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TOPICS

TOO GOOD TO BE TRUE?

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AUTOMATED ACCEPTANCE: DO IT!

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AUTOMATED REJECTION: DON’T DO IT!

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WHITEBOX: EXPLAINABLE RESULTS

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DECISION-MAKING OR DECISION SUPPORT?

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KEY QUESTIONS FOR ASSESSMENT

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WORKFLOW MANAGEMENT

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ROI WITHIN ONE YEAR

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IMPROVED CUSTOMER EXPERIENCE

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USE YOUR UNDERWRITERS MORE EFFECTIVELY

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COMMERCIAL UNDERWRITING – STANDARDIZED

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PERSONALIZED ACCEPTANCE

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PLUG AND PLAY

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CONCLUSION

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Automated risk assessment assists insurers in many ways‌ yet there are limitations that you need to consider.


TOO GOOD TO BE TRUE? A customer visits your website and enters their information. The computer makes a quick decision – acceptance or rejection. Your employees didn’t have to do a thing. Too good to be true? Indeed, it is. Fully automated decision-making isn’t a good idea, especially when acceptance or rejection is left to a computer. It can damage your reputation, and it’s also not wise from a legal or moral point of view.

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AUTOMATED ACCEPTANCE: DO IT! The benefits of automated acceptance far outweigh the risks. If a computer makes the wrong decision in accepting a new customer, the company bears the risk. There is no potential for reputation damage or legal action for discriminatory rejection. Better yet, speedy acceptance leads to increased customer satisfaction, lower costs and higher returns.

AUTOMATED REJECTION: DON’T DO IT! Systems that can automatically reject a customer leave the company open to considerable risk. Consider an example: A Scandinavian company was taken to court, accused of discrimination. An applicant had his application rejected and no reasoning was provided. It was only after the case went to court that it became clear why: his application was rejected by the computerized system because he lived in a rural area and originally spoke a different language. All other criteria, such as creditworthiness and payment history, were perfectly fine, and anyone else would have been approved for the loan. The company was hit with a hefty fine for discrimination. While it was obviously not the intention of the company to reject a good customer, in the end they did because their system failed to have a human verify the results.

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WHITE BOX – EXPLAINABLE RESULTS In this example the company was able to determine how the mistake was made, but not all automated decision-making tools work this way. Some assessments take place in what we call a “Black Box.” These decisions can’t be traced – not something you want to be up against in court. A “White Box” approach is preferred, where decision-making is fast and you can pinpoint exactly how a decision was made.

DECISION-MAKING OR DECISION SUPPORT? Artificial Intelligence is becoming more advanced and may eventually allow automated rejection to be feasible, but until that time, fully automated decision-making is unwise. Instead, consider it automated decision support. AI-powered support allows decisions to be made more effectively, efficiently and accurately. As AI advances, automated advice will become more reliable and the human factor will become less relevant.

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KEY QUESTIONS FOR ASSESSMENT

WORKFLOW MANAGEMENT

Automated systems can pick out who should be accepted and which applications need further review. They can do this almost instantly by answering three main questions:

While automated support is great for immediate acceptance, it’s also a powerful workflow tool.

1 Who is this applicant? 2 Can I accept this applicant? 3 Do I want to accept this applicant? If all lights are green, as they are in 75% to 80% of the applications, the application can be accepted immediately. If the system finds any red flags or can’t fully answer those questions, it will indicate what type of further assessment is needed. From here staff members can investigate to the extent needed and determine whether an application will be accepted.

When further investigation is needed, the system can trigger a manual review. It can also support that investigation by providing all necessary information in a central location, increasing the reviewer’s efficiency. The system can trigger different workflows based on initial findings – such as sending riskier cases to more senior staff. Automated systems can also quickly connect the dots and identify customers who may be part of an organized crime ring or terrorist group.

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RETURN ON INVESTMENT (ROI) WITHIN ONE YEAR Automated support for decision-making is very valuable. Usually the investment is recouped within the first year, often faster. Companies may be shocked when they see the value they were missing before automating risk assessment. Consider this example: During a study a major insurance carrier used an automated system to reassess customers they had already accepted. They found nearly 35% of risks they accepted would have been flagged had the automated system been active. Of that group, 90% yielded a negative return within only 2 years. With automated risk detection, these policies would have been rejected.

