Trust Automation - A way for insurers to speed up customer service, enhance trust, and reduce costs

Oct 10, 2023

Distrust by default

US retail magnate Joseph Wanamaker used to say that he knew 50% of his vast advertising budget was wasted and that he could drastically cut that spending – if only he could figure out which half to cut.

Similarly, property-casualty insurance companies know that only about 10% of their customers file fraudulent claims – but those insurers still must closely scrutinize virtually all customer claims because they can’t quickly and easily figure out which are the fishy ones.

Call it distrust by default.

And it cuts two ways. On the one hand, insurers are typically forced into rigorous and often time-consuming manual processes to minimize fraud when they underwrite policies, conduct investigations and settle claims. And they have to impose these processes on most if not all customers, because they lack better ways to distinguish between low-risk and high-risk customers.

On the other hand, what customers often get as a result of these processes is slower service and an inferior customer experience. The painstaking verification of claims can give honest customers the idea that their insurers don’t trust them. That in turn can lead to reciprocal distrust of insurers by their customers.

UNIQA saves $21 million in 2 years

One of Europe’s largest insurers, UNIQA, wanted to meet rising consumer expectations by transforming its business into a 24/7 service provider. It adopted FRISS trust automation across 15 countries in which it operates, speeding service and enhancing the consumer experience for trustworthy consumers.


  • $21 million in fraud savings in 2 years

  • Fraud savings per investigator up from $550,000 to $2 million

  • 4-month implementations delivered fast ROI

Slower service, lower satisfaction

Slower customer service and customer distrust can easily lead to lower customer satisfaction. That’s among the last things that insurers want at a time when boosting customer satisfaction has never been more important to getting and keeping competitive advantage. 

For example, JD Power reports that slower cycle times, more complicated claims processes, and communications challenges have dragged down customer satisfaction with homeowner insurance property claims to a five-year low. Similarly, Accenture confirms that the faster a claim is settled, the higher the reported customer experience.

Another unhappy consequence of distrust by default: lengthy, labor-intensive processes increase administrative costs and eat into margins - disappointing staff, management and shareholders.

Few insurers or customers are free of this distrust by default. Even when insurers and their customers share an important bond that contributes to innate trust – such as a military affiliation – the inevitable involvement of third parties, contractors and others outside of the shared culture can work against the trust relationship. Distrust can also arise between departments within an insurer, as when adjusters and investigators differ on the legitimacy of a claim and the degree to which it should be scrutinized.

Ready to learn more?
For more information about how trust automation can help you build better customer experiences and better security

How much is at stake?

More trust is better than less trust. But how big a deal is it, really? According to Gartner, “customer trust” is replacing “customer experience” as the foremost strategic term for an insurer’s positioning and messaging of differentiated services.

Organizations that implement a formal policy around using digital tools to promote trust will generate 30% more profit than those that don’t, according to Gartner. And insurers that can install digital trust will be able to participate in 50% more ecosystems to expand revenue generation opportunities. 

Being smart about applying technology to the problem of distrust by default can have distinct benefits for all of an insurer’s key departments:

Underwriters can…

• Write policies faster, more consistently, and with less bias
• Gather risk insights for an entire portfolio
• Combine data for a comprehensive view of every risk

Claims adjusters can…

• Pay out trustworthy claims faster
• Consistently screen claims to improve referrals and catch fraud
• Gain a helicopter view that shows actionable insights from all data points

Investigators can…

• Reduce turnaround times for legitimate claims by verifying trust
• Integrate their work with external vendors in a central environment
• Easily compile and share case notes when trust should be challenged.

But how do you use technology effectively to achieve these benefits?It sounds like a job for AI. The rapidly developing use cases that insurers are only just learning to use, of course, need to be carefully evaluated and managed to ticket of regulatory and ethical concerns.

IAG New Zealand boosts case volume productivity by 300%

The New Zealand arm of Australia’s top general insurance provider, IAG, wanted to boost productivity and overcome the increasing financial strain of combatting fraud. By adopting FRISS trust automation, the company achieved:

  • 300% increase in case volumes without increasing staff

  • 47% productivity improvement in claims management

  • Better investigator throughput

Trust automation: The way to slay distrust by default

For an insurance industry fighting to overcome distrust by default, the way forward is trust automation. Automating trust is crucial because it delivers the fast, reliable, and consistent processes that insurers need to safely speed up customer service and boost customer satisfaction and trust without incurring greater risk. It highlights connections among data that an unaided employee could not, giving insurers the confidence that they are writing the best risks and paying only legitimate claims. 

