Empowering Decisions by Quantifying Risks – Zeron

1. Can you give us an overview of Zeron and its mission in the cybersecurity space?

Zeron is a pioneer in the realm of cyber risk posture management, offering a revolutionary AI-powered platform designed to streamline and exemplify cyber dynamics. Our Cyber Risk Posture Management (CRPM) platform serves as the linchpin, accelerating trust and establishing a single point of truth for cybersecurity.

At the heart of Zeron is the commitment to centralize and standardize cybersecurity data. This, in turn, empowers stakeholders by providing them with the necessary insights to make well-informed decisions. Our platform acts as a conduit, bridging the inherent gap between security experts and decision-makers.

2. What inspired the founding of Zeron, and what specific gaps in the market are you addressing?

The inspiration behind the founding of Zeron was the recognition of significant gaps in the cybersecurity landscape, particularly the need for innovative solutions to quantify cyber risks and bridge trust gaps among stakeholders involved in cybersecurity decision-making. We identified that many organizations struggled with navigating the complex and rapidly evolving cyber threat landscape, often lacking the necessary tools to make informed decisions about their cybersecurity posture.

3. Can you explain what the Quantified Business Exposure to Risks (QBER) model is and how it differs from other cyber risk quantification models?

The Quantified Business Exposure to Risks (QBER) model is an advanced cyber risk quantification tool designed to identify emerging cyber threats and provide businesses with accurate risk assessments. QBER leverages advanced technology and data analysis to evaluate a business’s level of risk, facilitating effective resource allocation. Unlike traditional models, QBER integrates comprehensive industry-specific data—including market cap, employee count, endpoints, security solutions, and regulatory mandates—to deliver a detailed view of cyber risks. This model also offers actionable advice to help businesses bolster their cybersecurity and make informed decisions regarding insurance coverage.

4. How does the QBER model specifically benefit BFSI (Banking, Financial Services, and Insurance) companies?

The QBER model provides significant benefits to BFSI companies by offering a comprehensive and dynamic approach to cybersecurity management. It helps BFSI organizations identify emerging threats promptly, ensuring they are well-informed of potential risks. By accurately assessing their risk levels, QBER enables these companies to allocate resources effectively and strengthen their cybersecurity measures. The model also considers the unique aspects of BFSI companies, such as their size and existing security measures, to provide tailored advice for risk mitigation. Additionally, QBER supports regulatory compliance by integrating industry-specific data, helping BFSI companies navigate the increasingly stringent regulatory environment with greater accountability.

5. How does Zeron leverage AI in its cybersecurity solutions to provide real-time insights and strategies?

Zeron leverages AI in its cybersecurity solutions in multiple ways to provide real-time insights and strategies:

Policy Gap Analysis: Zeron’s in-house ZIN AI engine scrutinises every line of an organization’s security policies to identify gaps and weaknesses. This enables organizations to strengthen their policies proactively, ensuring they align with industry best practices and regulatory requirements.

Real-time Incident Analysis: Zeron’s AI-powered platform analyses security incidents in real-time, providing organizations with immediate insights into the nature and severity of threats. This allows for swift and effective incident response, minimising the impact of cyberattacks.

6. Can you share some examples of how AI has helped your clients improve their cybersecurity posture?

Examples of how AI has helped clients improve their cybersecurity posture:

Enhanced Policy Compliance: By identifying gaps and weaknesses in their existing security policies, Zeron’s AI-powered solution helped a client achieve 98% compliance with industry standards and regulatory requirements. This significantly reduced their risk of non-compliance penalties and data breaches.

Faster Incident Response: Another client experienced a 50% reduction in incident response time thanks to Zeron’s AI-powered platform. The platform’s real-time analysis of security incidents enabled the client to quickly identify and address threats, minimizing the impact of cyberattacks.

Optimized Security Investments: By quantifying cyber risks in financial terms, Zeron’s QBER model helped a client prioritize their security investments and allocate resources more effectively. This resulted in a 30% reduction in overall security costs while maintaining a high level of protection.

7. Being the first in India to launch an advanced CRQ model, what impact do you foresee this having on the Indian cybersecurity landscape?

