Me, myself and AI


Rocky Martinez considers how AI can help improve post-trade processes, and how SmartStream’s new reconciliations solution is moving a step in the right direction towards helping firms keep costs at sustainable levels

Financial institutions currently face a toxic cocktail of flat revenues, heavy operational overheads and a growing regulatory burden. Even a brief look at today’s financial press suffices to underline how much advanced technologies such as artificial intelligence (AI) are now spurring the interest of the finance industry.

AI involves the automation of non-routine tasks that require a degree of judgment or problem-solving ability—qualities typically associated with the human mind. On the face of it, replicating such powers would seem an almost impossible task, yet significant progress has been made lately in this field. A new generation of technologies has emerged that has endowed machines with human-like capabilities, for example, the ability to recognise handwriting and images, or even process natural language.

AI is a complex beast, however, and the market for it among financial institutions is still in its infancy. Even so, banks and other financial services organisations are already harnessing its potential in areas such as anti-money laundering and compliance projects.

Feedback from SmartStream’s global customer base suggests that financial institutions are increasingly keen to hear how sophisticated technologies such as AI can be utilised to improve the efficiency of their post-trade processing operations. Underpinning this interest is an intensified need to reduce operational overheads.

Traditionally, reconciliations processing and other post-trade activities were carried out by large numbers of back-office staff. While banks’ revenues were buoyant these armies of clerks gave little cause for concern. In the aftermath of the financial crisis, however, flattened revenues became the norm, forcing financial institutions to rethink their approach to post-trade processing. Banks turned to automation, but projects often involved a variety of point systems, installed across different parts of their operations. This typically resulted in the creation of a series of disjointed processing silos, which prevented organisations from achieving much-hoped for cost efficiencies.

Forward-thinking financial institutions sought out an alternative to this piecemeal approach and instead opted to implement single solutions, such as SmartStream’s TLM Reconciliations Premium. Reconciliations-agnostic and able to bridge silos, TLM Reconciliations Premium can accommodate all of an institution’s reconciliations processing requirements in one place and, in doing so, create a ‘one-stop shop’ serving the entire organisation.

Having systems that are up to scratch is becoming more essential than ever. One reason for this is the pressure exerted by incoming regulatory initiatives, for example, the second Markets in Financial Instruments Directive (MiFID II) and Regulation (MiFIR) in Europe. These new rulings are forcing financial institutions to perform greater numbers of reconciliations and are increasing the complexity of the reconciliations they have to carry out.

Non-regulatory, internal reconciliations are also growing in volume. Financial firms now view the carrying out of reconciliations between internal systems as part as an essential part of best practice, and an important aspect of good governance. Performing intersystem reconciliations can be a complex business and so a powerful, robust solution is a must. A tangle of creaking systems will simply not cut the mustard.

A combination of lower revenues and a mushrooming regulatory burden is putting pressure on firms as never before; they must achieve more in the back office but with fewer resources and limited budgets. In the search for answers to this dilemma, financial institutions are asking whether technologies such as AI can assist them. In particular, interest in AI is beginning to increase as firms start to become aware of its ability to reduce risk and costs.

Responding to the challenges currently faced by customers, SmartStream developers looked at how they could inject greater levels of end-user autonomy into the company’s reconciliations processing solution, but without compromising any of the powerful functionality for which the system is known.

The latest version of TLM Reconciliations Premium sees the introduction of a new user interface. This allows business personnel to build reconciliations themselves, with minimal assistance from technical staff. Underlying the interface is a powerful layer of AI, which helps guide the user, promoting greater levels of independence and freeing business staff from reliance on busy IT departments.

Ease of use and design flexibility are central to the new user interface, which offers a series of attractive dashboards, giving business users great freedom to organise how they search, view, group and chart data. Tailoring the dashboards is a straightforward process, as a sophisticated, underlying level of automation suggests rules, makes recommendations and prompts the user at every stage.

Importantly, the new user interface removes the need for a separate tool with which to build and configure screens. Non-technical business personnel are therefore able to customise the dashboards themselves, with only minimal training.

The solution provides the user with the ability to view and analyse all the data, both historic and real-time, in the system’s repository. Detailed trend analysis can be carried out in order to improve operational outcomes, better hit match rates, and to identify common exception patterns down to attribute levels. As a result of these improvements, business staff not only have better access to information but greater flexibility to ask questions of it. The solution promotes independence, too, as managers and other personnel can search and analyse data, without the need for additional IT support. This makes the solution an ideal choice for self-service models and potentially helps financial institutions cut operational overheads.

In answer to clients’ requirements, the SmartStream solution has been updated to enable more rapid onboarding and to promote greater levels of end-user independence. A fully-integrated service, TLM SmartRecs, has been introduced to orchestrate the onboarding of new reconciliations or the tuning of existing reconciliations. A powerful layer automatically suggests matching patterns for new reconciliations, giving non-technical business users the ability to test and build reconciliations without IT support. Importantly, by being truly reconciliations-agnostic, the TLM solution can onboard any type of reconciliation. Combined, these aspects assist banks and other institutions to cope with the growing volume of both regulatory and non-regulatory reconciliations they must perform.

In addition to these new services, and to further assist financial institutions in their battle to keep operating costs to sustainable levels, the solution also offers a range of different persistence models. These enable organisations to make choices as to how they store information—for example, in a relational database or using an alternative, lower cost means—depending on the business need involved.

Research and development has always formed a very significant focus for SmartStream and it is an area in which the company has invested heavily. SmartStream recognises that financial institutions are under intense pressure from a combination of diminished revenues, high operational overheads and the costs of complying with regulation, and it recognises institutions’ willingness to experiment with the latest technologies in order to combat these pressures. SmartStream development teams have, therefore, during the last year, been expanded in order to ensure that the TLM solution takes advantage of advances in areas such as AI.

Development work has also taken place to ensure that the SmartStream solution is aligned with other emerging technologies such as robotic process automation and distributed ledger technology.
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