Reimagine booking model controls

Many firms are dealing with the challenge of embedding their booking model control framework as regulatory scrutiny and expectations in this space mount up, while business complexity, customer expectations and trading volumes continue to grow. Forward-looking banks are responding with a new generation of centralised control solutions that allow for automated, preventative controls, ensuring trading activity is aligned to the firm’s booking model and strategy. The result creates a more scalable and sustainable, right first-time model. How can your bank get up to speed?

The booking model sits at the heart of the bank, governing multiple facets including how the firm manages bookings, risks and positions in different regions or for different entities. Controlling for this across asset classes and business locations, against complex legal entity structures is no mean task. Further hurdles range from proliferation of new trading platforms to the myriad of different interfaces and operational dependencies, both internally and across counterparties.

Under the spotlight

The direction of travel across global markets signalled by regulators including the UK Prudential Regulation Authority is to move away from ‘T+1 next day remediation’ towards a ‘right first-time preventative’ model. This is a big leap and for many banks this is likely to require an overhaul of their control model. Implementing pre trade or point of execution controls will require robust infrastructure that can achieve low latency requirements with good data to enable effective control. The control implementation task can be broken down and approached at a product, system or business level, though the firm risks ending up with disparate solutions requiring more ongoing overhead in ensuring consistent control application while any future changes will multiply the effort required for the roll-out.

Target state

A centralised firmwide solution that is flexible enough to handle the requirements of various elements of the booking model, for example legal entity mandates, trader mandates and cross border rules, offers a more scalable solution allowing multiple systems across the bank to connect up to a single control point ensuring consistent application of the booking model rules. Such a solution would be capable of bringing together and validating data from multiple platforms, entities and counterparties and could be achieved through a standardised application programme interface (API) to facilitate two-way data flows and accelerate integration.

Realising the benefits

The big question is how to implement this model in practice. In a perfect world you would probably want to strip out all the existing wiring and start again. But both the costs and need to avoid any breaks in trading makes this unfeasible. The model should also be able to adapt to new regulation, changing business demands and platform proliferation. Further considerations include whether to develop in-house or use a vendor solution, and how to harness and integrate new capabilities with existing systems.

Five ways to get ahead

How can you get your control model up to scratch in the most effective and pragmatic way? Drawing on our analysis of the changing demands and experience of working with a range of banks, five priorities stand out:

1. Check the health of your control model

Review the efficiency of your current controls in preventing and detecting breaches and compare this against best practice expectations. Map current capabilities and processes against incoming demands to identify gaps and gauge what needs to change. Key areas of focus include consistency of rules, understanding and enforcement of mandates, and the quality of validation and documentation needed to verify controls.

2. Foundational data source

Establish foundational data sources as required to support systematic control implementation e.g. standardised, machine readable central source of mandates and entity licensing and permissioning information for the firm’s businesses globally.

3. Data quality

Control implementation will utilise a variety of reference data for example product, client, trading entity, divisional and trading book data. If this reference data is not accurate, the control would be ineffective thus tackling data quality should be a priority.

4. Business prioritisation

There will be numerous systems multiplied by various instances across the bank globally that will require a control point. A big bang approach in rolling out the control carries enormous risk and will require a high level of resource capacity to execute the implementation. Prioritise business and systems, identifying potential higher risk, for example by volume, product type, known hot spots, to develop an implementation roadmap.

5. Bring your people with you

With so much focus on systems implementation, it’s easy to lose sight of the people this affects. Traders need to understand the impact of breaching their mandates, control protocols and any potential sanctions that might be imposed. Training and communication are therefore critical. A key aim is securing buy-in by explaining why the control model is being overhauled and how this can benefit them.

If you would like to find out more about how we can help with your booking controls, please contact Nicola Carter and Laavanya Raju.