The BFSI sector is highly dependent on IT infrastructure to deliver several services, such as mobile, online, and core banking. Security is among the primary concerns when performing financial transactions through online banking portals and other financial apps. The use of AI in cybersecurity is considered critical by financial services organizations, and according to Ocorian, banks in the U.K. spend GBP 6.7 billion each year to safeguard themselves from cybercrimes. With the consistent incorporation of the internet across BFSI channels and web & mobile applications, cyberattacks are becoming increasingly common, particularly for banks and other financial services institutions.
Cyberattacks have become a major concern for the banking sector. Banks and financial institutions are investing heavily in enabling digital services through multiple channels, creating new vulnerabilities. According to the VMware Carbon Black Threat Data report, cyberattacks against banks and financial institutions increased by 238% globally between February 2020 and April 2020 amidst the COVID-19 crisis. Therefore, organizations operating in the banking sector are incorporating application security testing tools and services on a considerable scale to protect applications and digital assets against manipulation and fraud. For instance, in 2021, BorlaSoft (India) partnered with Regulativ.ai (U.K.) to co-develop a new AI/ML-based cyber-regulatory reporting platform for global BFSI customers. In 2020, Mastercard, Inc. (U.S.) introduced Cyber Secure, an AI-powered suite of tools that allows banks to assess cyber risks across their ecosystems and prevent potential breaches. Furthermore, AI-based cybersecurity solutions enable insurance providers to recognize customer behavior that may lead to fraudulent claims, helping them save time and money and secure real-time applications, which helps lower insurance premiums for customers. Banks and financial institutions also need to offer a convenient and secure user experience to gain customers’ confidence and enable seamless services. Thus, the increasing demand for AI-powered cybersecurity solutions and services in the banking sector drives the growth of AI in the cybersecurity market.
AI-based cybersecurity solutions play an important role in the BFSI sector as they help predict cyber threats, ensure regulatory compliance, and boost overall business performance. The BFSI sector is prone to data breaches and cyberattacks due to the large customer base and the financial information at stake. For instance, according to Keeper Cyber Security, Inc. (U.S.), 70% of financial services organizations reported cyberattacks in 2020. In such cases, cybersecurity software & services can effectively protect digital assets against manipulation and fraud risks. Also, AI-based cybersecurity solutions allow insurance providers to recognize customer behaviors that may lead to fraudulent claims, saving time and money and lowering insurance premiums for customers.
Considering the BFSI sector’s high potential, prominent players in the AI in cybersecurity market are focused on maximizing their market shares by launching new and innovative solutions. For instance, in 2021, BirlaSoft (India) partnered with Regulativ.ai (U.K.) to co-develop a new AI/ML-based cyber-regulatory reporting platform for global BFSI customers. Additionally, in 2020, OneSpan, Inc. (U.S.) selected the Veracode security testing solution to protect financial institutions and other organizations from fraud.
Investments in AI-based cybersecurity technology are beneficial for the BFSI sector as the technology offers automated cybersecurity regulatory assessment & reporting, significant cost savings, identity verification & authentication, and improves business performance. Thus, the growing adoption of AI-based cybersecurity solutions in BFSI industries is expected to support the growth of the BFSI segment.
Identity & access management (IAM) enables user authentication and authorization, allowing BFSI to control access to sensitive information. AI-based IAM offers access privileges, reduces the risks of internal and external data breaches, and enforces policies around user authentication and validation. Additionally, it offers contextual insights and behavioral data analysis through machine learning to improve security statistics. Similarly, ML can analyze user login attempts and detect suspicious behavior such as password guessing.
According to the 2020 Verizon Data Breach Investigations Report, 81% of data breaches in companies or organizations leveraged stolen or weak passwords. Leading organizations, therefore, emphasize advanced cybersecurity to avoid data breaches. With the growing volume of access rights to administer across, many large organizations are struggling to manage and secure the fluid nature of user privileges. For instance, in 2019, Accenture PLC (Ireland) launched a next-generation digital identity & access management (IAM) capability to help organizations reduce the risk and costs associated with the over-provisioning of accounts tied to a user’s identity. Thus, IAM solutions help banking organizations meet industry compliance requirements and save costs by minimizing the time needed to deal with user account-related issues. These benefits are expected to increase the adoption of identity & access management solutions in the coming years.
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