Integrating Technology for Enhanced Audit Efficiency and Risk Management in Real Estate Banking

The meeting point of technology and real estate banking has radically changed audit processes and risk management structures. This paper evaluates the combination of developing technologies (including artificial intelligence (AI), machine learning (ML), blockchain, robotic process automation (RPA), and cloud computing) into real estate audit operations within banking institutions.Through review of current applications, case studies, and industry shifts, this research shows how technology acceptance improves audit performance, improves risk review accuracy, and strengthens legal requirements. Banking is expected to produce a yearly capacity of USD 200 billion to USD 340 billion of added economic value from AI uptake, mostly from increased productivity. The findings show that integrated technology solutions reduce audit cycle times by up to 50 percent, increase property value accuracy by 15 to 30 percent, and permit instant monitoring skills previously impossible through manual processes. This study examines the powerful role of technology in improving performance review and risk management in the real estate banking sector. By boosting machine learning and automation, financial institutions can ease audit processes, find potential risks, and make calculated decisions. This detailed framework examines the planned rollout of artificial intelligence, machine learning, robotic process automation, blockchain, cloud computing, and advanced metrics to change traditional manual audit processes into intelligent, automated, and fact-based tasks that deliver better risk insights while reducing costs and response times.