Process Automation Use Cases in Insurance

Hello and welcome to another episode of the Process and Automation Podcast with the Automation Guys. We have received a couple of questions from our community recently, and very specifically from professionals in the insurance industry, and they also ask us if we can cover a few use cases on the insurance industry. And yeah, of course, when we look at the insurance industry, automation can bring numerous benefits by streamlining processes and of course reducing that manual work, what is there in the insurances, improving that accuracy, and also enhancing customer experiences. So when you, when you then dive a bit deeper into that, so there are several areas within that industry specifically where it can be applied effectively. And yeah, some, some I like to just go high level on, and then later on we will talk a bit more specifically on, on those specific use cases. So that could be, for example, claims processing. It's obviously a very important process for insurance companies. The policy underwriting, customer onboarding, everything what is related to documents, the whole document management. Of course, we do not forget compliance. Every insurance company has to deal with lots of compliance and has to deal with fraud detection and on the external side deal with lots of customer services and requests. With questions related to claims and all sorts of stuff. So, so yeah, the insurance industry is, is, is huge. And yeah, pretty much in every department you find plenty of use cases. So let's, let's go into them more, more individually. Arne, do you like to kick off with the first chunk?

Yeah, sure. Thanks, Sascha. So obviously When we look at use cases for automation within site insurance, specific— specifically, you know, claims processing is a big one. Of course, processing of claims is a critical aspect of the insurance industry as a whole. And, you know, generally that involves handling and evaluating and settling off insurance claims. So what Automation can obviously significantly enhance efficiency and also the accuracy of the process. And that of course leads to faster claim settlements and improved customer satisfaction. So the claims process can obviously be orchestrated and automated using, you know, workflow orchestration, robotic process automation, and the kind of the elements that is subject to this is things like data extraction. So you could take relevant data from claim forms that's, that's, that's been captured and use things like OCR to extract it. And obviously that eliminates the need for manual input. You could validate data, so you could validate this extracted data on predefined rules. So an example of this, you could check if a claimant's policy is active. You could verify the COVID limits and again sort of validate the claim against your policy. You could use things like intelligent routing. So again, based on predefined rules, you could route the claim to the appropriate departments or loss adjusters, you know, or the individual teams to handle the claim. And again, that, you know, reduces processing delays and also improves efficiency of the process. And then of course, other things you've mentioned, fraud detection, but you could apply some rules, some machine learning algorithms on historic data and extract some sort of patterns that highlight fraudulent behavior. And again, this can save the industry as a whole if you work for insurance company. You know, this could save quite a lot of money. And, you know, the financial losses due to fraudulent activities can be quite high. So again, you know, that just kind of streamlines that and reduces the cost associated with fraudulent claims. Of course, things like integration with systems. So for instance, you can integrate with your existing insurance system automatically, or if there's no API, you can use a robot. Things like automated notifications, you know, if there's any updates to your claim, maybe your claim status has changed, you know, you could reach out to the customer and tell them where it is in the process. It means that they don't phone up and take valuable resources, you know, from your teams to ask, you know, the status of a claim, for example. And then, you know, overlaid across all of this is sort of real-time analytics where you can look at claims processing metrics, average processing times, claim settlement ratios, things like this. So again, very, very good from a claims processing automation perspective, you know, a lot to go after. And of course, technology, automation technology, you know, these points that I've touched on just now, it's, you know, I would say kind of the major broad stroke items that, you know, for this particular use case that you'll go after.

Yeah, so that's plenty of stuff, isn't it, already just in that area. And I know lots of insurance companies, they're looking into some areas specifically. Yeah, it's one of the key processes, but every one of those is huge on its own or can be huge on its own. So similar, similar, this was the underwriting automation, the policy underwriting automation. So it's as well similar like claims, one of the crucial processes. And of course, when the policy, when it's planned to kick off, it needs to, or companies need to involve or need to evaluate the risk, that's the right word really. Yeah. And to come up with the premiums customers have to pay and then decide ultimately also if they want to accept a client, want to provide that policy. That can be obviously in a small-scale car insurance or can be in a huge insurance for an oil rig or so. So lots of evaluating risks here. So when we look specifically at the risk assessment, automations can Obviously looking at specific risk factors and analyzing the data, something what we as a human obviously can do and did in the past. But that's, if it's from lots of different sources, it's very time-consuming and we might miss information. And automating that, going into all the different databases and historical claims data that will make it so much easier and so much faster to come up with a recommendation for the underwriters. So based on that information, that automation, underwriters make then ultimately the right decision.

Yeah.

