The trading life cycle is often plagued by siloed and fragmented data and a heavy reliance on human communication - issues that can lead to operational inefficiency and challenges with regulatory compliance explains Alastair Rutherford, managing director of Ascendant Strategy.
The TaDa chatbot is a technology that can help trading firms accelerate data access and sharing, increase operational efficiency, reduce costs, and improve regulatory compliance. According to Juniper Research, the operational cost savings from using chatbots in banking will reach $7.3 billion by next year.
To understand the potential impact of chatbots in capital markets, we must first acknowledge the challenging nature of the capital markets trade data environment.
The main reasons why we continue to see siloed and fragmented data in this environment are lack of investment (over not just years but decades) and tactical solutions being introduced into legacy platforms that makes data flow even more complicated and unreliable and harder to change.
This poor decision making and minimisation of investment when changes must be made creates an environment that is often referred to as a ‘data jail’ where it is very difficult to extract data from systems that all have different data models
The same transaction represented in two distinct systems could be very different in its representation and the way lifecycle events are represented can also be very different across different parts of the architecture.”
Very few people fully understand how data flows through this environment, how it changes on the way through, where copies and versions are made, and what certain indicators mean in different parts of the organisation.
Settlement impact
This leads to things going wrong that impact settlements and regulatory reporting. A typical scenario here would be a salesperson sitting in the front office who has executed a transaction for a client and where the client has contacted them to ask for the details around the transaction.
That salesperson would send an email to a shared inbox, where it would stay until it was picked up by someone in the settlements group who would make a request for the information. During this process the salesperson would have no idea if their request has been actioned or how it is progressing.
What often happens is that in the meantime the client has called up and told the sales person not to bother – which makes the sales person look inadequate for being unable to source the requested information from within their own organisation.
In this case, lack of transparency around requests for information has negative implications for client relationships. By helping the front office self-serve, the chatbot improves the experience for both internal and external customers.
Another possible use case is understanding the settlement instructions for a particular transaction, which may come as a request from the front desk into the reference data group.
Systems tend to be siloed within functions – so there will be multiple functions within operations, for example, whose systems tend not to be well integrated and this is also the case across finance and risk.
Information access
The solution to the challenges outlined above is to make it easy for people to access information residing in systems outside their functions, which is where TaDa comes in.
The TaDa bot queries ETD’s extensive data library including Intraday Symbology, Contract Specifications and Regulatory Data Updates from 110+ global exchanges. It has a simple user interface and an easily accessible set of commands where requests can be made with a trade reference and the bot interacts with other technologies and APIs to retrieve the information.
This means that the user not only gets the information they need quickly – they are also not dependent on human interactions that can take an indeterminate amount of time.
For various control purposes it is very unlikely that someone in one area would be granted access to information in another area as they may see things that are inappropriate to their job function.
Legacy systems typically don’t have granularity of control in a standard access set-up, so being able to control the delivery of data to only that required for the person to fulfill their job function is very useful.
The challenge from an implementation perspective in a legacy infrastructure environment is the API connectivity into the legacy platform, although this is more a case of setting priorities. The benefits of moving away from having large numbers of people making and processing requests more than outweigh the cost of building the API.
Data sets
Some of the data sets available through TaDa include corporate actions, contract issuance, and historical transactions. Corporate actions data is particularly interesting as someone sitting in the
settlement function faces the same challenge when it comes to communicating with the reference data group as the sales person has with the settlements group.
TaDa enables these individuals to quickly retrieve up to date information, so it is not just simplifying access within the organisation – it is also making it easier to access an external data feed.
Those working in corporate actions can also create customised watchlists around forthcoming events.
TaDa also has a role to play in helping users ensure compliance with regulatory rule changes such as the move to T+1 settlement, which could be implemented for US equities transactions as soon as March 2024.
The benefits here relate to data accuracy. When a transaction needs to be classified in a specific way, if it is hard to access the data the transaction may be mis-classified. This applies across all aspects of regulatory reporting down to something as basic as the set of transactions that need to be reported on.
If the user is able to query the transactional database without having to go through a different group, they are more likely to provide accurate data to the relevant regulator.
In conclusion
The trade data environment is plagued by siloed and fragmented data, which often leads to operational inefficiency, increased costs, and regulatory compliance challenges. TaDa chatbot is a technology that can help trading firms overcome these challenges by providing quick and easy access to data residing in systems outside of their functions.
The chatbot's extensive data library and simple user interface enable front office self-service, which improves the experience for both internal and external customers. TaDa also has a role to play in ensuring compliance with regulatory rule changes, improving data accuracy, and reducing misclassification of transactions.
By embracing technologies like TaDa, trading firms can accelerate data access and sharing, increase operational efficiency, reduce costs, and improve regulatory compliance, leading to a more successful trading life cycle.
