Balancing Product Innovation & Profitability: For Insurance & InsurTechs in Africa

Vol. 03 | 20.08.2024 | Miller Kingsley, FNAS, FSA

Introduction

Understanding Insurance Risk Principles:? Insurance is a critical component of financial stability, yet specific principles must be met for a risk to be insurable. These principles ensure that the risk is manageable, measurable, and ethical for both the insurer and the insured. For a risk to be insurable, usually, the following rules must be met:

1. Variability in Occurrence: There must be variability involved in the occurrence, timing, or magnitude of the occurrence. Whilst death is a certainty, the timing is uncertain and this makes it insurable.
2. Statistical Evaluation: The risk must be statistically evaluable to determine the likelihood of occurrence.
3. Moral hazard-free: The risk that a human intentionally sets off the risk should not be involved as that risk is difficult to quantify.
4. Not contrary to public policy: The provision of this insurance must not offend the general public’s sensibilities and the law. For example, providing an insurance cover for ‘yahoo yahoo’ (internet fraud) may appear innovative but since it would contravene the law and the general public’s sensibilities, it is not a good innovation.

Innovation Centres

As the insurance industry evolves, so do the risks and the ways in which they are managed. Innovation is crucial in responding to emerging risks, enhancing product features, and improving efficiency. Taking into consideration the basic principle of insurance risks, here are three broad areas of Insurance innovation, each addressing different aspects of risk, customer needs, and transforming the industry:

Emerging Risks

These are innovations focused on new risks which have not traditionally been covered by insurers. There is usually little data to price them and they present a huge pricing risk to the company. Recently, COVID was also a new risk, which insurers had to deal with

Additional features

This involves taking a product or risk that is already well covered within the market and padding it with more benefits. For example, taking a regular endowment product that pays a benefit at the end of 10 years with a feature that allows the customer to withdraw his funds at any time prior the 10 years. This is not a new risk covered but just an additional benefit to improve the product’s marketability

Efficiency Enhanced

This involves adding a feature to an existing product line, focused on improving the customer experience. This is an important category of innovation in today’s digital world where efficiency is now critical. For example, adding a digital process that ensures claims can now be paid within 24 hours

Potential Innovation Areas

As the insurance landscape evolves, several areas stand out as potential hotspots for innovation:

Telematics- Internet of Things

Using wearables to track the performance of assets like vehicles to record driver behaviour which could impact motor insurance pricing, and tracking health lifestyle which could impact life and health insurance pricing.

AI

AI presents 2 routes of opportunities for innovation in insurance:

1. Emerging risks arising from AI, for example, insurance to mitigate increased cybersecurity risks and bias and legal risks will need to be developed.
2. It could be employed to improve product features, gather big data for analysis, and product personalisation.

Product Personalisation

The future of product development is likely to be even more personal with every customer having his own product for his particular circumstance, instead of a generic product with limited options which everyone buys into

Payments

The ease with which customers can get their claim payments is still a big focus area of innovation. As our customer base involves the newer generations, the patience to run through traditional claim underwriting wanes and the insurer who settles faster is likely to have the future.

The Trade-off

While innovation is essential for growth, it comes with trade-offs that insurers must carefully consider. Here are some of the key challenges associated with this innovation:

Data

It can be difficult to get data to back up innovations. For example, if we introduce telematics on cars to track driver behaviour and impact premium, how do we know what the relationship between behaviour and claims is from day 1? Such data will only become available as time progresses but the insurer cannot afford to wait or track without action. Customers will not want to be used as guinea pigs and they expect action from Day 1. Emerging risks pose even further data challenges because if there was enough data to quantify it, it probably would no longer be an emerging risk

Pricing points Complexity

To price a product, usually, there would be a few data points to consider, such as Age, Gender, Asset Type and so on. Innovation however forces us to introduce new data points for consideration which further complicates the pricing models and introduces the risk of ‘spurious accuracy’. The pricing complexity challenge is a trade-off to consider in innovation. There is no point in having a product which cannot be efficiently priced for and the cost of building a proper pricing model may outweigh the benefits of the product feature.

As our customer base involves the newer generations, the patience to run through traditional claim underwriting wanes and the insurer who settles faster is likely to have the future.

Solutions

To navigate these challenges and successfully innovate in insurance, several strategies can be employed:

Dive In

As with all notable successes in life’s history, people have to dive in and take some risks at some point. You will never have enough information at the beginning of any notable innovation but history tells us those who win big are those who went in head first. Whilst care is required in protecting your head when going head first (proper mental modelling of the action, mitigations of worse case scenarios). A shot taken could be missed but a shot not taken is always a shot missed

Actuarial models

Actuaries could be useful in thinking through proxies that could be used for product pricing in the absence of the actual data needed. For example, if we do not have a death statistic in Nigeria for insured lives, what other potential data which resembles the pattern expected, could be used?

Phases

It helps to phase your ‘diving in’. For example, using analogies, you may want to do the first dive, with the mattress on the floor, the next dive on hard ground but with a helmet on and the 3rd dive on hard ground with no helmet but phasing in this way allows you to build on your experience. For example, perhaps you start with a waiting period of 12 months and as you get comfortable you gradually reduce this until it is 0 or whatever

Monitoring

This is a very critical step in the innovation & profitability trade-off. Having dived right in, with the benefit of actuarial modelling and common-sense judgements, you want to ensure that on a conscious and periodic basis, you are comparing your actual against your expected experiences and making informed adjustments as necessary. Adjustments could involve:

1. Taking out features you had added
2. Adjusting the pricing up or down
3. Adding more features.

Nothing beats a graphical chart of your experience and the more automated this process is, the more reliable it is. It is not an end-of-the-world scenario to have losses at the beginning of the product cycle. What is a problem is if these losses were not anticipated and if they continue to perpetuity or until the company enters ruin.

Miller Kingsley, FSA is a Fellow of the Society of Actuaries in the USA and the Nigerian Actuarial Society . He is also an Associate of the Chartered Institute of Insurance in Nigeria. ?His professional Actuarial experience spans over 18 years across the banking and insurance sectors. He is currently the CEO, Evolutics Technology and the President of the Nigerian Actuarial Society .

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