Implementing new technologies requires skills and knowledge, but cognitive computing is new and in its early stages of development. By getting familiar with the technology on a deeper level, it is easier to adopt the technology and understand its opportunities.
Areas of embedding cognitive solutions in banks
Deploying cognitive solutions create a win-win situation for both banks and customers. First and foremost, cognitive solutions enable banks to mine their data and provide meaningful insights, which position banks to offer more relevant and customised financial services. Another great opportunity for banks is to increase efficiency and accuracy within internal tasks such as review loans, fraud detection and manage regulations.
Cognitive solutions demand an enormous amount of high-quality data, which is rich in information. One of the challenges banks face when adopting cognitive solutions is that they don’t have enough high-quality data to realise their ambitions. Banks have a lot of data in their systems, but these data are from manual processes. As a result, the data has poor quality with limited information about their customers. It is, therefore, important for banks to identify which data they have and adjust their ambitions thereafter.
Banks should also begin collecting richer customer information using automated systems to acquire a better database for cognitive solutions. It takes time to accumulate enough high-quality data for cognitive solutions, so banks should start this process right away.
Data management, security and privacy concerns
Cognitive solutions rely on data derived from several different sources of information. The data used for these solutions in banks are often sensitive and has to be carefully handled. Developing cognitive solutions often demands moving data from the banks’ own servers to the vendors’ servers in order to analyse the data. This can be a challenge for banks since they lose control of their data. It is, therefore, important for banks to identify vendors, which can be trusted and have servers that comply with the bank’s security policies. In addition to different security systems such as encryption, the data may also be anonymised or aggregated to add an additional layer of security.
Implementation effort and cost
Since the technology is in its early stages, being the first mover embedding cognitive solutions, it may demand noticeable efforts and costs. Since there exist few use cases on the market today, it is difficult for banks to realise the return on investment (ROI).
However, adopting the technology today may give banks ROI in other ways than improved revenue or efficiency. For example, by experimenting with the technology, banks may gain experience for the next cognitive solution, which may bring up more value. Another advantage for early adopters is the marketing message of being forward-looking. Last but not least, first movers may have the benefit of collaborating and sharing the costs of development with the vendors that provide cognitive solutions.
Strategic options to implement cognitive solutions
Cognitive computing will be a core part of most banking services in the future. To adopt cognitive solutions, banks may consider three different strategic options: partnership, acquisition or in-house development. Banks should choose a strategy that align with their vision, size, competence, capital and available resources. Cognitive computing is here to stay, and banks should begin leveraging the powerful capabilities of cognitive computing to stay ahead in the market.
Download our cognitive computing whitepaper to learn more
This whitepaper explores cognitive computing, how it can be used in banks to overcome their challenges to stay competitive in the market and some strategic options to implement cognitive computing.
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