Funding for digital technologies
There are a variety of funding programs that can be used for digitization efforts. A good overview of current subsidy programs, for example, is provided by the funding database, in which many funding offers of the funding agencies (federal, state and European Union (EU)) are prepared and can be filtered according to relevant characteristics. Since the funding programs differ according to beneficiaries, possible recipients, purpose, type of funding and their topic / content / funding purpose, it must be decided which funding programs are suitable for the individual case. The following orientation questions
can help in the search for suitable funding:
- Who is entrusted with the implementation?
Not every funding program is available to all levels of local government or municipal enterprises or institutions; Therefore, it is first necessary to clarify where the financial resources are needed and who will become the recipient of the funding. Appropriate cooperations (eg with the private sector or research) can help to fulfill the funding target.
- Where should the project be implemented?
Depending on the funding program, different regions can be addressed, which are characterized, for example, by common characteristics or their geographical location. The Federal Ministry for Economic Affairs and Energy has recently launched the federal model project “Company Revier” for four regions, which are particularly affected by the structural change due to the brown coal withdrawal. There, regional investment concepts are to be implemented for specialist security, alternative value chains to strengthen regional economic power and increased attractiveness of the location, with a focus on future topics such as Industry 4.0, Crafts 4.0 and other digitization topics. In addition, a number of country-specific programs for the promotion of digitization exist. For example, in the competition “Digitale Zukunftskommune @ bw”, four municipalities and one regional association are supported in the elaboration of their digital agenda, which are selected in a competitive process beforehand.
- For what purpose are funds needed?
The purpose of the grant is decisive in the application for funding. In this case, it is fundamentally possible to make a distinction as to whether investments are necessary for the intended digitization project or whether it is only a matter of increased internal expenditure for the implementation, for example, In the form of personnel and material expenses. However, high initial investment plays an
important role, especially for the creation of a digital infrastructure, for which additional funds are needed. Funding in the infra- In this context, structural areas often focus on new investments, which can be used to explicitly promote digitization efforts.
Uses for the Internet of Things
The Internet of Things (IoT) refers to the widespread embedding of sensor and wireless technologies into objects, enabling them to convey data about themselves – about their identity, their condition and their environment ,
The number of items that can record data and send it to other items is steadily increasing. It is estimated that 50 billion homes will be connected to the Internet by 2020. This network of interconnected devices generates continuous data streams that can increase efficiency in a variety of business operations.
Many applications already exist: in public transport in tracking the arrival time of buses, in the pharmaceutical industry in the monitoring of temperature-sensitive products, and in insurance in the monitoring of the behavior of car owners, to provide more cautious drivers with price advantages in insurance. offer a premium. As the cost of sensors and data transmission continues to decline, we will soon be at the point where commercialization of the IoT is finally taking hold.
In the financial services sector, no convincing applications have yet come to market. But the IoT has many valuable applications (see Fig. 1), i.a. the following:
- Product design: For leasing offers, for example, For example, parameters such as mileage or loads transported are used as the basis As with traditional models, only consider the lease term.
- Risk Management and Pricing: Managing collateral is a key component of risk management. Better data on the quality and condition of collateral allows a more accurate risk assessment and assessment.
- Understanding customer needs: Accurate tracking of business activity could provide clues as to when a company has additional need for growth financing, such as: B. becomes apparent when leased machines are fully utilized and when not.
- Simplification of contractual processes: IoT devices will be able to collect and transmit data to digital platforms that manage and audit so-called “smart contracts” (computer protocols that review contracts or automatically enforce rights) Real-time data on these platforms can facilitate efficient monitoring of agreed covenants, automatic payouts, and the automatic release of collateral or goods.
Added value through Smart Data
Digital technology has significantly increased the amount of data available. Yet, banks have had difficulty creating value for their customers and themselves with the help of this new data.
In contrast, e.g. Online merchants and social media companies found ways to generate more value from data.
Some examples, like online retailers from data
Create added value:
- Customer buying habits are used as the basis for product recommendations, which increases the accuracy of fit and thus the success rate of offers and improves customer loyalty.
- The viewing and listening habits of media users are monitored to make appropriate recommendations about new products and services or to customize third-party advertising.
- Real-time or contextual satisfaction surveys indicate when a customer is dissatisfied and help diagnose appropriate customer loyalty initiatives.
- Location data is used for security and fraud controls or location-based referrals, adverts, and offers.
Despite significant investments in data management, financial institutions in this area lag far behind companies from other industries. It is not uncommon for big banks to spend more than $ 500 million on programs to address the data management challenges. At the same time, however, it can be widely recognized that these investments have not yet led to higher profits. In their attempts to use data for the improvement of their product range or the reduction of their operating costs, banks are far from creative or energetic enough.
The vast variety of problems that can be solved by data requires special Fachkomppe¬tenzen, where banks often lack. They could leverage the know-how of fintech companies by entrusting them with the task of performing the required analyzes or buying them. Through partnerships between banks and fintechs, the banks’ databases and the innovative analysis tools of the fintechs could be combined with each other extremely effectively. Figure 4 illustrates the types of applications that could be tackled.
The first step towards smarter data usage is to identify the problems data can solve. As banks exchange their data with those with relevant experience and analytical skills, specialized teams can help specialized teams develop algorithms that reveal trends, patterns, and anomalies. This would enable banks to derive real value from their steadily growing databases.