In this chapter, the authors discuss the importance of Decision Support Systems (DSS) in enhancing cybersecurity in financial institutions. It brings out the increased rate of cyber-attacks, including phishing, malware, denial-of-service (DoS), ransomware, and insider threats, which have resulted in massive financial and reputational losses in the entire financial industry. As financial institutions are becoming more reliant on digital infrastructures, cybersecurity has turned out to be a pillar of operational resilience, financial stability and customer trust. The study identifies the insider, external, structured, and unstructured attacks on decision support systems as a type of cybercrimes and highlights the way in which the vulnerabilities in the network systems and human behavior are exploited by each of the infrastructures. Some of the anti-protective techniques, such as multi-factor authentication, encryption, security audits, and capacity building of employees are also discussed. Another aspect that the chapter discusses is the way DSS combines data analytics, artificial intelligence, and machine learning to improve cyber threat detection, automated responses, and evidence-based decision-making. The major advantages of the cybersecurity DSS are enhanced threat detection, proactive security, resource optimization, and regulatory compliance. Nevertheless, issues such as high cost of implementation, quality of data, complexity of systems, and shortage of skilled manpower remain. Moreover, the paper determines specific cyber threats within capital markets e.g. market manipulation, third party risks and regulatory non-compliance and defines multilayer mitigation measures, including strong algorithm testing, surveillance, behavioral analytics, and vendor risk management. The authors have arrived at the conclusion that modern DSS cybersecurity models are essential in securing financial institutions, market integrity, and the confidence of users in the face of changing digital attacks.