While digitization is progressing, financial institutions are facing difficult tasks. Data is the new precious asset. New technologies must be implemented fast while the daily business runs on the existing system. But challenges are one of the best ways to spark innovation. Interdisciplinary teams have already been formed to embrace this transformation.
Data analytics transform unstructured data into actionable insights. The same techniques can also be applied in business. With the right technical support, analytics tools can help companies ease the pain of compliance and uncover untapped potential. Banking is a case in point. Financial services organizations save vast quantities of data, which are often underutilized – or at worst completely untouched.
The financial sector is one of the first domains to drive interest in using artificial intelligence (AI), even before high computing machines were available. With the release of Louis Bachelier’s thesis Théorie de la Spéculation (Theory of Speculation) in 1900, advanced mathematics in the financial field originated and the rise of statistical modelling marked the beginning of primitive AI in
Compliance has become a fact of life in today’s world – and it’s clearly here to stay. This means mounting challenges for companies, continually faced with adopting new measures to prevent violations. Compliance is also becoming part and parcel of corporate governance and risk management. An ominous prospect for some, fearful of a major administrative burden and rising costs. For
False positives: A harsh truth Alongside a string of compliance developments in recent years, companies still have the same old issues to deal with. False positives are one such serial offender. To avoid missing any critical hits, compliance systems tend to strike early, triggering false alarms. Weeding out these false-positive results can take up a substantial chunk of a compliance