Rising fraud forces insurance firms to sharpen their own services
Original article from The FinTech Times
Article by James Loft, Chief Operations Officer, Rainbird.
How to make sense of this recent spike? We’ve heard in the news that police are failing fraud victims. The crime demographics, meanwhile, have led some to direct their anger towards thirty-somethings and millennials as the main fraud perpetrators. But amid all the finger-pointing, what’s been less talked about is how businesses are arguably failing us even more.
Premiums are soaring; services are not
According to the Association of British Insurers (ABI) and the Office for National Statistics (ONS), the cost inflation of car insurance is now eating up 10% of a young driver’s average salary. As Cifas CEO Mike Haley has said, the idea that insurance scams are ‘victimless crimes’ has always been a bogus one – they unite us all as victims of slower claims applications and rising premium costs.
Ultimately, there is more that insurance firms could be doing to keep these prices down. First Notification of Loss (FNOL) is where the problems begin: contact centres typically field these calls, where handler error is common in an environment in which employee turnover is high, roles are often low paid, and employee engagement can be poor. At square one in the claims cycle, a flawed fraud judgement has numerous knock-on effects: claim delays, increased costs, reputation damage for the insurer and dissatisfaction for the customer.
With resources stretched and employee turnover high, not every claims handler can be an expert in their given field – be that collision damage or work-related injury. But what they can be is properly armed with all the relevant, real-time information they need to cope with a constant stream of potentially fraudulent claims.
Fraud is shape-shifting; fraud departments should follow suit
Businesses would be wise to adopt a dynamic approach to what is an open-ended problem. Whether due to specific regional or market trends or persistent areas of vulnerability, it’s important to remember that every insurance company’s fraud profile is unique; there isn’t a one-size-fits-all solution. A tailored approach to fraud prevention is key: this means investing in decision-making platforms that are configurable, scalable, and based on the logic of firms’ best gatekeepers of fraudulent claims.
It’s this interpretable, easy-to-use approach that can allow firms to modify their own automated decision-making systems as their business grows and challenges change. With fraudsters becoming increasingly creative, fraud departments need to remain adaptable to react to constantly shifting goalposts.
For example, PI reforms are likely to diminish the type of fraud that we often see in the motor PI market today. What the fraudsters will do next, however, is harder to foresee – so firms that are able to pivot the rules or logic powering their technology will be much better placed to tackle new forms of attack.
Data alone won’t do
With a target as morphing and malleable as insurance fraud, historic data can’t be relied on to spot whatever’s coming. After all, few economists or criminologists would have predicted last year’s surge in fraud statistics based on the previous year’s data.
Couple this with the fact that the insurance industry is one blighted by poor quality data. You wouldn’t build your house on sand, so why build your fraud prevention tactics on bad data?
Data has traditionally been the lifeblood of the insurance industry, and sure enough, most insurers’ idea of deploying AI means training it on masses of statistics. But any reliance on monumental amounts of digits introduces a new risk that Accenture calls “data veracity”.
“IT’S IMPORTANT TO REMEMBER THAT EVERY INSURANCE COMPANY’S FRAUD PROFILE IS UNIQUE; THERE ISN’T A ONE-SIZE-FITS-ALL SOLUTION”.
80% of the insurance executives surveyed for Accenture’s Tech Vision 2018 reported that their organizations increasingly use data to drive automated decision-making at scale – yet a recent study estimated that 97% of business decisions are made using data that the company’s own managers consider to be of unacceptable quality.
Keep humans at the centre of decision-making
Beside creating operational risk, an over-reliance on data also risks devaluing the power of human expertise. Human-centric AI, based on the logic of people rather than the amalgamation of numbers, makes the most of expertise and overcomes the challenges associated with building models based on insurance data. McKinsey & Co believe that by 2030, AI will inform every major decision an insurance company makes – but stressed the continued integral role of underwriting and claims experience. “There’s no substitute for good old-fashioned claims and underwriting experience,” senior partner Ari Libarikian said, “and that will very much still be part of the organisation.”
The nous and expertise of seasoned decision-makers in detecting and examining insurance fraud will arguably be at a premium in years to come – particularly with waves of baby-boomers exiting the industry and less traditional workforce demographics replacing them. Workforces are becoming more transient, more fluid; the odds of employees moving on for a different experience rather than gathering years of experience at your firm are rising all the time. Firms should be acting now to not only nurture and preserve their most valuable people but also scale and maximise that expertise that they possess. You hear a lot about knowledge leakage – but insurance firms will soon become very leaky indeed without sufficient planning.
Rebuild consumer trust with quality and convenience
Trust has been an issue in recent years for the insurance industry. Shady brokers or dodgy practises, such as slyly jacked-up premiums, have damaged the relationship between insurers and consumers and dented reputation at a PR level.
Some would argue that this severed relationship has laid the groundwork for the recent upturn in fraudulent foul play. The best way to rebuild trust? Transparency. If claims handlers can keep their customers more thoroughly informed about claims decisions, with more detailed accounts of the rationale that was applied, customers can rest easier – even if the decision is an unwelcome one. To achieve this while maintaining an efficient claims process, human-centric and transparent automation is really the only option firms can take.
Equally, if not more important, is the role of quality human interaction. EY describe claims interactions as “moments of truth” in customer relationships – the strength of these critical interactions dictates the loyalty of customers in the long run. A claims department armed with AI-powered decision-makers – who have time and relevant information to offer their customers – can create these long-lasting relationships.
Of course, to really satisfy customers, all of this needs to be built on a foundation of efficiency. It’s not just fraud or pricing inflation that’s come into focus in recent months. The insurance industry is coming to terms with the fact that it needs to follow the same march of progress as all other customer-facing sectors: a race towards convenience.
Speed is a large part of this equation. According to Genpact, an AI-enabled claims department means claims adjusters can spend 95% of their time optimising indemnity and customer service, while Deloitte finds that prospects are 20% more likely to purchase a life policy as the underwriting and application process gets closer to real-time – which can only be facilitated by accurate, frictionless fraud decisioning.
Meet IFSR 17 with full transparency
As well as building trust, transparent technology is also a way to internally cope with upcoming legislative challenges. Insurers utilising new technology could face a struggle to remain fully compliant, particularly with the International Financial Reporting Standard 17 (IFRS 17) on the horizon. If their technology is designed with the audit process in mind, providing full rationale for automated decisions regarding insurance contracts, then the IFRS 17 demands of reporting transparency can be met with much less efficiency or profit loss. The legislation will require firms to grasp the front-end and back-end business rules that are applied to process contracts, and the acute risks involved. Automation technology with in-built, detailed audit trails will, therefore, be a crucial asset.
Insurtech coming of age?
Thankfully, the fraud arms of insurance companies look to be maturing: tech budgets are generally on the rise, with 41% expanding their tech budgets for 2019, and two-thirds expecting to acquire claims fraud detection technologies. Only 2% of tech budgets contracted for this year.
If they get their fraud decisioning right and are able to explain their rationale while improving their accuracy and efficiency, firms will see the positive overspill in the customer journey – and hopefully a subsiding of the current fraud spike. It all depends on whether this traditionally (and by definition) risk-averse sector is able to marry its efficiency gains with the transparency, consistency and adaptability of scaled human expertise.