And then that leads nicely to that quote generation automation. So based on that predefined rules and the risk assessment results, where we can create that quote, calculate the premiums, and yeah, by automating this, insurance, insurances can be so much quicker. Yeah, so that's a very, very typical thing when it comes to like document generation. Yeah, rules-based underwriting is another area automation can apply these predefined rules and guidelines and assist that underwriting process. And that, that really makes sure that all the decisions are consistent and, and really gets rid of the, the human errors and biases in that process. The next big one is data verification, again a very time-consuming task if not done with some process automation. Sure, the accuracy of that information can be cross-referenced, or so we find more accuracy by cross-referencing data into so many databases we have. Yeah, and if you look at insurance companies, there's so many systems, sometimes up to 100 different databases. We have to go into. So it's sometimes ridiculous if you look from the outside into it. So yeah, but it makes sense that we apply automation here. And yeah, the next big area there, like in many other areas, is the workflow automation. The whole end-to-end process needs to be orchestrated with lots of human interactions, lots of tasks involved in that. What's the process status, those kind of things we need to look at as well. So for that, workflow automation is the right thing. Yeah. And then as with many businesses, integration with other data sources. Yeah, super important. With the automation, we can integrate into so many different systems. Just think again about the 100 databases. And I know sometimes customer service, some other people in other departments, they have to do some bits manually, and that's still the case these days. And if you can automate that and you can update these 100 databases, data sources in one go, data is more accurate, less risk. Yeah, and you just get rid of all these robotic tasks for your employees. And yeah, the next big thing in underwriting is, we mentioned that earlier a little bit, is the underwriting decision support. So yeah, by analyzing that historical data, the automations can identify patterns and come up with more recommendations and specifically also alerts for the underwriters, come up with even better decisions going forward.

Yeah, yeah. And I guess the next one is customer onboarding and sort of automation of that. And of course, this is a very critical process in the industry. And this is where we go and collect customer information. We verify their identity. And we also initiate the coverage, essentially creating the policy. So again, if you introduce automation here, you can improve this efficiency and accuracy of the whole sort of customer onboarding process and make that more seamless. And obviously from a customer perspective, that's going to increase customer satisfaction, customer experience is going to be better. So again, you know, just areas that you will go after is automated data collection. So obviously eliminating paperwork. You also have, you know, kind of ensure that you've got completeness of customer data. So it just means that, you know, all the information you capture is really accurate. Then things like identity verification, you know, you can integrate with verification systems out there, sort of credit checking systems. So it just really streamlines that process and take the human out of the loop. Get something that you can either do by APIs or automate this using RPA. And, you know, the same is true for sort of background checks as well. That, you know, if there's any flags against a particular customer, for example, you know, that could be flagged as well during the process. You know, so, and you could, you know, again, sort of use a digital worker like a robot to actually go and interrogate third-party websites. In terms of the customer onboarding, so once they you know, apply for insurance cover, you can automatically generate the policy, you send them over all of the policy documents, for example. So you can use some document generation there, and that can all be based on predefined templates. So again, this just eliminates any sort of manual document creation that could potentially lead to some chances of any errors or discrepancies. And again, sort of from a compliance perspective, you know, you could fulfill all of your compliance needs as well. So if you have compliance systems or databases, you know, your automation can actually perform these checks and ensures that customers, you know, from a compliance perspective, meet all of the requirements. And of course, that that will help insurers to avoid any penalties if, you know, if they don't adhere to sort of industry regulations. And again, you know, I spoke about this earlier, but sort of automated notifications and updates, you know, once, once you sort of onboarded a customer, you know, make sure they're informed by sending them sort of an automated response. It's consistent. It just means they've got all their documentation so they don't phone in to the call center. So it just sort of reduces, reduces the costs on, on that front. And then, you know, from onboarding perspective, of course, you know, you want this to be integrated with, with your backend systems, um, you know. So there's a lot of savings, um, to be made there as well, either by sort of APIs, or again, if you have legacy insurance systems, you need to use RPA bot. So again, sort of just the high-level ones from a from a customer onboarding perspective. But again, lots to go after there, Sascha.

