Cognitive computing is constantly developing, and implementing this new technology requires both expertise and skill. Gaining deeper insight into the technology makes it easier to understand and make the most of the opportunities that it offers.
Both banks and their customers will benefit from the development of new, cognitive solutions. Better data mining generates valuable insight into customer usage patterns, and this can help a bank to be more relevant to its customers. This is because it makes it easier to customise solutions and adapt financial services to customer requirements. Banks can also become more efficient and accurate in their work with internal data in connection with lending, fraud detection and their management of regulatory requirements.
Cognitive solutions depend on data from multiple different sources. In the banking world, this data is often sensitive and needs to be managed with care. Developing new cognitive solutions often requires data to be moved from a bank’s own servers to its supplier’s servers for analysis. Identifying robust, reliable providers that have servers that comply with the bank’s security policy is therefore essential. In addition to encryption, for example, data can be anonymised or aggregated to optimise security.
High-quality data is essential
Cognitive solutions require enormous quantities of high-quality data that is rich in information. A lack of such data gets in the way of the ambitions that many banks have in the area of cognitive computing. Banks can have a lot of data in their systems, but if this data comes from manual processes it can often be poor quality and can provide only limited information on customers. In order to increase the quality of such data, a bank can used automated systems to gather better customer information. Accumulating enough high-quality data for cognitive solutions takes time, so this process needs to be started as soon as possible.
Resource usage in connection with implementation
Banks in particular can consider three different strategic options when looking to implement cognitive computing: a partnership, an acquisition or internal development. The strategy they choose should correspond with their vision, size, expertise and capital as well as with the personnel they have available.
As the technology is in its early stages, its implementation can require significant work and can be expensive. There are few examples to look to, and it is therefore difficult to be sure that cognitive computing will give you the return on investment you are looking for. There is, however, no doubt that cognitive computing will be a key part of most banking services in the time ahead. Learning and gaining experience as early as possible will provide a valuable competitive advantage in an industry in which banks compete for customers to a very significant extent.