9 August, 2018

We’ve seen a diverse set of industries embrace the highly efficient and precision-enhancing benefits of advanced AI technology of late to help them transform their business connections for the better. However, it comes as no surprise that the traditionally change-resistant insurance industry has been slower in adapting to the global shift towards explainable Artificial Intelligence (XAI).

The technological power of XAI lies in its intuitive supply of human-interpretable explanations, a software platform effective at explaining the reasons behind why data decisions have been made. This enhanced data insight is for both underwriters and their customers to gain, about what kind of outputs are being generated from a variety of inputs; this effectively allows for better internal communication between technical and business users, and an improved experience for better informed customers.

On account of this, XAI is being acknowledged as a force that essentially opens up the ‘black box’ style of Machine Learning by making XAI answerable to both regulators and customers.

XAI not only enables decision makers to show what inputs drives the results, but the real game changer is how they can best influence the model which suggests its unlimited potential ahead for reshaping the future of underwriting.

It’s ‘access all areas’ benefits like these opened up to both the insurers and the insured that has triggered a notable rise in businesses proactively starting to experiment with novel ways to integrate XAI into their day-to-day operations. XAI has several key assets that businesses can take advantage of: not only does explainable outputs help make faster, smarter data driven decisions along the entire customer journey, but equally impressive is its clarity of performance to predict, automate and improve underwriting management processes.

There is now clear evidence that XAI is starting to transform the underwriting business operation as a whole, from quote conversion, risk pricing to claims process optimisation and customer retention.

In essence, XAI technology presents less risk, better decisions and more growth. Such concise, consistent and transparent data analysis has increased underwriters’ capability in providing policyholders with more personalised risk assessment and tailor-made price-appropriate premiums plus a detailed level of explanation around their calculations. The enablement of faster, better, more consistent business decisions and the clarity to customers will serve to increase business retention long term.

In addition to a high speed, highly empowered data management process, XAI offers better protection against fraud as well as a reduction in insurers’ cost and loss ratio, enabling them to more efficiently allocate underwriter resources and concentrate on more profitable cases with high margins.

The transformation has been beneficial for improving efficiency at the operational level too, through a fundamentally more streamlined insurance process that better connects applicants with insurance companies more effectively, effortlessly and transparently.

The transformation XAI can make to the management of a business is quick and simple and through a platform users can access as a cross-functional self-service resource with the ability to dramatically improve their decision making processes across the board.


Risk appraisal is becoming more and more the realm of machine learning in underwriting. The integration of XAI and how its performance lends itself to best practice in business accountability, responsibility, and transparency is vital to underwriters’ ability to best analyse and evaluate potential risk.

Accessibility is a key component of XAI and indeed serves to increase the same to a host of business boosting benefits: these are not only acquired through more relevant data sources with which to heighten accuracy in the risk assessment process but also through a more intelligent explanation of potential exposure to the insurers themselves better enables them to provide solid reasoning behind more responsible decision making with which to forward foster their client relationships.

Essentially, more adequate risk assessment translates to more appropriate insurance premiums which itself proves beneficial in the long run to both the insurers and the insured. In an industry where the difference between the competition largely rests on price, the availability of more automatic data consumption and customization that’s easy to translate can only benefit customers in paying for adequate insurance coverage they truly need.

This signifies boundless XAI automation potential for future transformation of the insurance sector especially in terms of the all-inclusive business model, in developing new products for the benefit of all, and taking them to market more rapidly than ever before.


Fraudulent claims have always been a major concern for insurance companies, so the integration of XAI technology as a key watchdog that actively resolves system loopholes is radically transforming insurers’ fraud prevention operations. Advanced machine learning offers the ability to increase pass rates whilst maintaining or reducing current default risk; this translates to a more profitable bottom line and enables insurers to re-use capital more effectively.

The current trends prove that the market will likely move towards insurance companies that are able to best harness XAI to improve the customer on-boarding and claim management processes (and keeping ever mindful too of staying ahead of the anticipated rise in fraudulent activities against the advances of XAI).

With self-service data visualisations representing a key part of XAI Machine Learning Platforms, insurance decision makers are better able to understand how to work a more interactive insurer-insured relationship without the need to have data scientists in house to interpret the data on their behalf.


The end goal of making XAI transparent, explainable, and accountable is for the technology to enhance human expertise, rather than replace it. Not only is XAI both time-effective and real time-sensitive in its predictive data capabilities, these means of data usage offer an improved business relationship that both customers and insurers can enjoy through underwriters recommending more bespoke products and services.

Furthermore, XAI is also bridging the gap between the insurer and the insured by eliminating the need for third party distribution chains. By reducing the complexity of information intercepted from a myriad of sources and the amount of data entry and re-entry, there is once again less room for human error to reinforce a higher level of accuracy and efficiency.

This likewise plays an important part in strengthening underwriters’ ability to optimise the channels and spend used

for lead acquisition and to identify more cross-sell and up-sell opportunities in tailoring offers to the right lead profile, in addition to providing more efficient customer service.


The long and short of it is rather than focusing on performance alone, explainable Artificial Intelligence has the potential to transform the management of every aspect of the underwriting business, and ensure best practice accountability, responsibility, and transparency every step of the way, from underwriting and predictive analysis, to risk mitigation and claim settlement.

Following new GDPR procedures, there is no doubt that there has ever been a better time for insurance companies to implement more transparent forms of digital technologies in their operations if they hope to remain in business with their competitors in the near future.

The potential that XAI offers the future of the insurance sector and its clients cannot be overstated. Its impact may yet to be fully implemented, but the exciting techniques and applications of XAI available to the market so far, has allowed insurance industries to extract unprecedented customer intelligence and drastically improve customer experience, and will prove to be the way forward in XAI research.

Logical Glue’s team of highly experienced team of machine learning experts helps the insurance industry harness the explosive power behind XAI and Data Science: our cost-effective solution provides the business- critical assurance that insurers and lenders need through our expert marrying of cloud-based machine learning, data science and lending acumen as an intuitive learning experience.

Logical Glue’s Machine Learning Platform has been specially developed to equip underwriters with a powerful self-service data platform to justify decisions based on the principle of accountability and produce an
auditable trail that details their analysis. The results are already proving profound: enhanced communications between business users internally and customers externally is helping our insurance clients achieve higher conversions rates of up to 40% and an uplift in profits of up to 20%.

Logical Glue’s experts ensure that the way underwriters utilise data to guide their decision-making is collected, created, and managed in a fair and clear manner, taking care to minimise bias and enforcing privacy and security.

XAI making its way into the insurance sector has already started to transform things for good and with time and the support of Logical Glue, the impact of its transformation is limitless.