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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