Accenture's 2022 report "Transforming Claims and Underwriting with AI" contains some fascinating insights. Covering 6,754 auto and home policy holders (PH) who made a claim across 25 countries it deserves reviewing and comparison with an insurer's own claims operation. 26 claims executives across 13 countries also took art in the survey.
The respondents claim (no pun meant) that speed of settlement is the key to PH satisfaction. The following visualisation from Accenture shows an underlying threat for insurers.
Consumers have raised their expectations of the organisation they deal with. Despite the pandemic, supply chain disruption, war and inflation they still have Amazon and other suppliers delivering goods fast and furious and keeping them informed of progress. Insurance claims might be more complex but the benchmark is there to be compared against.
There is an obvious caveat to this speed of settlement metric. An inaccurate, unfair settlement delivered fast must be worse than an accurate and fair settlement that takes longer. As long as the policy holder is kept informed regularly and can see the carrier and agent are working on her behalf.
This has become more critical recently where repairable vehicles are given a total loss decision as a result of long delays to parts availability, high cost of credit-hire for "vehicle off road" and rising parts and labour costs.
In the last two weeks I have seen three such cases e.g. a vase reported by Bart Patrick CRO at Genasys.
"In summary. The car was deemed to have about £5k worth of damage. the 3rd party has admitted 100% liability. Yay!
The damage is less than 20% of the value of the car. It was booked in to be fixed. 1 part missing. The new rear wing section - 3 months back order. Credit hire raises its ugly head. The insurer redoes the maths. A totally repairable car is now a total loss. Not because it is badly damaged, it is not. Because the cost of a hire car for the next 3 months makes it a total loss. When is a car too badly damaged to be repaired? Clearly when the cost of a hire car makes it so you silly person you.
The unbelievable bit is that they have already flagged the car as a total loss. It is effectively scrap. That's the first disgusting part of this. An insurer has now deemed a totally repairable car to be a total loss - it has been classified as a damaged car so even if repaired it is worth about 1/3rd of what it was before. I am stunned by the ineptitude of this. ESG anyone? You know, green issues? Who scraps really repairable cars? Oh you silly person, it's this insurance company! (I descend into sarcasm, yes it's the lowest form of wit, but all I can muster on a Friday evening).
So, the second unbelievable bit. So now they have deemed the car a TL we head into the murky world of insurer valuation. They have offered 30% below market value. You cannot get a car, like for like for what they offer. The reason? They base their valuations on Parkers and Glass's. Neither of which have updated their valuations in line with the huge uptick in market prices (I have been informed of this by an industry insider).
So this poor chap has had the rug pulled from under him. He is a innocent victim of an accident, an intransigent insurer who has changed their mind about how they are dealing with his loss, and an insurer that writes off utterly repairable cars because the cost of car hire is too much. All he wants (genuinely) is his car back in it's shiny and non-crumpled condition. Doesn't seem too much to ask.
I am really angry on his behalf about how my industry (I count myself as part of the insurance industry) has let him down so badly by making consistently bad decisions for the claimant, consumer and the environment. "
Three reported cases on three weeks may be outliers or indicators of a problem.
Whilst I talk about leveraging technology below ( to speed up decisions and settlement) it is obvious that in times of abnormal claims inflation and extended repair times that skilled Claims Adjusters, Independent Adjusters play a vital role. AI only does what the algorithms and data say and when wither or both a wrong then the customer suffers.
When the combination of homo sapiens augmented by technology come up with the optimal answer for insurer and customer ten speed of settlement must indeed be a deciding factor of customer satisfaction.
Accenture states that speed of settlement is particularly important for insurers, since claims dissatisfaction is a major factor in driving policyholders to switch to another company, with: -
74% of dissatisfied customers either saying they did change providers (26%) or are considering it (48%).
Whilst 70% of PHs said they were satisfied or highly satisfied with claims, 30% were not. And with supply chain disruption, labour shortage, claims inflation and pandemic after-effects that 30% is likely to have increased.
Accenture draws the these conclusions: -
- $170 billion in premium is at risk over the next 5 years as customers switch carriers due to not being fully satisfied by the claims process.
- Underwriters are spending 40% of their time on non-core activities, representing an efficiency loss of $85-$160 billion over the next 5 years.
How should insurers counter this risk and inefficiency?
Accenture believes that: -
- AI has emerged as the transformative technology and critical differentiator in the insurance industry when applied in tandem with humans.
- AI has matured and costs have come down significantly over the past 5 years, delivering ever increasing value for insurers
But the hurdle to leveraging AI is the gap between belief in its importance and actual deployment.
Why is there this gap?
Is it insurance executives wanting to show the world how their strategies encompass AI so as to stand on the shoulders of competitors? Or is it more a case of the practical difficulties in leveraging AI holding back deployment?
One hurdle is, and ever was, data. Data in silos inherited, over many M&A years, in mainframes, AS400s, a multitude of technology stacks and various point software solutions. Even if they have overcome these challenges in motor it is often the case that home and contents, commercial and speciality are a different kettle of fish.
Talk to brokers and data is a perennial nightmare again not made any easier by the many systems inherited over years of acquisition- particularly by the big four global brokers. Innovative syndicates do buck that trend but when it comes to technology ecosystems that problem resurfaces e.g. between Lloyds and the Syndicates.
Whilst there is no easy answer there are shining beacons of light.
