SmartStream’s Andreas Burner discusses the development and launch of the firm’s new artificial intelligence solution
Can you tell us about SmartStream’s new AI and machine learning capabilities?
Last year, SmartStream announced the launch of SmartStream Air. Since then we have been working on SmartStream Air version 2, which is the latest artificial intelligence (AI) technology to transform data quality and reconciliation processes that would usually be measured in weeks and months, to just seconds. In addition, with cloud-based technology accessed via a new user interface, it manages large volumes of data, in any format, to achieve even higher match rates.
SmartStream Air version 2 has been launched to enable organisations with more complex data scenarios to instantly compare all types of data sets, regardless of format and complexity.
The latest version features inbuilt observational learning capabilities, this new AI technology is called ‘Affinity’.
Affinity observes the manual actions of a user and, once trained, supports the user and reduces the effort in the business workflow. It is an observational learning solution that aims to meet the technical demands and business agility for operational data management and data quality processes.
To explain how it is used, imagine there are three packs of poker cards, and I threw all the cards into the air and they land randomly on the floor. I then ask you to sort them by number. This task would be difficult, especially at the beginning, because the cards are everywhere and completely distributed. This task is very similar to reconciling data. Records come in unsorted and they need grouping and sorting to verify if there are disputes.
This is where Affinity comes into its own. The AI technology observes you, for example, which card you are picking up and how you are sorting the cards and after short periods of time it would become confident enough to organise the cards for you, so you can collate them without searching for them.
Affinity observes the users’ actions and establishes its own understanding of how records correlate. It will then assist the user and significantly reduce the time it takes for matching complex data sets. Once the neural network is trained, Affinity acts as a virtual user to support businesses dealing with large amounts of data – the more it observes, the more efficient it becomes, boosting matching rates – delivered to the end-user with high-quality results.
There is a big efficiency gain by using this technology.
The banks have recognised that they need to roll out AI and machine learning technologies to realign resources, increase straight-through processing (STP) and optimise costs.
In our projects, Affinity has outperformed matching rates of anything else available on the market today. Client projects have been very successful and they are estimating 20 percent cost savings for their reconciliation business. It is very gratifying that after 12 months of working with clients on our AI solutions, the technology has matured and we are now at a stage to deliver real value.
How can banks ensure the new AI solution is secure?
SmartStream Air version 2 carries the PCI-DSS label, which is the most recognised data security standard, and has been certified at the highest level of security standards when hosting digital payments data. SmartStream’s solutions are also certified with SOC 1, SOC 2, SOC 3, attestation, and ISO 27001 and ISO 27002 standard. This ensures robust security controls across the whole organisation, including physical security, personnel security, fraud control mechanisms, IT and data security and data privacy.
What are the main challenges when deploying AI for data management?
AI is only accepted if it is bringing value to the business users. In the financial industry, there is a lot of potential to bring real value to the business user, however too frequently we see financial institutions just adopting cloud strategies. There is a strong movement of firms moving to the cloud but they yet do not develop an AI strategy. Other industries already have developed and deployed AI technology, but in the financial services industry, SmartStream is one of the first and is seen as an early adopter and often we are asked to coach our clients how to set up an AI infrastructure. SmartStream Air has the major benefit that it can be deployed with our AI services as a well configured and packaged SaaS offering, so clients do not have to worry – they can simply subscript and use it.
Do you think the global pandemic has seen an increased amount of industry participants move to the cloud?
We have seen in the SmartStream managed services organisation that there is a big change. Data centres and other companies are deciding to move to the cloud in light of the COVID-19 pandemic.
Although having a cloud strategy in place is seen as positive, many firms are lacking an AI strategy yet, which would benefit users more than a cloud strategy alone.
For example, during the pandemic, payment settlement times were taking longer. With SmartStream and its AI functions, when the settlement times change within our cash and liquidity system, the system will adapt its cash predictions automatically. AI and machine learning are both very strong products in disruptive times, such as a pandemic, because they can adapt quickly, compared to older software that needs a lot of reconfiguration and manpower to allow it to adopt and adapt.
Do you have any further plans to develop AI and machine learning within your business?
We are currently starting five new feasibility studies to confirm AI business cases, the demand for new technology is huge and the team is extremely pleased to be partnering with our clients to make this happen.
Also, we are just starting to understand what Affinity can do for us, and it is one of the innovations of SmartStream where we are at the beginning to see its full power and benefit for our clients. The applications are endless and we have already seen extraordinary results.
With Affinity, it was interesting to see that we as humans are typically looking for correlations of data. However, machine learning can work by exclusion and it learns by excluding hundreds and thousands of records and identifies the right record. For a human that is impossible, for a machine that is doable and the results are amazing. There is a lot to learn with this groundbreaking technology and we will run further client projects and explore how we can use AI components in different scenarios.
What changes do you see within the asset services industry in terms of AI and machine learning?
The whole industry needs to provide a better user experience and there is so much to learn from the user experience that people have come to expect from Netflix and Amazon. For example, if you buy trousers, the Amazon website will recommend matching shoes for you or when you watch a movie on Netflix it recommends another film you probably will like.
The financial services industry needs to act and create a similar experience for users. For example, if somebody is looking to buy shares, the application should be able to recommend a product or service to that person.
The industry has so much data and we need to utilise it to empower users and business. It really needs to improve the user experience to stay competitive and AI/machine learning technology is an essential component to achieve this.
