They [Yameo] adapt quickly, they’re responsive, and they have good technical skills. I’ve worked with different companies before, and we sometimes receive a product that works but is a nightmare to maintain. I haven’t had this kind of problem with Yameo; they think through the architecture. They always ask good questions about how we want to use the platform in the future, whether it will be multi-country, multi-customer, or so on. They’ve created a very nice and scalable architecture.

Jacek Salek
Jacek Salek
Director
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Artificial Intelligence in customer-facing processes. What you probably do not know.

23 May 2022 posted by Maciej Krajewski

I’m pretty confident everyone has heard of Artificial Intelligence at this point. Human intelligence and discernment are used by computers to carry out tasks and activities where normally you need a human. In customer-facing processes, we are probably most familiar with A.I. in the form of chatbots – either on a website, in a mobile app, or in other front-end solutions. Yet there are already hundreds of examples of solutions using A.I. – you’ve probably already used an A.I.-based solution today.

  • Google Maps: Analyses the speed of movement of traffic. It also takes in user-reported incidents, such as traffic accidents or road construction, to predict how long it will take you to reach your destination and uses that information to suggest the fastest route.
  • Your Roomba: uses A.I. to scan the size of the room it is in, identify obstacles, and determine the most efficient route to sweep the space.
  • Facebook, Snapchat: have all utilized A.I. in their facial recognition technology. Snapchat uses A.I. to recognize users’ faces and apply face filters to users’ photos. On Facebook, facial recognition is used to identify faces in photos and invite users to tag themselves or their Facebook friends.

 

So with A.I. becoming so readily used in our everyday customer-facing processes – how about for Insurance, Financial Services and Healthcare? These are the 3 big industries focused on customer services.

 

Insurance

According to a McKinsey article from March of last year, there are 4 big trends to watch for in insurance:

1. A huge growth of data from connected devices

With consumer devices becoming more technologically advanced they expect more data to be used from everyday items like watches, your car, smartphones, home assistants, fitness trackers, and door cameras. This trend will continue as currently, other less technologically advanced items like clothing, eyewear, and home appliances push to close the gap. The expected result will be a huge amount of data helping insurers satisfy their customers with new products, personalised pricing, and better real-time service delivery. What do you think?

 

2. Increased prevalence of physical robotics

By 2030, a much larger proportion of standard vehicles will have autonomous features, such as self-driving capabilities. Carriers will need to understand how the increasing presence of robotics in everyday life and across industries will shift risk pools, change customer expectations, and enable new products and channels.

 

3. Open-source & data ecosystems

As data becomes omnipresent, open-source protocols will emerge to ensure data can be shared and used across industries. Various public and private entities will come together to create ecosystems in order to share data for multiple use cases under a common regulatory and cybersecurity framework. For example, wearable data could be ported directly to insurance carriers, and connected-home and auto data could be made available through Amazon, Apple, Google, and a variety of consumer device manufacturers.

 

4. Advances in cognitive tech

Cognitive technologies, which are based on the human brain’s ability to learn through decomposition and inference, will become the standard approach for processing the large and complex data streams that will be generated by insurance products tied to an individual’s behavior and activities. With the increased commercialisation of these types of technologies, carriers will have access to models that are constantly learning and adapting to the world around them—enabling new product categories and engagement techniques while responding to shifts in underlying risks or behaviors in real time.

 

Financial Services

In a World of Finance article from February of this year, the main focus for A.I. in this industry is on better service offerings and minimising risks such as cyber security and fraud.

Better service offering 

Although financial services are predicted to always need a real human presence, A.I. is forecasted to play a pivotal role in the systems that customers interact with. Think along the lines of A.I. understanding consumer behaviours and recommending on-point and relevant services. Financial service organisations already use AI to detect fraud, predict cash-flow events, create invoices, fine-tune credit scores, conduct cost and benefit analysis, as well as for account creation and goal setup. And the forecast is that this will continue and expand.

 

Minimising risks – cyber security & fraud 

Where A.I. can help understand consumer behaviours and offer better service as a result, this can also help with fraud detection. A.I. is expected to become more aware of fraudulent practices and identify them much quicker and more reliably than a human can. Elements such as cyber security can be greatly improved as A.I. is able to quickly identify loopholes and weak points in banking systems.  

 

Healthcare

One of the biggest challenges facing healthcare is supply-demand. There is a huge demand for doctors and medical staff worldwide whilst the supply of newly trained professionals is not keeping up. A recent Economist article researched how A.I. will shape the healthcare industry moving forward. 

Currently, experts are saying that A.I. in healthcare is in the 1.0 phase – meaning A.I. helps with automating mundane tasks. A.I. 2.0 is where the industry is heading when large-scale data can be analysed and combined with medical knowledge to create new products and services which help with the care, prevention, and curing of diseases. The perspective is that A.I. will become a game-changer in healthcare and by 2027 the A.I. market will have grown by 8x since 2020. Healthcare providers will not be able to function by 2040 without some form of A.I. in their patient-facing care.

So with A.I. becoming a more readily used technology, when should you start with A.I.?

The answer to be honest in my opinion is now. Where previously trends like ‘digitalisation’ have taken decades to kick-off and become ‘mainstream’, this is not the case with A.I.. Artificial Intelligence is already a common technology in many everyday services and products we use. You may already have A.I. elements on your omnichannel in a chatbot or voicebot. We have also seen a rise in A.I. requirements in the projects we do for customers, from picture analysis and automatic damage assessment for insurance to visual identification of customers for our kiosk banking platform. The key here is to know where you can effectively use A.I. to have immediate gains for both you and your customers. Considering a Zendesk study where it is identified that 50% of EMEA customers said they would switch to a competitor after a poor customer service experience it is becoming vital that organisations adapt to become customer-centric in their use of new technologies like Artificial Intelligence. 

 

Where to start with A.I.? 

I’d like to say the first place to start is with Yameo! We have dedicated teams ready to brainstorm, learn your processes and identify where A.I. solutions can support your customer-facing processes. However, the first place would be with the persons responsible for innovation, strategy, customer service and operational success. After I would say a good step is to brainstorm with a partner who understands healthcare, insurance, or financial service customer processes. 

 

If you have your own idea on A.I. or would like to receive some more insights, get in touch with one of our specialists.

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Maciej Krajewski

I am a Software Engineer and Software Manager myself and I know what bothers you. Doing robust software is fun if you have enough experience and work with serious people.

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