The BFSI industry depends heavily on IT infrastructure to provide a variety of services, including core banking, mobile, and internet. When conducting financial transactions using online banking websites and other financial apps, security is among the top concerns. Financial services organizations view the use of AI in cybersecurity as essential.
Cyberattacks have the capacity to destroy major company networks and get access to private and sensitive data that is normally protected by sophisticated security systems and protocols. Depending solely on cybersecurity professionals might not provide a failsafe defense against significant hacker attacks. Banks have made significant investments in artificial intelligence and BFSI software testing to meet the necessary objectives surrounding security.
Diving Into The Current Scenario
It has been noted that more businesses are using AI to stop fraud and cyberattacks than other vendor-related services. Given this, it's critical to examine how the installation of artificial intelligence interacts with the security measures implemented by banks so that, in the case of a malicious cyberattack, a complete strategy can be established.
Banks in the U.K. spend GBP 6.7 billion annually, according to Ocorian, to protect themselves from cybercrime. Cyberattacks are on the rise, especially for banks and other financial services firms, as a result of the ongoing integration of the internet across BFSI channels and web & mobile applications.
The financial industry is now quite concerned about cyberattacks. Banks and other financial organizations are making significant investments to make digital services available through many channels, which is generating new vulnerabilities.
In response to the COVID-19 issue, cyberattacks on banks and other financial institutions rose by 238% globally between February 2020 and April 2020, according to the VMware Carbon Black Threat Data report. In order to safeguard applications and digital assets against manipulation and fraud, organizations working in the banking sector are heavily utilizing application security testing technologies and services.
Insurance providers can identify consumer behaviour that could result in fraudulent claims using AI-based cybersecurity solutions, which helps them save time and money and protect real-time applications and minimize insurance premiums for clients.
The Need For Security Upgrades
In order to acquire clients' trust and provide seamless services, banks and other financial institutions must also provide a convenient and safe user experience. As a result, the market for AI in cybersecurity is expanding as a result of the rising demand for AI-powered cybersecurity products and services in the banking industry.
In the BFSI industry, AI-based cybersecurity solutions are crucial because they improve overall business performance by predicting cyberthreats, ensuring regulatory compliance, and securing data protection. Due to the size of the customer base and the sensitive financial information involved, the BFSI sector is vulnerable to data breaches and cyberattacks. For instance, 70% of financial services organizations reported cyberattacks in 2020, according to Keeper Cyber Security, Inc. (U.S.).
In such circumstances, cybersecurity software & services can successfully guard digital assets against threats of fraud and manipulation. Additionally, AI-based cybersecurity solutions enable insurance carriers to identify client behaviors that can result in false claims, saving time and money, and bringing down insurance costs for clients.
Why Artificial Intelligence?
Given the tremendous potential of the BFSI sector, major players in the AI in cybersecurity market are concentrating on increasing their market shares by releasing fresh and cutting-edge products. For example, BirlaSoft (India) and Regulativ.ai (UK) collaborated in 2021 to co-develop a new AI/ML-based cyber-regulatory reporting platform for international BFSI clients. Additionally, OneSpan, Inc. (U.S.) decided to use Vera-security code's testing technology in 2020 to safeguard businesses from fraud.
The BFSI sector benefits from investments in AI-based cybersecurity technology because it delivers automated regulatory cybersecurity evaluation and reporting, significant cost savings, identity verification and authentication, and enhanced company performance. Therefore, it is anticipated that the increased use of AI-based cybersecurity solutions in BFSI businesses will help the segment's growth.
By enabling user identification and authorization, identity and access management (IAM) enables BFSI to regulate access to sensitive data. Access privileges are available, internal and external data breaches are less likely, and standards governing user authentication and validation are enforced thanks to AI-based IAM. In order to increase security statistics, it also provides contextual insights and behavioural data analysis. Similar to this, machine learning (ML) may examine user login attempts and identify dubious actions like password guessing.
