Advanced real-time analytics are replacing traditional spend analysis capabilities to reshape cost reduction strategies in financial operations. Some of the ways you can use Gen AI for business cost reduction are:
Data processing and analysis
Traditionally, data processing and analysis have been reactive. However, using Gen AI in financial operations automates 60-70% of data processing to reduce the time and effort spent. Businesses can proactively identify spending trends, revenue leaks, anomalies, and avenues for cost reduction in financial operations.
Evaluate supplier performance
Supplier performance, including delivery times, delays, quality of goods, and compliance with contract terms, plays a vital role in a company’s financial health. Using Gen AI for business operations can help analyse these key metrics proactively to assess supplier reliability and cost-optimisation opportunities. With Gen AI, you can find suitable suppliers and negotiate favourable terms with existing ones for cost reduction.
Real-time spend monitoring
Detect and track any deviation in annual budgets and alert the relevant teams to take corrective actions. With a real-time feedback loop, you can prevent cost overruns and adhere to financial plans before any significant financial damage.
Spending categorisation
For large businesses dealing with several suppliers, categorising their spending is a challenge. Gen AI in financial operations can do all of this and identify cost-saving opportunities. Isolate areas of overspending, redundancies, and supplier or product consolidation and develop targeted strategies.
Forecast spending
Analysis of historical spending data and patterns can help you arrive at accurate future expenses. Use this information to build efficient budgets, allocate resources efficiently, and avoid unwanted costs. Forecasting can simulate financial scenarios to plan for different economic conditions.
Data-driven virtual scenario modelling
Virtual scenario modelling is helpful in predicting the financial health, expenses, and risk exposure of a business. With AI for business, you can create realistic scenarios (e.g., a critical supplier goes out of business) and test the impact in a virtual environment for precise planning. This saves your business from costly errors and reactive measures.
Market intelligence gathering
Use Large Language Models (LLMs) to crawl the internet and discover market trends, shifts in customer demand, and competitors. You can also provide customers with the facility to leverage LLM and search the company’s vast financial data for insights and summaries.
Financial reporting and information analysis
AI models for business help generate financial reports such as balance sheets, profit and loss statements, investor relation documents, annual budgets, and compliance and risk reports. Reduce the manual labour by letting Gen AI do the work while your staff reviews and audits, thus adding value.
Optimising FinOps with Gen AI
Gen AI has continuously made headlines for its ability to optimise costs by automating and simplifying financial operations. This impact spreads across industries, be it manufacturing, communications, finance, retail, professional services, healthcare, and more. By integrating Gen AI into their core operations, companies are proactively maintaining equipment, reducing administrative costs, and increasing their profit margins.
Studies have shown that 20% of manufacturers have already implemented Gen AI in financial operations, and 30% are planning to do so in the next three years. A leading global automobile brand has added value worth $1,200k by using Gen AI to improve back-office efficiency.
A global management consulting firm, in its study, found that by using Gen AI for contemporary business operations like predicting mechanical failures and performing proactive maintenance, manufacturers can increase uptime by 20%. This reduces breakdowns by 75% and increases productivity by 25%, directly impacting the bottom line.
A medical equipment manufacturer found that by identifying weak links in large machines with electronic components, they can reduce repetitive medical tests by 30% and increase the report quality by 100%. This reduces the capital investment by $555 thousand.
How can Infosys BPM help with optimising financial operations with AI?
The AI-first platform from Infosys BPM uses Gen AI with ready-to-use BPM solutions to add value to financial operations. Infosys Topaz comes with 12,000+ use cases and 150 pre-trained AI models to help your business simulate scenarios and optimise costs.
Read more about AI for business at Infosys BPM.