There are proven, scalable and beneficial software companies that offer point solutions that leverage data and AI/NLP/RPA...... Take a small selection.
- Be Valued
- Claims Genius
- Symbility (CoreLogic)
- Value Checker
How do you integrate these with complex core systems and/or claims management solutions?
Some claims Platform as a Service (PaaS)companies try and build everything and seeing as that is complex, time consuming and expensive the outcomes will probably be too late, too obsolescent and too difficult to maintain. Ever suffered those three to five-year major upgrades when everything is frozen for twelve months?
Other claims platforms focus on the customer backwards ( PH- Insurer/Broker-MGA- Technology Ecosystem Partners).
They ensure digital claims management optimised for ENOL/FNOL, the gateway to faster settlement, and deliver configurable/customised claims journey for every line of business and every peril. AND, here's the key success factor: -
Collect the structured and unstructured data collected from eNOL/FNOL, and then in real-time pass to the optimal point solution for its AI driven app to make the right decision which the platform then passes on to the next stage where a decision is required.
If it is a simple matter of accidental damage to a TV any platform worth its salt can collect data on what happened, the damage, the specific article and flag if the photos uploaded have been doctored, the dates or location inconsistent with the registered event or the context just plain suspicious.
Let's say all is good and the claim decision is bona fide.
Fewer claims platforms can automatically pass this data in real-time to the next decision stage e.g. home contents automated software like SLVRCLD to identify the modern day equivalent replacement and offer the PH an Amazon voucher, virtual credit card for the amount, Cash settlement - all with deductibles having been accounted for.
Then integrate with the insure's core system/payments and hope its not a cheque to be issued. If so, better to securely send the instruction in real-time to Stripe, Imburse, Mastercard etc to electronically pay the PH immediately and securely.
In this way straight-though processing (STP) is powered by the platform and the optimal point solutions for each insurer-market-region. For more complex claims and those involving third-party liability, injury and/or need for human support the platform takes care of the mundane automatically and enables collaboration and orchestration with human claims adjusters and specialists.
Not out of the box and not easy. You have to put the planning in, get buy-in from all participants and approach it a step at a time.
“Let us assume we have a clear design for our desired future state. It won’t take you long to realize there is little chance that a single intervention can get you from here to there. So, the next major deliverable must be a roadmap organized around a maturity model, or what we like to call, a stairway to heaven. Each step up the stairway should be designed to deliver value upon completion, thereby allowing the organization to pace its change management, funding things as it goes, building its confidence, and reassuring its various stakeholders.
With such a roadmap in place, now you have a current-state/future-state accountability mechanism that can govern each stage of the transformation—the software and systems, the systems integrators, the process owners insider your enterprise, and the people responsible for executing the processes. As we have noted elsewhere, digital transformation is not a restaurant. You cannot simply pay for it and have it delivered to your table. It is a gymnasium. You still have to pay for it, but to get any value out, you have to actually do the transformational work yourself.
Geoffrey Moore famous for his book and consulting "Crossing the Chasm".
Yes; it is always possible to deliver FNOL claim solutions in weeks, and full claims journeys in months, but to get buy-in across all people in the customer takes as long as it takes. Even more time when brokers.agents are involved. Follow the money and get the balance right between cashflow, capabilities and ability of customer to deploy.
Of course there are other technology partners involved in the complete technology ecosystem beyond those AI powered apps. Here is a brief selection to help you on the journey.
Traditional core insurance platforms Guidewire, Duck Creek, Majesco, Pega, Innovation Group and so on. Good on breadth of functionality but often lacking in specifics e.g., claim management. And traditionally involving Capex and high annual licensing costs though that is changing.
SaaS and Micro-service architecture core platforms ICE, EIS, Genasys, Duck Creek
Quote & Buy, MTA & Renewal Platforms like Go-Insur, HUGHUB, iptiQ that enable an insurer to allow a customer to interactively manage all their policies from one dashboard
Digital Claims Platforms RightIndem, Snapsheet, ClaimsGenius, Claims Technology, Salesforce Industries, Five Sigma, 360Globalnet etc
Ecosystems Providers incl. telematics data exchanges: Verisk, CoreLogic, LexisNexis Risk Solutions, Mitchell International, CCC Intelligent Solutions and Arity
Point Solutions Tractable, Audatex/Solera, Shift, Friss Sprout.ai, Solera and many others
Telematics Service Providers: Movingdots, Octo, IMS, True Motion, Cambridge Mobile, Vitality Drive and The Floow
Shared Mobility Systems: Uber, Lyft, Enterprise CarShare, Zipcar, Car2go, GIG, Turo, Getaround
Combined claims services and technology providers Crawford & Company, Sedgwick, Davies Group, Claims Consortium Group. Control€xpert etc.
No-Code/Low-Code app building platforms from Unqork, Netcall…
Embedded insurance Wrisk, Qover, Wakam etc
Want some help? - drop me a line to Mike.Daly@rightindem.com
Why Cycle Time Should NOT Be the Driving Metric of Auto Damage Claims a view from the front line
Executives already know the importance of using AI in claims. The graph below shows that, for each area of the claims value chain, at least 75% of executives said AI and machine learning can bring “considerable” or “great” value. Yet, there’s a disconnect between this intention and taking action. The same graph shows this gap, where even the most advanced area (claims adjusting) still has only 44% of executives saying they are advanced in their use of AI, automation and machine learning. In this scenario, our definition of “advanced” is after the level “using in initial stages.”