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Digital transformation in Finance: why can't you afford to ignore it
Many firms struggle with decades of legacy data stored in dozens of disparate systems. Thus, digital transformation in Finance may seem like a daunting task. There is not enough time for banks, insurers and others in the sector who have not yet made the transition to digital.
The struggle for security
According to the trend of recent years, data thieves and hackers were able to gain a number of high-profile hits in 2017. Firms such as Verifone, Dun & Bradstreet, Equifax, even SEC all reported data theft last year. The result will be a steady stream of new and stricter privacy and security rules, both from internal and external sources.
An external example is the EU General data protection regulation (GDPR), a new strict set of rules that will apply to any enterprise doing business with EU citizens. For most current accounts, many organizations are unfortunately not sufficiently prepared for the additional burden that these new rules will place on their data infrastructure, and they will need to take decisive steps to develop and implement effective compliance programmes — and quickly.
Internal security efforts will also increase as the negative impact of data breaches increases. A number of financial companies are exploring the technology of the blockchain as a means of safe information transmission, thus depriving the captors of the data substantial purposes which often provide local data storage or cloud storage. Although the technology is still very much at the experimental stage, it promises, provided that some of its more complex problems can be solved.
IoT, artificial intelligence and improved customer service
At the dawn of the era smartphones brought with them many new challenges for banks and other financial companies, as well as new opportunities. By combining the functions of a typical smartphone-Geolocation, camera, touch biometrics-with advanced Analytics, institutions can optimize common processes and provide real-time sales or cross-selling offers, increasing revenue and strengthening customer relationships.
However, most organizations are slow to develop such solutions because their own analysis and data groups are often overloaded with day-to-day tasks. As a result, external resources are required.