IMPROVED CUSTOMER EXPERIENCE Customers now expect to shop for and buy just about everything online, and insurance is no exception. A major advantage of automated decision support is straight through processing. Risks that are given a “green light” are easily accepted without an underwriter’s intervention. As it turns out, these account for the vast majority of applications – meaning lots of happy customers. 8


USE YOUR UNDERWRITERS MORE EFFECTIVELY When most legitimate customers receive instant acceptance, underwriters can spend their time dealing with actual risk assessment. Most applications flagged for review truly need extra attention. Often an underwriter can accept the policy with extra conditions, exclusion or adjustments to the premium… or, if necessary, reject it altogether. And they’ll enjoy their job even more, because it’s suddenly become more interesting!

COMMERCIAL UNDERWRITING – STANDARDIZED Commercial underwriters spend a good amount of time compiling offers. When an automated system approves an application, the underwriter can then focus on computing an appropriate premium and drafting any conditions or exclusions. The system can then store these offers (and how they were computed), and in short time, provide an objective framework for all underwriters to provide consistent offers. 9


PERSONALIZED ACCEPTANCE When assessing the applications of persons, little or no individual assessment takes place. This mainly concerns the risk offered, the claims history, any registrations and the like. If the system does not identify any objections to acceptance and no further assessment by an underwriter is required, then a standardized offer is made.

If the system does not identify any objections to acceptance and no further assessment by an underwriter is required, then a standardized offer is made.

The number of product variants can be a complicating factor for the configuration of the system. A decision is sometimes made to make a personal offer, for example by means of exclusions. This results in extra administration and the risk that something could go wrong in the event of a claim. Although the configuration of the automated risk assessment system often takes a little longer due to the large number of product variants, the return is often high. Not only with regard to the portfolio result, but also with regard to the costs of the acceptance process, customer satisfaction and employee satisfaction.

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PLUG AND PLAY Software as a Service (SaaS) providers may offer a plug and play solution, meaning it’s nearly ready to do its job right out of the box. Commercial risks can often be assessed in a standardized way, meaning a good risk assessment of a company can generally be made very quickly based on uniform business rules. Based on the number of products and variants offered, configuration for personal lines assessment may take just a bit longer. Data availability is a key concern – do you have enough to get a complete picture of the applicant? Software services start with a comprehensive integration of data sources and support interfacing with external sources deemed necessary by the carrier.

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CONCLUSION By now you’ve learned that automated risk assessment is not an independent process. With a few organizational adjustments, it can lead to a reduction of “busy work” and allow your staff to focus their attention where it’s really needed. There’s much value in the time saved across nearly all acceptance processes, and certainly lots of money saved by avoiding risky customers. Automated decision-making support was just a trending topic a few years ago, but insurance carriers have begun to realize its true value in dollars. You know who you’re dealing with much faster and quickly decide whether you can and want to do business with them. Internal processes are streamlined, and both employee and customer satisfaction are greatly improved. Artificial Intelligence further enhances automation, ensuring its continual development and sustainability.

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ABOUT FRISS FRISS is 100% focused on automated fraud and risk detection for P&C insurance companies worldwide. Their AI-powered detection solutions for underwriting, claims and SIU have helped 150+ insurers grow their business. FRISS detects fraud, mitigates risks and supports digital transformation. Insurers go live within months with fixed-price projects and realize an ROI within the first year. FRISS solutions help lower the loss ratio, enable profitable portfolio growth, and improve customer experience.


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Profile for Maarten Uri

The Computer says Yes, Automated underwriting: Too good to be true?  

E-book over geautomatiseerde risicoanalyse en fraudedetectie, geschreven door Maarten Uri www.uricom.nl in opdracht van FRISS Fraud, Risk &...

The Computer says Yes, Automated underwriting: Too good to be true?  

E-book over geautomatiseerde risicoanalyse en fraudedetectie, geschreven door Maarten Uri www.uricom.nl in opdracht van FRISS Fraud, Risk &...

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