Minimizing non-performing loans (NPLs) using an effective AI-powered loan agent can be achieved through several strategies. These strategies revolve around leveraging AI's ability to process large amounts of data, predict future borrower behavior and take proactive measures to manage loan performance. 1. Enhanced Credit Scoring and Risk Assessment

There are several ways to mitigate asymmetries in banking caused by the use of Artificial Intelligence (AI). As AI is increasingly integrated into banking systems, it introduces risks of power imbalances, where large institutions and firms with access to more data and advanced technology gain an advantage over consumers and

Automatable Credit Scoring SIPOC process: Data flow: Input(x) > Process algorithm(m+b) > Output(y) 1.      Establish supervised learning model 2.      Train model using historical data (x) to predict creditworthiness (y) Basic equation: Credit Score (y) = m*(Financial History) + b for iterative optimization of the data fitting algorithm

Actuaries play a critical role in ensuring the financial stability and reliability of insurance companies by calculating reserves, assessing risks, and guiding financial strategies. However, several potential risks arise from their work, which can impact both insurance firms and policyholders. Potential actuarial risks to be mitigated: 1. Inaccurate Reserve Calculations

Warren Buffett’s investment strategy, often referred to as value investing, revolves around several core principles. Based on information in the book "Warren Buffett and the Interpretation of Financial Statements" by Mary Buffett and David Clark, the essence of Warren Buffett’s approach can be distilled into the

The SIPOC process notation is considered a "master process pattern" because it provides a comprehensive and structured AllinOne framework for understanding and modeling and last but not least analyzing processes. This approach is applicable universally to integral process & data contexts as exemplified by the sensory processes of

1. Transparency Explainable AI provides transparency into how decisions are made by algorithms. When users understand the rationale behind an AI system’s output, it demystifies the process and helps build confidence in its results. Transparency allows stakeholders to see the inner workings of AI models, making it easier to

[ AI = f(Comprehensive Financial Data, Advanced Machine Learning Algorithms) + Identification of Undervalued Assets, Market Trends Analysis - Risk Assessment and Mitigation Strategies ] Data: The comprehensive financial data utilized in the AI wealth management project includes historical market performance, individual investment preferences, risk tolerance levels, macroeconomic indicators, real-time market updates and

Opportunities & risks associated with AI projects arise from the project's process context and its impact on stakeholders. 1. Process Context * Data Quality and Availability: The process context, including data sources, preprocessing methods, feature engineering and model selection, significantly impacts the quality and performance of AI algorithms. * Algorithm

A cobot or collaborative robot, also known as a companion robot, is a robot intended for direct human-robot interaction within a shared space or where humans and robots are in close proximity. My design thinking example is about a cobot assisting in the real-time visual inspection in manufacturing done for

SIPOC process mapping can play a crucial role in helping stakeholders identify conceivable risks of non-compliance of AI projects with the EU AI Act by providing a structured framework to analyze the process flow, dependencies and data handling practices. 1. Supplier Identification (S) * Risk Identification: Stakeholders can identify potential risks

What’s the relevance and value of data without process context ? Does data need process context to be relevant and of value to stakeholders ? Do risks depend on how processes are deployed ? Are process maps a prerequisite for any risk assessment of AI systems, product & services development & deployment

The ProcessHorizon web app for AllinOne data & process modeling in SIPOCe notation with instantly auto generated visual process maps as a catalyst for developers, customers and users as well as for organizations and companies. SIPOC data & process flow from source to destination:                                           Supplier > Input > PROCESS >

A stakeholder value model is a framework used by organizations to consider the interests and contributions of all stakeholders involved in or affected by their operations. Implementing a stakeholder value model requires a shift in mindset from a purely profit-driven approach to a more holistic view of business success. Companies

The smart ProcessHorizon web app for Business Professionals & Subject Matter Experts & Domain Experts ProcessHorizon is the smart app for AllinOne process- & data modeling in stakeholder oriented SIPOC notation with auto visual process mapping in support of quality & risk management & compliance as well as governance of

A bank's multi-stakeholder dilemma must be addressed in business model design of how to balance money supply and demand in the best interest of lenders and borrowers as well as of other stakeholders.     Based on three examples I will demonstrate the stakeholder dilemma in total value creation vs.

The integration of the ESG model, i.e. enviromental, social and governancecriteria into a company's business model and process model can be a differentiator for example in the electric car marketaddressing the expectations of environmentally conscious prospective buyers. MP1 Environmental processes PR1 Manufacture vehicle parts using sustainable materials

Energy literacy refers to the understanding and knowledge that individuals possess about energy-related concepts, sources, uses, and impacts. 1. Basic Energy Concepts: Energy literacy involves understanding fundamental concepts such as energy forms (e.g. kinetic, potential, thermal), energy sources (e.g. fossil fuels, renewable energy), energy units (e.g. joules,

Quality is vital for AI model development as well as for deployment of AI products and services in a process context. AI model development depends on data quality whereas AI systems deployment is dependent on process design & process quality. AI model development and AI product and services deployment must

To anyone interested in banking management and governance, risk & compliance (GRC) from a stakeholder point of view, I herewith provide a list of my ProcessHorizon blog posts from March 2023 until May 2024. Real-time monitoring of transactional data for AI-driven banks https://blog.processhorizon.com/ghost/#/editor/post/663dddd038c9865bc20e7063

Financial engineering is a multidisciplinary field that applies mathematical, statistical and computational techniques to solve problems in finance. It involves designing and implementing innovative financial instruments, strategies, and processes to achieve specific financial goals, such as managing risk, optimizing investment portfolios and enhancing returns. 1. Risk Management: Developing methods to

A personal cash flow statement provides an overview of the cash inflows and outflows over a specific period, usually monthly or annually. It helps individuals understand how much cash is being generated and where it is being spent, aiding in budgeting and financial planning. Cash Inflows 1. Salary and Wages

A personal life income statement, also known as a personal income and expense statement, summarizes an individual's financial performance over a specific period (usually monthly or annually). It includes revenues (income) and costs (expenses). Revenues (Income) 1. Salary and Wages * Gross salary from employment * Bonuses * Overtime pay * Commissions

A personal life balance sheet is a financial statement that summarizes an individual's financial position at a given point in time. It includes three main components: assets, liabilities and equity. Assets (savings & property) 1. Current Assets * Cash and Cash Equivalents: * Cash on hand * Checking accounts * Savings accounts

Eine Einheitskrankenkasse mit einheitlichen Prozessen bietet zahlreiche Potenziale für den Einsatz von Künstlicher Intelligenz (KI), die sowohl die Effizienz des Systems erhöhen als auch die Qualität der Gesundheitsversorgung verbessern können. 1. Datenanalyse und Prävention * Großflächige Gesundheitsdatenanalyse: KI kann große Mengen an Gesundheitsdaten analysieren, um Muster und Trends zu erkennen. Diese