The launch of the QBER model marks a significant milestone in India’s cybersecurity journey. As the first advanced CRQ model in the country, QBER addresses two critical challenges: the rapidly evolving cyber threat landscape and the increasingly stringent regulatory environment. Its introduction is expected to enhance the overall cybersecurity posture of Indian organizations by providing them with robust risk management solutions. By enabling businesses to make informed decisions about cyber risk mitigation strategies, resource allocation, and regulatory compliance, QBER will help organizations stay ahead of emerging threats and meet regulatory requirements more effectively. This, in turn, will foster a more secure and resilient business environment in India, driving greater confidence in the country’s digital ecosystem.

8. What challenges did you face in developing the QBER model, and how did you overcome them?

Challenges in developing the QBER model and how they were overcome:

The primary challenge in developing the QBER model was understanding the unique business context of each organization to ensure accurate risk quantification. Different parameters and factors contribute to cyber risk for different organizations, depending on their industry, size, and specific vulnerabilities.

To overcome this challenge, Zeron adopted a collaborative approach, working closely with clients to gather relevant data and insights about their business operations, assets, and potential threats. This enabled Zeron to tailor the QBER model to each client’s specific needs, providing more accurate and actionable risk quantification.

9. What are the future plans for Zeron in terms of product development and market expansion?

Zeron’s future plans involve focusing on cyber risk quantification using its QBER model, which encompasses categorising cyber risks and assessing their impact across various industries, notably healthcare, which faces the highest data breach costs. Furthermore, Zeron aims to assist organizations by recommending mitigation strategies through tailored action plans. These plans will outline necessary tool investments or updates, along with corresponding financial requirements, aimed at enhancing cybersecurity measures.

Additionally, Zeron plans to facilitate insurance providers with estimated cyber value at risk for the organization. This capability will enable insurance providers to create more informed insurance policies, accurately charge premiums, and provide risk coverage tailored to the specific cybersecurity needs of organizations. This integration will help organizations better manage and mitigate cyber risks through comprehensive insurance solutions aligned with their risk profiles and mitigation strategies. The ultimate goal of Zeron is to be the Single Point of Truth for Cybersecurity.

10. How do you see the role of AI evolving in the field of cybersecurity over the next five years?

Over the next five years, AI will play a pivotal role in changing the cybersecurity landscape. As AI algorithms become more sophisticated, they can be utilised to identify patterns in cyberattacks, enabling organizations to detect potential threats in advance and predict new attack vectors that may pose risks to specific organizations. Given the vast volume of security data that needs analysis to extract actionable insights, AI will help organizations make informed decisions to strengthen their cybersecurity posture. AI-powered systems will increasingly automate response actions to security incidents, reducing human intervention time and mitigating threats in real-time.

Human psychology has always played a pivotal role in the successful execution of cyber attacks. With the increasing adoption of AI, these models will analyse user behaviour and establish baselines, allowing for more reliable authentication processes and early detection of suspicious activities. Moreover, AI tools will assist cybersecurity professionals by automating routine tasks, enabling them to focus on more complex challenges and strategic initiatives.

AI with ease of use also brings in concerns on the

11. What emerging cybersecurity threats should fintech organizations be most aware of?

Fintech organizations should be cognizant of cybersecurity threats that require vigilant defences. Ransomware remains a top concern, with attackers increasingly targeting financial data and systems for hefty ransoms. Phishing attacks, especially whaling attacks, directed at high-profile targets, like C-level executives and use the social engineering, email spoofing and content spoofing methods to access sensitive data.. Distributed Denial-of-Service (DDoS) attacks can cripple online services, disrupting customer access and damaging reputations. Mobile Device Security Risks, as observed in the recent times Mobile Applications are a cornerstone of FinTech, providing convenient access to financial services. However, they are susceptible to security vulnerabilities due to their widespread usage. APIs and third-party integrations also pose security challenges, potentially exposing sensitive data through poorly secured connections. Additionally, Insider threats from disgruntled or negligent employees can lead to data breaches.

As fintech continues to innovate, robust cybersecurity measures, including employee training, threat monitoring, and advanced encryption, are essential to safeguard assets and maintain customer trust.