Trust automation works by:

  • Automating data-gathering processes to empower your underwriters to evaluate all risks, including those they couldn’t previously consider for lack of data

  • Distilling data into easy-to-read fraud indicators that empower claims adjusters to flag claims that need deeper reviews

  • Centralizing the investigation and automating tasks, so that the right people have access to the right information in one place, and investigations are completed in a timely manner.

It’s also important to understand what trust automation isn’t. It isn’t a way to replace your people; rather, it’s a way to make them more productive, so they respond to customers more quickly and appropriately, delivering better customer service. 

Also, trust automation isn’t a fixed offering. It’s an approach to the need to safely speed up processes to deliver better, faster customer service while maintaining and increasing accuracy and reliability. As such, trust automation isn’t a one-size-fits-all solution that you must shoehorn into your current IT infrastructure. Rather, it’s a mindset with which to evolve your infrastructure to address the distinctive challenges you face in delivering your services. 

Trust automation in real life

That’s trust automation in theory, but how do you implement it in practice? 

The difference between trust automation and traditional approaches begins at the most basic level: While traditional approaches typically focus on a single snapshot in the relationship between insurer and customer, trust automation is a process that runs like a river throughout the relationship.

Trust automation centers on three components: 

  • Risk assessment at underwriting

  • Fraud detection at claims

  • Managing investigations

In a trust automation process, risk assessment begins at underwriting and integrates a range of data, building a summary of the proposed risk that is as accurate and complete as possible. 

When a claim is submitted, automatic fraud detection processes include consideration of all this information against data in the newly submitted claim. Once a claim is flagged as suspicious, it should move automatically to a comprehensive case management tool that investigators use to collect notes, photos, and other data.

Seguros El Aguila cuts policy, claim resolution times by 50%

This Great American Insurance Group-owned Mexican auto insurer, Seguros El Aguila, projected that its internal claim-verifications systems wouldn’t scale sufficiently to meet expected growth. It adopted FRISS trust automation. Results:

  • 75% reduction of false positives

  • 50% decrease in time spent per policy application and claim

  • Fast-track processing for acceptable risks speeds customer service

Trust Automation is AI-enhanced

FRISS understands these challenges like no other company. That’s why, since 2006, we’ve focused solely on solving these issues for Property & Casualty carriers. Here’s a look at how FRISS drives the risk/fraud detection process for both underwriting and claims. Because insurance is as dynamic as the markets and customers it serves, trust automation must be highly customizable. Criteria or patterns that merit red flags for a certain line of business in one area can be ignored in others, especially where past analysis has shown they aren’t relevant. Processes are also customizable to match the risk appetite and other preferences of any given insurer. 

The process accepts data from a range of sources including documents and images, internal data from Guidewire, Duck Creek, Sapiens and other core systems, and external data via API integrations. This information then undergoes a four-part, AI-based entity resolution process – which is a key difference from traditional approaches. 

The system applies scenarios from its global knowledgebase, looking for matches or patterns that raise red flags for further inspection or investigation.

Network analysis then helps to identify complex fraud schemes in which, for example, a customer’s relative may have submitted a similar claim, or a common body shop, roofer, or ambulance service might be associated with several suspect claims.

AI text mining applies natural language processing to claims and policy descriptions, notes fields, and other structured content. AI text mining logic identifies suspicious words or phrases that may indicate fraud within local geographic regions and languages. When extended with an OCR tool, AI text mining can analyze complex word patterns in property reports, police reports, sworn statements, medical reports, and other attached documents in seconds, saving hundreds of hours annually.

AI modeling further uncovers potential fraud patterns in submitted data, in part by comparing underwriting or claims data to historical events that have been confirmed as legitimate or fraudulent.

Trust automation implements these analyses in mere seconds and provides a score that can be categorized as either legitimate (for straight-through processing), possibly suspicious (for a closer look), or warranting full investigation. Like the AI analytical processes, the categories and their parameters are customizable, so an insurer can set the threshold for acceptance, rejection, and further investigation however appropriate for its business.

Underwriters, claims adjusters and investigators can access trust automation information, scores and reports through their existing custom or commercial portals.

With trust automation, insurers can pay legitimate claims faster, reduce claims leakage and provide better customer service. And because they devote fewer internal resources to such claims, they can redirect their resources more profitably to the claims that warrant investigation.