Professional Services

Our professional services span the risk and analytics spectrum: from strategic advice on credit strategy and product development, regulatory and policy developments through to data sourcing and integration we can help you achieve your objectives. We are experienced in model development, model validation and business intelligence and have deep domain expertise in decision systems and governance.

We can support your organisation through an immediate business challenge, like building or adapting a credit strategy, measuring risk, valuing a portfolio or identifying new marketing opportunities. Or we can work with you to develop and implement a longer term strategy to build a risk framework or integrate analytics into your business. We have the proven capability to unlock the potential for data-driven decision-making to increase productivity and generate revenue.

We focus on providing the domain knowledge and expertise to solve challenges and deliver business benefits, whatever tools and technologies our clients use. Our people have skills and experience across a wide range of businesses, platforms and technologies, and we work with technology partners where needed to deliver complete business solutions.

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Customer Advocacy

When defining and embarking on an analytics journey, it can be challenging for executive stakeholders and senior managers to connect all of the parts of what is typically a complex puzzle and create a vision that can be used to secure internal support and funding. This service provides extensively experienced practitioners who can guide and coach senior stakeholders and sponsors as they shape the journey that will most effectively deliver to their organisational needs.

Analytic Project Management

Having a project manager who understands analytics and the challenges of connecting data to your analytical assets and business decisions is crucial to a successful project. This service provides an experienced analytics project manager to support your project and ensures they are supported by deeply experienced analytical consultants and delivery experts.

Model Build

The art and science of building models, whether ratings models (PD, LGD and EAD) or decision models (applications, behavioural or collections) requires technical skill, business understanding and experience. It is often an understanding of the business and how a portfolio is managed that drives a more predictive, technical outcome. Connected Analytics have deep skills in both rating models and decision models that can provide support to in-house teams.

Integration Services

Throughout the project lifecycle, technical tasks such as coding, unit testing, system testing, architecture, etc., need to be performed to create the systems and processes to support analytics. Typically, these tasks are performed by technology professionals with limited understanding of analytics and this can lead to rework, particularly around data and characteristic definitions. Integration of analytics is best performed by experienced technology professionals who also have knowledge of analytics and can better identify problems and test solutions.

Model Deployment

Once a model has been specified by the model-building team, it needs to be deployed into an environment where it can be efficiently executed and the modelling outcomes passed to a host system so they can be connected to business decisions. Having experienced technology professionals with expertise in analytics and model deployment can reduce effort and duration during the project lifecycle and increase the efficiency and sustainability of the models deployed.

Model Validation

All models in use should be subject to an on-going monitoring and validation programme. This may be at least annually for ratings models under AIRB, quarterly for high-volume and high-value decision models, such as mortgage originations models, or less frequent for other decision models. A validation will review periodic monitoring and other qualitative and quantitative measures to determine the on-going fitness of a model for the purpose for which it was intended.