Natural Language Processing (NLP)
Artificial intelligence (AI) has a subfield called "Natural Language Processing" that works with using natural language to ease interactions between machines and people. To successfully use natural language, NLP aims to recognize, understand, and analyze its patterns and important information. In order to identify any data or relationships that might point to potential cybersecurity risks and attacks, banks utilize NLP to scan enormous datasets of emails and other information.
Before an attacker attacks the internal systems, banks conduct highly complex security checks using NLP to find weaknesses and hazards, giving them plenty of time to stop the attack. NLP-based cybersecurity policies and ongoing monitoring of emails and data entering the financial system can quickly identify and isolate patterns of malicious conduct.
High-Level Machine Learning (ML) Products
Another branch of AI that offers sophisticated applications for cybersecurity in the banking industry is machine learning. Machine learning and neural networks can be used by the IT departments and teams at banks to effectively foresee the next moves that an attacker might make.
Products and services made possible by machine learning enable banks to track threats and security issues in real-time, making the entire security process much more pro-active and effective. They are able to quickly identify suspicious activity and fraudulent transactions, confirm user identity, and take rapid action to stop cyberattacks.
Additionally, data scientists can train systems to detect any attempts at money laundering or to isolate prospective cyberattacks in order to reduce and manage the consequences of such attacks.
For instance, if you use online banking, you are already aware that the inability to verify your identity has a direct impact on your ability to access your account and, in certain situations, even to suspend all transactions to and from the account. This occurred as a result of an algorithm alerting the banking system to your status as an illegal user and blocking your access.
Wrapping Up!
Artificial intelligence is no longer a cutting-edge technology with a sporadic presence in the corporate sector. It is today one of the most widely used technologies in practically every industry, but especially in the banking and financial services sectors.
To improve user security and fend off cyberattacks, banks can use artificial intelligence and its many application areas. If banks only rely on cybersecurity employees, it would simply fetch the risk of having inadequate safety and declining user trust, while having a comprehensive security policy that includes banking software testing with the correct use of AI can be a very beneficial long-term business strategy.
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An application stands out among numerous ordinary tools, as it has turned into the most convenient and effective channel of interaction with customers.Today’s consumer would rather choose a bank with a convenient website, Internet banking, a user-friendly mobile application and speedy services; indicators such as interests and deposit rates, or the place of a bank in some ratings, are placed on the back burner.
Hence, to win the loyalty of clients and remain competitive, a bank should be mobile.Some statistics to prove the increasing popularity of banking apps: Mobile banking users are expected to exceed 1.75 billion by 2019, representing 32% of the global adult population, according to Juniper research.45% of respondents named convenience the main reason they started using mobile payments, Statista found out.As of June 2018, the financial business is in the top of the most popular Android app categories worldwide, taking 53% of the market share.Statista also provided data on the availability of the world’s leading payment providers Apple Pay, Samsung Pay and Android Pay in global regional markets.
It turned out that the Asia-Pacific region has the highest number of total active markets across all three payment systems.
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The global BFSI security market size is estimated to reach USD 74.3 billion by 2025, expanding at a CAGR of 13.1%, according to a new report by Grand View Research, Inc. Increasing risk of data loss owing to cyberattacks on banks and insurance companies is anticipated to propel the growth.
Thereby, cyber threats have prompted financial institutions to deploy reliable safety solutions at their premises.Frequent emergence of new malware variants is driving demand for advanced safety solutions in the banking, financial services and insurance security market.
For instance, in 2016, a mobile malware, masked as an application upgrade, was discovered.
The malware displayed fake sites over authentic banking homepages for filching banking credentials of consumers.
Financial databases stored on cloud create need to verify safety systems of the cloud service provider.
The market is lucrative in developing regions, such as Asia Pacific, owing to digitalized business operations in the BFSI industry.Financial companies are stressing on consumer data protection and are implementing solutions such as firewall and threat management software.
