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Technology today is making onboarding much easier for customers across segments. And offer opportunities for companies to take a holistic view of onboarding - as a process where they can help the customer, get to know them, learn more about them, and offer additional services or products tailored to their needs based on the data the company has collected. All this in seconds, minutes at most, and for the best possible customer experience.
The advent of the pandemic has increased customer demands for convenient onboarding. They expect to handle it with one app, from any device, and in moments. Regardless of the segment, the need for what they want to handle or the product or service they want to negotiate.
Just two years ago, a number of surveys, like the one from PwC, showed that three-quarters of companies already offered online onboarding via a web or mobile app. At the same time, the research revealed that many of these companies did not have smart assistants. Or advanced systems to cater for text conversion and fast document processing.
Smooth onboarding through technology
Another Experian survey of 380 senior executives and leaders illustrated this insight. A full 70% of them admitted that their companies are not delivering an optimal customer experience across the touch points of the customer lifecycle.
Yet even two years ago, customers could be onboarded relatively seamlessly. Today, technology is leaps and bounds ahead in helping companies engage and build relationships with their customers. The kind of relationship that shows customers that the company knows them based on data. And at the same time, the kind of relationship and access that will make customers want to come back.
That’s why it’s a good idea to take a holistic approach to onboarding. Using approaches and the latest technology to make it as customer-friendly as possible. And in turn, to help the company to get better relationships, data and more effective sales without annoying the customer. In our case, it’s the use of artificial intelligence.
Automated and safe onboarding for both sides
Remote onboarding, in which the customer does not have to visit the company’s brick-and-mortar branch, is a must in the age of covide. But in some sectors, we have long seen the adoption of onboarding technologies as far more skeletal. One of these is the financial sector. According to a Deloitte survey, at least 38% of customers abandon the onboarding process at traditional financial institutions during the onboarding process. This is often due to frustration with the number of steps and paperwork required or the need to visit a branch as a final step.
Such onboarding requires identification and possibly additional documents that must then be reviewed. And the necessary data manually entered into systems. This takes time, a lot of manual work and transcriptions often lead to errors. Systems based on optical character recognition (OCR) and natural language processing (NLP) take over these processes and process the documents immediately. They handle the conversion of documents into digital form. From our own experience, we know that they reduce the costs associated with manual document processing by up to 80% and the time by up to 98%.
Based on our implementations, we know that it’s seconds to process documents. The system then verifies the retrieved values across public databases (address, name) and between each other (consistency of retrieved values). The output is data in a machine-readable format that is ready for further processing. Similarly, a data extraction and verification system will help comply with regulations requiring biometric verification using a standard web or mobile camera.
Control mechanisms and fraudulent conduct
However, there are types of companies that encounter fraudulent behaviour during onboarding, despite control processes with defined rules. These include, for example, telecommunications companies that deal with fraud attempts in connection with subscriptions and tariffs (customers not paying for services and devices). Even with this type of business problem, artificial intelligence helps.
Clever algorithms based on machine learning detect fraud attempts almost in real time. Moreover, thanks to continuous learning. They are also able to detect the latest and most sophisticated fraudster tactics from the data. By deploying such a solution, companies can minimize the number of frauds, improve risk management and strengthen the fraud prevention process by up to approximately 30% in our experience. At the same time, the technology helps reduce the number of false positives by up to 60%.
Another level of control and a recent trend is then behavioural fraud detection when completing, for example, online questionnaires and documents. Mouse movement, click speed, keyboard typing patterns, number of typos and other behavioural biometric points serve as input data for the AI to analyse. The technology is thus able to identify an individual person as well as the general pattern of normal behaviour, and therefore also deviations from it.
A quick helper that’s always at hand
No matter what a customer is looking for in a company, they often appreciate a virtual assistant or chatbot to help them with onboarding or filling out more complex documents such as investment questionnaires.
Chatbots and assistants, which have experienced a major boom in the last three years, operate on the basis of machine-based natural language processing. They can interact and evaluate what the user is asking and compose and send a relevant response. This is all thanks to the integration of the assistant/chatbot layer with the understanding layer, for which quality data from which the assistant learns is essential.
This allows the application to decide whether it needs to ask other systems to answer the query and what response to send to the customer. Moreover, many customers prefer it to seeking help from customer care operators – the technology works at any hour and responds instantly.
Personalisation of everything that concerns the customer
In a few seconds, the company can automate the first verified data and create an initial overall picture of the customer, on which further data should be added. The more data, the better the picture companies can have, while making more effective decisions in the overall context.
At the same time, the data is used to adjust and improve the digital experience of the company. Thanks to constantly learning algorithms, this is a continuous process. Artificial intelligence, specifically machine learning, can easily find new relationships and rules in customer data, allowing the company to significantly improve its offering as well.
So it always pays to take a holistic view of the data, in the case of customers, it’s called customer 360. Based on both online and offline data, a picture can be created that can be used to subsequently create personalized interactions throughout the customer lifecycle, e.g., the acquisition of an asset (car, real estate) or a life event (wedding, addition to the family). This makes it easy for the company to offer the customer a loan consolidation or mortgage when they need it, through the most convenient channel for them and at a price they are willing to accept. Moreover, it is in the financial and insurance sectors that the use of artificial intelligence in the creation of offers is expected to be essential.
In addition to purely business purposes, data is used to tailor content according to communication channels: personalisation of content on the web, in the client area, in the annual letter, etc.
Better targeted sales
In addition to tailored offers, AI also significantly helps in upselling (an approach where sales offers the customer to buy a more expensive version of a good or service, or an upgrade) and cross-selling (techniques for selling related goods or services to complement those the customer already has). This is when the customer sets up specific services and products or access to the company.
With the data the company has on the customer from all the different channels, contracts and history, salespeople know which products and services they can still offer. So that they are relevant to the customer and at a price they will be willing to pay. Or offer those that will complement their existing products and services appropriately. In this case, AI can easily calculate the optimal highest price the customer will be willing to pay, as well as easily recommend products and services at the appropriate time and tailored to the specific customer.
There are a number of options and processes where AI can be deployed to make a real difference. Therefore, their adoption and implementation needs to be considered in terms of need, business goals and pluggability into the running of the company and its processes. There is a proven innovation framework that guides a company through the entire process from idea to implementation. At the same time, our so-called AI Open Days, where we help companies generate AI business use cases tailored to their needs, have proven to be successful.
Author: Ondřej Vaňek – co-founder and CEO of Blindspot Solutions – article was published by IT Systems magazine 3/2021. You can also find it online at systemonline.cz.