It's now over to the document management within the insurance sector. Of course, managing paperwork manually can be very time-consuming and of course leads to errors quite often. So yeah, automation can really support that whole document management process, making them, yeah, of course, like with all the other areas we talked about, more efficient and more convenient. So let's look into the first one, document digitization. So automation can really convert those physical documents which are still present, like forms and contracts and policy documents, maybe send in like a letter or so, into like digital formats. And by having that automated, you can make them easily searchable and accessible. And yeah, that saves, yeah, of course, lots of space. So when you think of not storing these physical documents somewhere in a basement, so just getting everything on a digital level, very important. So the next part is document classification and indexing, so the automation can then look through these digital documents and categorize and tag documents. So based on that content, make sense out of it and making it easier to retrieve that information when needed later on in some specific processes. So your document management really covers the areas we talked about in earlier already. So the claims, the onboarding, the policies. So it all comes down to lots of documents being generated. So plenty of workflow automation in that area as well as a possibility. So with automation you can streamline these very specific document-centric workflows by automating that routing and the approval processes. So that, yeah, will lead as well for very timely processing and reduces that manual intervention. So it's not like you have to ask for certain documents because you know exactly where they are and they exactly go where they need to go. Yeah, version control and collaboration is another area. Automation makes sure you have that version control really in place, sort of getting rid of all the confusion which might be around that area caused by, by sort of different document versions. Historically, that, that has happened a lot. And yeah, it also enables that real-time collaboration. Among other team members. So yeah, that's a plus for productivity. And of course, when it comes to security and compliance, automation can really help to enforce security measures to protect these documents and make sure we comply to all the data privacy regulations and those kind of things. And of course, a really, really big one is the document generation part. So with that automation, you can really create that policy documents, personalized documents, certificates, all sorts of information you need as part of your process. And you can collect from so many data sources and build the right documents you need. And yeah, so there's actually no need to go into Word, copy and paste from one template into the other. So yeah, document generation and then further down the line as well, signing, those kind of things. Yeah, very, very cool stuff.

Yeah, and you mentioned compliance, and I think there's a lot of obviously regulatory compliance within the insurance industry, um, you know, and so compliance requirements, and to fulfill that is probably looked after, you know, quite a few teams or quite big teams in large insurance companies. So automation can actually help insurance companies ensure, you know, that all their compliancy with all the regulatory standards are met by sort of automating these sort of various tasks and processes involved. And it's things like monitoring for regulatory changes. So you could, you know, integrate with regulatory databases or, you know, use automated web scraping techniques. To highlight any of those changes and what that might be in terms of the impact to your operations. Things like policy and procedure updates. So this, you know, you're looking at automation that facilitates the updating of your policies and procedures to align with new regulations. So for instance, if there's a change in, in, in the regulation, or, you know, automated systems can actually trigger notifications or workflow to update your relevant policies and to ensure that obviously you're still compliant across your organization. Things like compliance checks and audits. So for instance, you could use automation to to automate compliancy checks and audits because you can run predefined checks against policies or procedures and even your customer data. So they just help to identify any gaps or anomalies from a compliance perspective. And also, if that's highlighted, you can take some corrective actions to, you know, very quickly in order to you know, fix those issues. And then from a sort of regulatory perspective, if you look at sort of reporting and documentation, you know, you can generate your compliance reports automatically by sort of extracting the data and putting that into kind of standardized reports. I can imagine if you have to present that and you have to generate these reports manually, that's quite a quite a big job. So again, if you have this automated processes and it's done at predefined intervals, then it just means that that process is a lot more optimized. And, you know, from a cost perspective and the time saving, that can be pretty big actually.

Yeah, very good stuff. Yeah, thank you on that point. So now let's go into the The fraud detection area. All right, yeah, of course we all know fraud can be a significant challenge for insurance companies, very often leading to plenty of financial losses and ultimately the loss of trust for those insurance companies. So when we look at the automation areas and combine data analytics, machine learning algorithms, and that will definitely help to to detect and ultimately prevent fraud in the insurance companies. And so there are 4 specific areas we usually look at. So this is the pattern analysis as the first one. So automation systems can analyze vast amounts of historical claim data and really identify these patterns and can also find these anomalies that may indicate fraudulent activities. So they are— when, when you think about insurance company, what's going on, a big one, there are thousands, hundred thousands of signals and events and, uh, probably millions a day. So it's really impossible to do that sort of manually. So by, by really looking on, on, uh, on, on that data or into that data, um, with automation, um, we can learn from, from these, uh, historic fraud cases And yeah, the systems can detect similar patterns in new claims and help to flag potential fraudulent activities. So the next, the next part is the data validation. So automation can immediately validate claim data by cross-referencing the data with external databases, maybe even further in into sort of social media profiles or other public records to really come up with was the right information and really finds the inconsistencies and discrepancies in the data maybe which was provided. So, and that can then be dealt with. So the next big area is like risk scoring. So automation can assign a risk very specifically to a claim on these predefined rules and data analysis and And claims with a higher risk score, for example, can be passed on to, to someone else to, to do further investigation. Yeah, and just come, come up with, there was a right level of attention here, maybe from, from humans and maybe further system analysis. So real-time alerts is another big area. So automation systems can generate these real-time alerts when, for example, the pattern analysis then finds something weird, suspicious, and that alert can be sent to some investigator straight away, to the relevant departments, and you could immediately stop those things impacting the company. So yeah, fraud detection, super important. Not necessarily the— it doesn't feel like the sort of the best topic, but, um, uh, but, but yeah, it's very important.

