Existing insurers and disruptors are utilizing Artificial Intelligence to create new business models

We can see that Artificial Intelligence (AI) is transforming many parts of our lives, but do we know where this journey is taking us? Insurers need some certainty on what their future will looks like. Some new insurers are trying new business models enthusiastically and then changing direction sharply, like a speedboat swerving to avoid a collision. The larger insurers, however, are like large cruise ships; they need to be able to see far ahead before they plot their course, and they don’t want to keep changing direction.

This research tried to identify the viable AI driven business models to help give some clarity. Some traditional insurers are just trying to be more effective with AI, while others reinvent themselves to fully utilize the new capabilities available. Tech-savvy companies from outside the sector like Tesla, are entering and disrupting it. Would these diverging paths continue, or would they converge in the future towards one, ideal, business model? This research focused on one example of a traditional insurer and one new tech-savvy disruptor and evaluated whether their models are converging.

AI is changing the insurance value chain, as illustrated in figure 1. Most new insurers, like Tesla, offer fully automated simple services. The traditional insurers offer some of their simpler services in this way. The more complex services are supported with AI, but a human makes the final decision. An example of this are audits for fraud, where the AI identifies unusual patters and cases for an expert to evaluate.

There are signs of convergence between the models of traditional and new insurers. First, there is convergence in technologies, such as the use of chatbots utilizing AI. Second, there is a convergence in processes, for example, the interaction with the consumer. Third, there is convergence in the strategy on costs and pricing.

However, there are two areas where there seems to be a limit on convergence, which seems to suggest the business models of the incumbent and the disruptor will remain distinct. These are: (1) evaluating risk and (2) the cost of attracting the user and profitability.

Despite some convergence, certain differences are likely to remain even after this transitionary period. This is because the two models have distinct competitive advantages. Traditional insurers no longer monopolize the capability of providing insurance, but they still have the existing user base and utilize it to evaluate risk. Technology-savvy companies that now offer insurance, have their own forms of engagement with their consumers, use different methods to evaluate risk due to their access to real time data, and do not prioritize generating revenue but instead utilize insurance to increase their user base, overcome barriers, and reduce the overall cost of their products and services.

Therefore, when insurers are thinking about how to utilize AI and plot their course through the turbulent, unpredictable times ahead, they should stay true to what they are. This is their comparative advantage.

Dr Alex Zarifis is a lecturer at the University of Nicosia in Cyprus.

This article is adapted from his paper, “Evaluating the New AI and Data Driven Insurance Business Models for Incumbents and Disruptors: Is there Convergence?” available from https://doi.org/10.52825/bis.v1i.58.

The future of automation for UK asset managers

The last 18 months have been amongst the most disruptive that the financial services industry has ever experienced, forcing many sectors to reconsider business models.

Asset managers in particular have undergone a substantial transition as video conferencing has replaced client-facing interactions. To better understand how these firms have responded to market disruption, we surveyed 100 Heads of Operations across UK asset management firms to learn about their operational challenges, automation objectives and plans for regulatory compliance in 2022.

From this study, three lessons stood out for their relevance to the wider fintech industry:

1. Operational challenges and tech improvements are company-specific

We asked asset managers what does and doesn’t present a challenge to their daily operational processes.

While the availability of automated systems and adequately skilled staff were highlighted by two-thirds of respondents as the most significant challenge, firms also pointed to many others including the functionality of manual resources, process complexity and a changing regulatory burden.

Although nearly 8 in 10 acknowledge that the capabilities of current systems are hindering operational growth, firms have identified a range of priorities to improve these systems from seamless data flow, AI-assisted dashboards and dynamic data management through to enhanced risk management and talent acquisition.

The variety of responses tells us that no two firms face the same operational challenges and, consequently, that technology infrastructure improvements for 2022 will be equally varied in their application to the asset management industry.

2. Manual reconciliations continue to challenge asset managers

Reconciliation is an essential process for keeping accounts and financial records accurate. In recent years, more firms have been automating reconciliation procedures to eliminate risk of error and improve accuracy.

Despite this, our survey reveals that:

• 60% of asset managers worry that manual reconciliations are the greatest risk to their organisation
• 75% say that the number and volume of manual processes is an immediate operational challenge
• Only 7% say that manual processes present no challenge to their firm

Data preparation was also highlighted amongst the most time-consuming tasks for businesses, which further highlights how the complexity of data management continues to grow year on year. This is consistent with our work across other sectors, where we find that manual processing is really the core issue underlying poor reconciliation disciplines.

With half of UK asset management firms allocating budgets between £0.5 and £10m to address manual inefficiencies, we can expect automation to become more deeply embedded in the industry throughout this year.

3. Regulation is accelerating the trend towards automation

Although manual processing has been steadily declining for years in favour of automation, our findings show that a growing regulatory burden is definitely a factor in this transition.

Just 2% of asset management firms in the UK have no plans to invest in automation to achieve regulatory compliance. For the majority that did, top focus areas include operational resilience, prudential regulation, MiFID II and CASS. A further 7 in 10 felt that automation will be instrumental in achieving compliance with the IFPR regulation, which came into effect on 1^st Jan 2022.

These findings tell us that UK firms are actively pursuing automation as a convenient and cost-effective way to fortify against regulatory breaches. Nevertheless, with 42% still pointing to new or changing requirements as the biggest threat to their company, such solutions need to be flexible as requirements continue to grow in scope and complexity.

What does this mean for software providers?

The results of our survey clearly demonstrate that automation in finance will become ubiquitous in the medium to long-term. However, the variety of responses and priorities outlined also shows that firms do not want an off-the-shelf solution; instead, they want a reconciliation platform which:

• Is configurable to specific operational needs
• Eliminates manual intervention through end-to-end automation
• Is purpose-built around specific regulatory requirements
• Is flexible to accommodate for multiple iterations of regulations

Of course, these are welcome findings at AutoRek, where we have spent over two decades working with financial firms to build bespoke solutions for unique reconciliation, operational and regulatory requirements.

In the short-term, it is clear that asset managers recognise how automated reconciliation disciplines do and will continue to form the cornerstone of an effective business model in today’s post-pandemic environment. It will be interesting to see how this plays out across the wider financial industry over the next 12 months.

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