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New Business Models Through Algorithmics and AI

 esides designing and optimising corporate functions and processes, algorithmics and AI also have the potential to challenge and reinvent business

models.

Netflix, for example, owes its current success to the fundamental disruption of a business model from video-on-demand to streaming media. This

way the company made it from the lower end of the market to the global

market leader in no time at all, even ahead of the streaming portal of the

giant Amazon. In addition to the production of their own series, Netflix

won recognition in particular through the AI they developed, guarantee-

ing maximum, dynamically adapted streaming quality, even if the Internet

bandwidth is very low. As a result, the company was able to even prevail on

markets with a rather underdeveloped infrastructure and establish itself at

the top.

Likewise, the agile start-up Airbnb is already threatening traditional

industry leaders such as Marriott. Having started out as an idea of an inexpensive solution for budget travellers with air mattresses in living rooms of

strangers, luxurious apartments can now be booked via the portal. The innovative price formation algorithm is setting new standards.

With the aid of a trained deep learning network, factors such as location,

furnishings, demand, but also presentation are weighted differently in real

time, and the system calculates a price tip for the host. In this way, the provider manages to serve an entire sector and offer all users the best price. The

popularity of this business model speaks for itself!

The financial service provider sector is also positioning itself anew.

Recently, the expanding and critically discussed start-up Kredittech has been

stirring up the market—on the basis of big data, it calculates a consumer’s

creditworthiness score with a precision and term that would not be imaginable with conventional methods. This way creditors can minimise their risk

of payment defaults and the credit applications of customers are accepted or

rejected much faster (Fig. 3.12).

The B2B sector is also reacting with appropriate AI-as-a-service, allowing

a digital, synthetic credit score to be calculated automatically on the basis of

big data and AI.

Offers of Robo Advisor such as scalable capital in investment consulting or the clark.de app in insurance consulting and administration are also

booming. Customers are informed about most recent market developments



in real time and are able to react. The offer can be adapted to exactly meet

the customer‘s needs, and accessibility of offerings via mobile smartphone

apps or Internet portals is not comparable with a local adviser.

In data economics, data also plays a central role as a source of expanded

or new business models. Figure 3.13 provides a list of questions to determine the potential of data for expanded and new business models.

Considerations are to be made as to whether available data can be used

to expand the business model or can be monetised through the sale to other

companies. On the other hand, in line with the assessment of potential

threats, it is necessary to examine whether competitors might possess data

that pose a threat to one’s own business model.

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