Yeah, big impact, I think, on, on profitability as well. You know, obviously fraud and insurance is, is, is a big topic. Um, um, you know, so, so is the last point I want to talk about is the customer services element and also customer support. I think this is quite a big differentiator. So if you've got automation in the back office, and you've got some good automation for underwriting, you know, about fraud protection. What you want to do is sort of enhance your overall customer experience and the type of support that you provide to them. And it needs to be seamless, and it needs to be a really kind of personalized experience as well. Obviously doing that without automation is extremely hard. So the things that you can do in this area, sort of automated responses, I'm using a chatbot, you can use natural language processing engines, you know, that understand customer queries and, you know, you could resolve those queries straight away without the customer calling a call center, for example. Things like policy inquiries, if a customer has inquiries about their coverage, maybe there's some changes they want to make, you know, some that affects the the premium, you know, you could kind of automate this by, you know, ensuring that the customer's got some up-to-date information. Things like routing and escalations. So for instance, if there's a customer inquiry and needs to be routed to the correct department, that's something you could do or optimize using automation as well. So then that obviously improves the overall efficiency. Of your customer support process, and it also reduces response times that leads to sort of customer retention. Also providing self-service portals, so this is a portal where customers can log in and they can sort of view their insurance documents, make payments, request changes, or initiate a claim. So you can plug that into your automated claims process. Then things like, you know, this is sort of still, I guess, part of the kind of the self-service element of it is providing some claim status updates. So if a claim has been initiated and it's moved forward, and perhaps a loss adjuster needs to be scheduled to come and do a site visit, all of this, just if you keep the customer informed on the status of a claim or what's kind of the next step, You know, it just sort of enhances transparency and really improves the customer service element of the process. And I suppose the last one here is just personalized offers and recommendations. And I think, you know, automation can analyze customer data and their preferences and help you to generate personalized offers, discounts, for example, policy recommendations. So if you You know, if you have a pet, and maybe he could recommend you have an insurance policy that covers for pets, for example. So, you know, it is really sort of just kind of know your customer and their needs, their preferences, and then using the automation system to, you know, to tailor, you know, things like cross-selling and upselling opportunities specific to to your customer, and that obviously enhances their experience and their loyalty, and, you know, and it increases customer retention.

Yeah, it's important.

Yeah.

So I think that when you go through with a claim, if it's health insurance or car insurance, you stick with the insurance company which pays you the fastest, isn't it? Ultimately, yeah. And if that can be automated, when you, when you send a picture into the chatbot and say, okay, yeah, here, money is already on your way, that's, that's the kind of automation and service we like.

Exactly. And I think automation provides that sort of ability to onboard a customer very quickly. If there's a claim, you know, try and pay the claim as quick as possible without compromising on, on fraud detection, for example. So sort of just overall experience from a customer perspective is just that much better. I mean, like I said, the topic is vast. I mean, we've gone through a lot of information today, but it is just such a popular— for automation, a very popular industry because there is a lot of processes within site insurance. And, you know, hopefully, hopefully the ones we've we've touched on, give our listeners a bit of an insight on where automation can be applied and the art of the possible when you start automating your processes within, inside insurance companies.

Yeah, it's super beneficial for these companies by applying or really embracing automation. So yeah, join us next time. So we go more into other topics around process automation. We cover pretty much every area of intelligent automation, hyperautomation, low-code workflow, RPA, AI. So, so many different topics. So yeah, so it's not just the insurance industry, it's pretty much every industry. So if you have a very specific focus, you're very specifically interested in those use cases, like we have received as a request to cover this industry. Just reach out to us on social or on our community website, theautomationguys.net. And don't forget to subscribe to our podcast and stay tuned for more episodes. Yeah, thank you for listening. And yeah, we will be back very soon. And until then, let's automate it. Unfortunately, that's it again. With this episode of the Process and Automation Podcast. If you like this episode, please give us a 5-star rating and don't forget to subscribe to this podcast so you don't miss any upcoming episode. We hope you will tune in next time, and until then, let's automate it. So automation systems can generate these real-time alerts when, for example, the pattern analysis then finds something weird, suspicious, and that alert can be sent to some investigators straight away, to the relevant departments, and you could immediately stop those things impacting the company. So yeah, fraud detection