Technology trends in the securities services industry
September 2016

"The challenge for financial institutions is to leverage new technology trends in order to design bespoke offerings for customers in an industrial way."

Artificial intelligence, machine learning, big data, analytics, distributed ledger technology and cloud computing are all technology trends of importance to financial institutions because they offer the opportunity to improve our understanding of and interaction with customers. They also enable us to reshape processes and reduce costs. Cloud computing, for example, gives access to massive computing power, either via domestic country-based networks or private ones, at a low cost compared with even a few years ago.

Technologies such as AI and robotics are particularly useful for financial institutions with processes that are very labour intensive and require a high amount of human resources, such as reconciliations. Just as car manufacturers have already done, financial institutions need to envision all of the possibilities there are to reduce their costs base by introducing AI and robotics. This is beginning to happen in areas such as private wealth management, where some banks are deploying robot advisors on portfolios of below $1 million value. This technology has proved to be more reliable and accurate than human advisors.

Financial institutions are at present trying to understand how far they can go with technologies such as AI. Questions are being asked about how these technologies will affect production set ups and also communications with customers. The more familiar with these technologies financial institutions become, the better they can design services for customers that are more personalised.

In reviewing all of these new technology trends an institution can often become overwhelmed with too much information in too short a space of time. This makes it difficult to assess the impact of technologies on processes and customers. In many cases these technologies mean a new way of automating on the production side of the business; huge amounts of information can be computed and linked in a way that is beyond human capacity.

Big data is beginning to deliver on its full potential. Initially, financial institutions were used to stockpile huge amounts of data but they didn't really know how to use that data in a meaningful way.

Now we have technologies to build links between different data sets in order to better understand the behaviour of customers and as a result to anticipate and make better recommendations to customers. This means we can make more accurate proposals that are matched to the exact needs of the customer

On the other side, data can also be computed to improve industrial performances, understand and prevent risks in a better way and feed a continuous improvement of the production set up.

By Damien Jamet, Chief of Staff and Chief Digital Officer for SGSS





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"The challenge for financial institutions is to leverage new technology trends in order to design bespoke offerings for customers in an industrial way."

Artificial intelligence, machine learning, big data, analytics, distributed ledger technology and cloud computing are all technology trends of importance to financial institutions because they offer the opportunity to improve our understanding of and interaction with customers. They also enable us to reshape processes and reduce costs. Cloud computing, for example, gives access to massive computing power, either via domestic country-based networks or private ones, at a low cost compared with even a few years ago.

Technologies such as AI and robotics are particularly useful for financial institutions with processes that are very labour intensive and require a high amount of human resources, such as reconciliations. Just as car manufacturers have already done, financial institutions need to envision all of the possibilities there are to reduce their costs base by introducing AI and robotics. This is beginning to happen in areas such as private wealth management, where some banks are deploying robot advisors on portfolios of below $1 million value. This technology has proved to be more reliable and accurate than human advisors.

Financial institutions are at present trying to understand how far they can go with technologies such as AI. Questions are being asked about how these technologies will affect production set ups and also communications with customers. The more familiar with these technologies financial institutions become, the better they can design services for customers that are more personalised.

In reviewing all of these new technology trends an institution can often become overwhelmed with too much information in too short a space of time. This makes it difficult to assess the impact of technologies on processes and customers. In many cases these technologies mean a new way of automating on the production side of the business; huge amounts of information can be computed and linked in a way that is beyond human capacity.

Big data is beginning to deliver on its full potential. Initially, financial institutions were used to stockpile huge amounts of data but they didn't really know how to use that data in a meaningful way.

Now we have technologies to build links between different data sets in order to better understand the behaviour of customers and as a result to anticipate and make better recommendations to customers. This means we can make more accurate proposals that are matched to the exact needs of the customer

On the other side, data can also be computed to improve industrial performances, understand and prevent risks in a better way and feed a continuous improvement of the production set up.

By Damien Jamet, Chief of Staff and Chief Digital Officer for SGSS




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