Case Study: Tier 1 Bank Raises Match Rates from 88% to 95% with AI
Updated: 1 day ago
In short: A Tier 1 bank was manually matching thousands of bank transactions a day after its rules ran. Matchimus raised the average match rate from 88% to 95%, removed about 4,000 manual matches a day and cut mismatches from around 200 to 6 per day.
The finance industry is undergoing a significant transformation, driven by the rapid advancements in Artificial Intelligence (AI). One area where AI is making a substantial impact is reconciliation, a critical process for ensuring the accuracy and integrity of financial data.
Reconciliation automation, powered by AI, is transforming how financial institutions operate, offering unprecedented levels of efficiency, accuracy, and cost savings.
The Challenges of Traditional Reconciliation
Traditionally, reconciliation has been a manual, time-consuming, and error-prone process. Financial institutions often deal with vast amounts of data from various sources, making it challenging to match and reconcile transactions. This manual effort not only consumes valuable resources but also increases the risk of errors and delays in financial reporting.
AI Reconciliation Automation
AI is transforming reconciliation by automating the matching of transactions, identifying discrepancies, and resolving exceptions. AI-powered systems can analyse large datasets, learn patterns, and make intelligent decisions, significantly reducing the need for manual intervention.
Case Study: Operartis and AI Matching Technology
Operartis builds machine-learning matching for reconciliation and exceptions management. Their AI Matching Technology, as demonstrated in a case study with a tier 1 investment bank, highlights the transformative potential of AI in finance.
The Challenge:
The investment bank, managing over $3 trillion in assets, faced a significant challenge with its daily FX and derivatives trade settlement cashflows reconciliation process. Their existing in-house ML-based matching system, while improving match rates, still required a team of over 20 people to manually match between 5000-10,000 bank transactions daily. This manual intervention was costly, time-consuming, and prone to errors.
The Solution: Matchimus by Operartis
The deployment of Matchimus by Operartis brought about a dramatic improvement in the bank's reconciliation process. Matchimus, powered by AI, significantly boosted average matching rates from 88% to 95%. This reduced the manual match workload by an average of 4000 bank transactions per day, translating to 70 user hours saved daily.
The Results:
Increased Efficiency: Matchimus reduced manual intervention by 80%, freeing up valuable resources for more strategic tasks.
Improved Accuracy: Matchimus achieved a match accuracy of 99.99%, dramatically reducing mismatches from 200 to just 6 per day.
Cost Savings: The reduction in manual workload and the elimination of errors resulted in significant cost savings for the investment bank.
The Benefits of Reconciliation Automation with AI
The case study with Operartis clearly illustrates the numerous benefits of reconciliation automation with AI:
Enhanced Efficiency: AI-powered systems can process vast amounts of data much faster than humans, significantly reducing reconciliation time.
Improved Accuracy: AI algorithms can identify and resolve discrepancies with greater accuracy than manual processes, minimising errors and improving data integrity.
Reduced Costs: Automation reduces the need for manual labour, leading to substantial cost savings.
Better Compliance: Accurate and timely reconciliation is crucial for regulatory compliance. AI-powered systems help financial institutions meet their obligations more effectively.
Increased Scalability: AI systems can easily handle increasing volumes of data, allowing financial institutions to scale their operations without compromising efficiency or accuracy.
Focus on Strategic Initiatives: By automating routine tasks, AI helps finance professionals to focus on higher-value activities, such as strategic analysis and decision-making.
The Future of Reconciliation Automation and AI in the Finance Industry
Reconciliation automation is just one example of how AI is transforming the finance industry. AI is being applied to various other areas, including fraud detection, risk management, customer service, and investment management. As AI technology continues to evolve, its impact on the finance industry will only grow, leading to greater efficiency, accuracy, and innovation.
AI-powered reconciliation automation is transforming the finance industry, offering significant benefits in terms of efficiency, accuracy, and cost savings. The case study of Operartis and its AI Matching Technology demonstrates the transformative potential of AI in streamlining financial processes. As AI continues to advance, it will play an increasingly vital role in shaping the future of finance, enabling institutions to operate more effectively and deliver greater value to their customers.
Frequently asked questions
What did the Tier 1 bank achieve with AI matching?
The average match rate rose from 88% to 95%, about 4,000 manual matches a day were removed, and mismatches fell from around 200 to 6 per day.
How does AI reconciliation differ from rules-based matching?
Rules only match when fixed conditions are met. AI matching learns from historical decisions, so it can match transactions with inconsistent references or narratives that rules miss.
What happens to transactions the AI isn't sure about?
Matchimus gives each proposed match a confidence score. Low-confidence items go to analysts for review, so the team stays in control of the exceptions.
Ready to Take Control of Your Financial Data?
Operartis can help you modernise your reconciliation processes and realise the power of your financial data. Our Proof of Value (PoV) assessment provides a personalised evaluation, allowing you to see the tangible benefits of our solutions before committing. We'll measure the match rate improvement on your reconciliation data and provide a detailed report outlining your potential return on investment (ROI).
Book a free Proof of Value
Book a Proof of Value and discover how automation can transform your financial data management. Let's work together to increase efficiency, improve exception management, reduce costs, and enhance visibility into your financial data, helping you to thrive in the ever-evolving financial landscape.
