Cloud computing adoption across industries has revolutionized enterprise operations while introducing significant challenges in compliance management. Organizations must continuously meet evolving regulatory requirements such as GDPR and ISO 27001, yet traditional manual review processes have become increasingly inadequate for modern business scales. This paper presents a novel machine learning-based framework for automating cloud computing compliance processes, addressing critical challenges including resource-intensive manual reviews, extended compliance cycles, and delayed risk identification. Our proposed framework integrates multiple machine learning technologies, including BERT-based document processing (94.5% accuracy), One-Class SVM for anomaly detection (88.7% accuracy), and an improved CNN-LSTM architecture for sequential compliance data analysis (90.2% accuracy). Implementation results demonstrate significant improvements: reducing compliance process duration from 7 days to 1.5 days, improving accuracy from 78% to 93%, and decreasing manual effort by 73.3%. A real-world deployment at a major securities firm validated these results, processing 800,000 daily transactions with 94.2% accuracy in risk identification.

It is well-established that accounting is a data-intensive stream. It is filled with numerical, non-numerical, statistical and non-statistical data. There is data involved in invoices, purchase orders, employee salaries, daily expenses and a load of other things. Such enormous amounts of data can get overwhelming after a point. Accounting professionals have to undergo a tedious process to collect and analyze such enormous amounts of data. Moreover, the data is scattered at various sources.

Then Luca BRUNI will introduce you to our speakers and special guests. Then Luca BRUNI will introduce you to our speakers and special guests.

Banks around the world are continuing to be penalized heavily for their inability to meet with ever-changing and complex financial regulations. Regulatory fines imposed in 2017 alone proved this to us in many ways. For example, financial intelligence regulator Austrac handed gaming giant Tabcorp a fine of AUD 45 M (USD 35 M) for non compliance, the highest ever civil penalty in corporate Australian history. We also saw U.S. authorities hit BNP Paribas with fines amounting to approximately USD 600 M for market misconduct and trader collusion that took place over 6 years. The big fines also keep coming for Deutsche Bank, the German lender was hit with about USD 630 million in penalties on a USD 10 billion Russian money-laundering scheme.