Daily Tech Digest - July 08, 2024

How insurtech startups are addressing the challenges of slow processes in the insurance sector

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. 

Transforming Business Practices Through Augmented Intelligence

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.

Request for proposal vs. request for partner: what works best for you?

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.”

If you’re a CISO without D&O insurance, you may need to fight for it

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.’ “

How DORA is fortifying Europe’s financial future with a new take on operational resilience

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 Sprawl: Continuing Problem for the Enterprise or an Untapped Opportunity?

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. 

AI’s moment of disillusionment

AI, whether generative AI, machine learning, deep learning, or you name it, was never going to be able to sustain the immense expectations we’ve foisted upon it. I suspect part of the reason we’ve let it run so far for so long is that it felt beyond our ability to understand. It was this magical thing, black-box algorithms that ingest prompts and create crazy-realistic images or text that sounds thoughtful and intelligent. And why not? The major large language models (LLMs) have all been trained on gazillions of examples of other people being thoughtful and intelligent, and tools like ChatGPT mimic back what they’ve “learned.” ... We go through this process of inflated expectations and disillusionment with pretty much every shiny new technology. Even something as settled as cloud keeps getting kicked around. My InfoWorld colleague, David Linthicum, recently ripped into cloud computing, arguing that “the anticipated productivity gains and cost savings have not materialized, for the most part.” I think he’s overstating his case, but it’s hard to fault him, given how much we (myself included) sold cloud as the solution for pretty much every IT problem.

How nation-state cyber attacks disrupt public services and undermine citizen trust

While nation-states do have advanced capabilities and visibility that are hard or impossible for cyber criminals to replicate, the general strategy for attackers is to target vulnerable perimeter devices such as VPNs or firewalls as an entry point to the network. Next they focus on obtaining privileged credentials while leveraging legitimate software to masquerade as normal activity while they scout the environments for valuable data or large repositories to disrupt. It’s important to note that the commonly exploited vulnerabilities in government IT systems are not distinctly different from the vulnerabilities exploited more broadly. Government IT systems are often extremely diverse and thus, subject to a variety of exploits. ... Currently, there are numerous policies and regulations, both domestically and internationally, which are inconsistent and vary in their requirements. These administrative requirements take significant resources which could otherwise be used to strengthen a company’s cybersecurity program. 

How Quantum Computing Will Revolutionize Cloud Analytics

As we peer into the future of quantum computing in cloud analytics, the emphasis on collaboration and continuous innovation becomes undeniable. Integrating quantum technologies with cloud systems is not just a technological upgrade but a paradigm shift requiring robust partnerships across academia, industry, and government sectors. For instance, IBM’s quantum network includes over 140 members, including start-ups, research labs, and educational institutions, working together to advance quantum computing. This collaborative model is essential because the challenges in quantum computing are not just about hardware or software alone but about creating an ecosystem that supports an entirely new kind of computing. That ecosystem comprises components such as quantum hardware development, quantum algorithms, software tools, and educational resources. Also, it has made significant achievements, such as developing quantum hardware such as the IBM Quantum System One, advancing quantum algorithms for practical applications in chemistry and materials science, and creating the Qiskit software development kit to make quantum programming more accessible.

How continuous learning is reshaping the workforce

Gone are the days when lengthy training programs were sought after and people took breaks from their careers to pick up an upskilling program. Navpreet Singh highlights that upskilling will become an ongoing process integrated into the workday. “The focus will shift from acquiring specific job skills to fostering adaptability and lifelong learning. Critical thinking, problem-solving, and creativity will be paramount as automation takes over routine tasks. Traditional ways of learning may not always reflect the skills needed. Alternative credentials, like badges and micro-credentials, will showcase the specific skills employees possess, making them more competitive. By embracing this future of upskilling, we can ensure our workforce is adaptable, future-proof, and ready to drive innovation in the ever-evolving automotive industry,” explains Singh. Within the next decade or so, we will see greater demand for agile ed-tech tools that help employees learn on the go and prepare them for new roles, says Daniele Merlerati, Chief Regional Officer APAC, Baltics, Benelux at Gi Group Holding.

Quote for the day:

"Perseverance is failing nineteen times and succeeding the twentieth." -- Julie Andrews

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