Wie wir unseren Kunden helfen
Risk | Analytics & Modelling
- Developing regulatory compliant risk models with a current focus on IRB and IFRS 9 models, but also including risk models for other purposes and parts of the risk management value chain, such as decisioning models, credit portfolio models, stress testing solutions, provisioning models, etc.
- Validating models: covering processes and governance, data and methodology to assure the adequacy of the result. Conducting validation of retail, corporate, sovereign, counter party credit risk and specialised lending credit rating models. Experience also in cost-efficient off-shore validation. In addition, set-up of validation frameworks, tools and templates, as well as automating of model validation.
- Data analytics: including database design, data infrastructure and process mapping; extracting, merging and preparing large data sets. TNP also provides support in the development of BCBS 239 compliant governance and processes with regard to risk management data aggregation and reporting for risk and beyond.
- Model risk: includes creating a model risk management framework that validates models, allocates roles and responsibilities and coordinates tasks among other elements. TNP supports clients assessing model risk, typically being driven by the likelihood of a model being erroneous, on the one hand, and the materiality of a model, on the other hand.
- In cooperation with The Analytics Boutique, TNP offers a model risk management and workflow tool, which is a web-based and integrated solution for model risk assessment, model risk reporting, management workflow and management of the model lifecycle.
- Machine learning: TNP can assist in preparing machine learning platforms, processes, policy standards and frameworks, as well as in developing machine learning enhanced predictive models and validating these. Areas of adoption of machine learning techniques include regulatory credit risk modelling, financial crime risk management, customer lifetime value management, life and non-life insurance.
- In cooperation with The Analytics Boutique TNP offers a machine learning for credit analytics tool, which includes generalised linear models, decision trees and state-of-the art machine learning algorithms for predictive analytics.
Risk | Balance Sheet Management
- Organisational design: Configuration of a modern, integrated finance and risk function, definition of roles & responsibilities at various levels and interfaces to other functions
- Risk profile management: Risk appetite framework definition and cascading, risk identification and materiality assessment, stress testing, limit management, risk MIS, portfolio management
- Integrated financial resources management (IFRM): Fully integrated and dynamic forecasting of B/S, P&L and key metrics under various macro-economic and idiosyncratic scenarios
- Active capital, liquidity and balance sheet management
- Optimisation of balance sheet structure and funding model
- Risk measurement: Credit, market, operational, business, ESG, insurance and liquidity risks; non-financial risk management frameworks
- Pricing and performance management based on economic value, regulatory and economic capital, incl. decision support tools, value-based MIS, incentive systems
- Strategic risk management: Risk aggregation and monitoring, portfolio management (incl. concentration risk)
- Credit processes: End-to-end process review, re-design, optimisation and automation including pricing, risk monitoring, structuring and workout
- Regulatory compliance and beyond: ICAAP, ILAAP, Recovery Planning - gap-analysis, framework review and validation of quantification methodologies, enhancement, document submission, preparation for and support in on-site inspections
- Tools: IFRM tools, scenario analysis and forecasting tools, credit portfolio models, model risk management tools, operational risk quantification and stress testing, pricing engines for retail and wholesale products
Finance (Operations and Cost Management)
- Cost-efficiencies: Applying deep dive methodologies and predictive analytics to create efficiencies and improve success rate across different business objectives (revenue, cost, market share, etc.)
- Process optimisation: End-to-end process review, streamlining and optimising processes by reducing the monthly closure timelines, automating monthly reporting activities and developing dynamic and interactive reports
- Planning & forecasting: Building customised planning, forecasting and budgeting tools – standalone or integrated in web-based platform with the ability to stress the organisation’s income statement, balance sheet and capital
- Target Operating Model: Reviewing Finance Taxonomy, Finance structure and rightsizing the Finance function, based on benchmarks, process and activity related efficiencies
- Strategic planning & target setting, forecasting capabilities and analytics underpinning strategy development
- Linking of business, risk and capital strategy
- Integration of new risk types and business opportunities (e.g. ESG, model risk) into business and risk strategies; adjustment of RAS and risk-return frameworks
- Development of strategies for asset growth incl. assessment of strategic fit, quantitative analyses, business cases development/challenge, loan-book due-diligence, capabilities required and resources
- Market-entry and expansion strategies incl. specific markets like African countries
- In Retail and Wholesale Business: Product / Segment / Client growth strategies, Branch network optimisation, Revenue optimisation
- Development of function and/or risk specific strategies: Funding strategy, Credit risk strategy, Market risk strategy, FX strategy, Sustainability strategy, etc.
- Establishing successful partnerships: Fintechs scan, introductions, exploration of potential for collaboration and design of an effective collaboration mode
- TOM redesign to support strategy implementation
- Execution support: PMO-role, drive of specific initiatives, “hands-on” support in strategy implementation
- Post-implementation review
- Defining ESG vision, linking “sustainability” strategy to business and risk strategy
- Integrating ESG into Risk Appetite and strategic/business planning
- Establishing a fit-for-purpose ESG governance framework: embedding ESG in organisational structure, defining TOM, roles, responsibilities, interfaces between Risk, Finance, Businesses, Investor Relations, “Climate Expert Group(s)”, defining ESG-related reporting framework
- Improving monitoring: Setting-up monitoring framework for initiatives (KPIs, KRIs) and overall performance measurement (to achieve ESG-related strategic objectives)
- Integrating ESG in credit processes and loan origination to (1) assess impact on borrower’s creditworthiness and (2) design fit-for-purpose origination and monitoring process for “green” loans and/or sustainability-linked products
- Integrating ESG risks into ERM (e.g. ICAAP) including risk identification and materiality assessment, portfolio/sector “heat maps”, climate-related scenario analyses and stress testing, mapping of transversal ESG risks into prudential risk taxonomy
- Assessing impact of climate-risks (physical and transition) on loan portfolios and/or own operations
- Integrating ESG risks into risk ratings and pricing
- Enhancing ESG disclosure incl. benchmarking against peers, best practice and considering the variety of voluntarily and mandatory disclosure requirements (TCFD, SASB, GRI, PRI, etc.); set-up of processes and tools to support report generation
- Setting-up ESG data framework and data base including identification of most appropriate data sources