6 pain points of traditional data collection in insurance and how to solve them

Insurtech startups are growing by the day, with insurtech investments more than doubling from 2019 to 2021.  Most of these new companies focus hard on a digitally enhanced client experience based on data, which McKinsey analysts say poses a "competitive threat to incumbents." 

Such an experience is only possible when organizations have access to consistent, connected, and accessible data. But most insurance companies are still using traditional data collection methods, including email questionnaires, webforms, PDF forms, and good old-fashioned telephone conversations. Inefficient data collection is the root of the problem, leaving you without the data insights that your rivals are using to gain market share. It's holding your business back from accurately understanding customer needs, assessing risk, predicting trends, and delivering good customer experience (CX). 

Here are the 6 main pain points that stem from traditional data collection, and some suggestions about what your organization can do to resolve them. 

Pain point #1: data is not accessible

The data you gather is only useful if it's accessible across the organization. When data trickles into your company in a fractured manner, through a PDF form here, an agent telephone conversation there, and a web form from yet another direction, it's very likely to end up isolated in siloes scattered throughout the business. 

One department might have ownership over data that would be helpful to another department, but the other department doesn't even know that it's there, let alone have an easy way to access it.. You might even find that each agent has vital customer data in their files, inaccessible to the employee sitting next to them. 

Pain point #2: it's hard to view the right data at the right time

Gaining the data you need is only part of the challenge. You also need each insurance agent and underwriter to be able to see that data at the right time. Having to wait for gatekeepers to respond to a query about claim levels or recent risk assessments adds an unnecessary delay to application or claim workflows. 

When we talk about seeing the right data at the right time, we also mean viewing recent, fresh, and up to date data. When data is siloed in individual employees' files or one department's storage, it's often difficult for underwriters or agents to track down the up to date data they need. 

Pain point #3: data is often unreliable

A great deal of insurance company data is collected using fillable PDF forms, or else over the phone when a representative is talking to a customer. With manual data collection methods such as theses, it's all too easy for mistakes to creep in. 

When customers complete forms without professional support, there's a risk that they'll misunderstand a question, or skip a vital field, which you need to have completed in order to accurately assess the request. It's not always much better when agents ask the questions. They might mishear names and addresses, make spelling mistakes, and/or misunderstand the customer. 

Because PDFs are file-based, they have to be fully replaced every time there's a small change in customer details, which is a hassle for agents and irritating for customers. The more friction there is in gathering data, the higher the risk that data is outdated or incorrect. This data could then guide agents to the wrong decisions. 

If you can't rely on your data to be accurate and up to date, you can't make decisions with confidence. 

Pain point #4: automation is out of reach

Deloitte's 2022 insurance industry outlook reports that around 70% of insurance companies are increasing spending on data management tools this year, and 74% are investing more in artificial intelligence (AI), which supports automation, among other advantages.

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[.figure]70%[.figure]

[.emph]of insurance companies are increasing spending on data management tools this year[.emph]

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If you want to keep up with insurance leaders, you need to make your operations more efficient. In 2022, that means adopting robotic process automation (RPA) to automate as many repetitive manual workflows as you can. 

But it's impossible to automate when your data isn't standardized. With older data collection and storage methods, data is often not collected in a standardized manner or stored in standardized formats. You also can't easily automate data workflows when some data is stored in word docs, some in PDF answers, and much of it is locked away in the individual agent's files. 

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Pain point #5: manual data processing is expensive

It's not just that historic data collection methods are often inaccurate and lead to data silos, although that's bad enough. Manual data processing is also time-consuming and expensive, especially as your datasets grow. 

The more data you have, the more people you need to pay to spend time verifying, and when necessary cleaning, datasets. Manual data processing sucks up employee work hours which could be better spent on activities that drive revenue, and require more outlay than introducing and running automated data processing. 

Pain point #6: customer experience is suffering

All these issues negatively impact customer experience. Customers have to wait to get responses to their requests for quotes, renewals, or claims, at a time when everyone is used to instant gratification. Agents are forced to ask customers to answer the same questions they answered yesterday, because they can't access their previous replies.

In 2022, when consumers are accustomed to smooth digital experiences and personalized financial products, they have no patience for such delays or avoidable friction. One survey found that poor customer experience was the top reason why people switched insurance providers, outstripping either price or coverage issues, with 26% of respondents saying they moved to a different provider in the last 12 months. 

It's vital to resolve these data collection pain points if you want to improve customer experience and prevent churn in your company. And you can do it with ease when you switch to digital data collection. 

Digital data intake journeys can help overcome these challenges

When you use digital data intake journeys to collect customer data, you can address all the above issues:

• Data gets verified in real time on point of entry. 
• All data streams are automatically directed to a single data repository, so datapoints can be cross-referenced and all your data is united. 
• It's easy for agents or customers to update any individual data that has changed, without having to complete the entire form again

Enabling automation through digital data collection

Digital data collection streamlines and standardizes the customer data intake process, enabling automated workflows downstream, pushing the right data to the right agent at the right time. This gives each agent the information they need to respond quickly to each customer query, make fast decisions about risk, and swiftly process claims, quote requests, and renewals. 

That's what US-based insurance company VGM did when they replaced their manual data processes with digital data collection, so as to improve the customer journey.

Once you begin automation, you can improve CX even more by using AI to crunch data and offer personalized products and self-guided customer journeys. For example, German insurance company Nürnberger introduced a new digital customer journey at the beginning of the pandemic, which enabled them to automate processes enough to offer customers self-serve insurance policy options.

Switching to digital data lowers operational costs at the same time as improving customer experience, delivering an overall boost to profit margins. McKinsey reports that even the top insurers saw loss ratios improve by three to five percentage points, new business premiums increase 10 to 15%, and retention in profitable segments jump 5% to 10% by raising the bar on their data and analytics capabilities. 

Digital journeys offer pain-free data collection

Classic, mainly-manual data collection processes are expensive, error-prone, and an obstacle to innovation and improvement in insurance companies. By gathering customer data digitally, insurance providers can make their data more reliable, accessible, and up to date, while saving money on data processing. Digital data collection enables more efficient, automated workflows, and ultimately improves the customer experience.