July 08, 2024
Kannan Subbiah
FCA | CISA | CGEIT | CCISO | GRC Consulting | Independent Director | Enterprise & Solution Architecture | Former Sr. VP & CTO of MF Utilities | BU Soft Tech | itTrident
Even though compliance and regulation are critical for the security of both the insurers and customers, the regulatory process could be quite long. Compliance requirements demand meticulous attention to detail and can significantly prolong the approval process for new products and services. Another factor can be risk aversion. It (risk aversion) within the industry fosters a culture of caution, where insurers are hesitant to embrace change and experiment with new approaches to product development and underwriting. ... One of the solutions for these industrial challenges lies in the collaboration of the insurance sector and the latest technologies. Insurtech solutions offer myriad innovative tools and technologies that promise to streamline product development and automate underwriting processes. One such solution gaining traction is artificial intelligence (AI) and machine learning algorithms, which can analyse vast amounts of data in real time to assess risk and expedite underwriting decisions.
While AI raises apprehensions about potential job displacement, viewing it solely as a threat overlooks its capacity to enhance human capabilities, as evidenced by historical technological advancements. Training and education play a key role in this process, as AI has become an integral part of our reality and must be harnessed to its full potential. It is essential to align the use of artificial intelligence with the overall strategy of the organization for smooth integration of applications with data, processes, and collaboration between stakeholders. In a landscape where the internet simplifies transactions, software provides tools, and AI leverages data to make informed decisions, training and education become crucial. ... At its core, technology has always revolved around processing data. When viewed through the lens of enterprise architecture, an AI-powered machine learning tool can adeptly craft roadmaps tailored for businesses. Through advanced AI analytics, automation, and recommendation systems, enterprise architecture facilitates more informed and expedited decision-making processes.
An RFProposal is an efficient choice when the nature of the work is standardized, while an RFPartner is the better choice when the buying organization is seeking a strategic partner for the overall best fit to meet its needs. ... When organizations shift to wanting to find a partner with the best possible solution, it’s important to understand the nature of the selection criteria change. With an RFPartner, buyers evaluate suppliers not only based on technical capabilities but also on the best value of the solution. ... “On the surface, an RFPartner sounds like a heavy lift, but we find that the overall time and effort is about the same,” he says. “In an RFProposal, the buyer is spending more time upfront defining the specs and in contentious negotiations. The RFPartner process flips this on its head and creates a more integrated bid solution that generates better solutions, spending more time together with the supplier co-creating, especially if your aim is making the shift to a highly collaborative vested business model to achieve strategic business outcomes.”
Recommended by LinkedIn
D&O insurance covers the personal liabilities of corporate directors and officers in the event of incidents that lead to financial losses, reputational damage, or legal consequences. Without adequate D&O coverage, CISOs are left vulnerable, highlighting the need for this in an organization’s risk-management strategy. ... Lisa Hall, CISO at privately held Safebase, agrees that CISOs at all companies should be covered under their organizations’ D&O insurance policies, particularly in light of these new regulations. “I do think adding CISOs to D&O insurance will be more and more of a thing, and there is, for sure, more chatter in my CISO groups about how companies are handling this,” she says. “A lot of CISOs are also taking out errors and omissions insurance personally. I have that just for the consulting and advisory work I do.” ... “A lot of CISOs are thinking about this, especially after SolarWinds,” she says. “And if we feel that we’re not 100% protected for any decision we make, and we can be personally liable for a breach or possible incident even if we do the right thing, it’s really pushing CISOs to say, ‘Hey, company, I’ll join if you cover me or give me a different title.’ “
For DORA, digital operational resilience very simply means “the ability of a financial entity to build, assure, and review its operational integrity and reliability by ensuring, either directly or indirectly through the use of services provided by ICT third-party service providers, the full range of ICT-related capabilities needed to address the security of the network and information systems which a financial entity uses, and which support the continued provision of financial services and their quality, including throughout disruptions”. Developing on this statement in a conversation with FinTech Futures, Simon Treacy, a senior associate at global law firm Linklaters, describes DORA as “a very prescriptive framework for financial entities, primarily to build and improve the way that they manage ICT risk”. “It applies very broadly across the EU regulated financial sector,” he continues, “and really part of its aim is to harmonise standards so that the smallest payments firm is subject to the same rules for operational resilience as the biggest banks and insurers.”
Data fabric technologies excel in integrating and managing data across various environments. However, they often focus on conventional data sources like databases, data lakes, or data warehouses. The result is a gap in integrating and extracting value from data residing in numerous SaaS applications, as they may not seamlessly fit into these traditional data repositories. The combined solution of data fabric and iPaaS can address complex business challenges, such as integrating data from SaaS applications with traditional data sources. This capability is particularly valuable in today’s business landscape, where data is increasingly scattered across various cloud and on-premises environments. The merging of data fabric and iPaaS technologies offers a groundbreaking solution to this challenge, opening the door to new opportunities in data management and analysis. The integration of data fabric with iPaaS addresses the complexity and expertise-dependency in iPaaS. Data fabric can enable users to discover, understand, and verify data before integration flows are built.