SET Training - Banking and Fintech

Despite massive investments and hype, AI hasn't yet delivered on its promised transformative impact. Experts believe it will take much longer than expected to see significant changes in daily life and the economy. Key issues: Overhyped Expectations Massive investments: Tech giants and startups are pouring billions into AI research, development, and infrastructure. This includes acquiring AI startups, building specialized AI chips, and constructing massive data centers. Inflated valuations: The stock market has rewarded companies that integrate AI into their business plans, leading to inflated valuations and a fear of missing out (FOMO) among investors. Unrealistic timelines: There's a tendency to overestimate the speed at which AI will revolutionize industries and daily life, leading to unrealistic expectations about its near-term impact. Limited Practical Applications Narrow intelligence: While AI excels at specific tasks like image recognition and language translation, it...

The Financial Action Task Force (FATF), originally created to combat money laundering, has been increasingly weaponized by authoritarian regimes to silence dissent and suppress opposition. By exploiting the vaguely worded FATF standards, autocrats can freeze assets, harass activists, and even imprison critics under the guise of fighting financial crime. Key tactics employed by these regimes include: Data collection: Governments amass financial information on citizens and opposition figures, often using it to build cases against them. Asset freezing: Banks, fearing repercussions, comply with government requests to freeze accounts, leaving individuals financially crippled. Politically motivated arrests: Critics are detained on spurious financial crime charges, with lengthy pre-trial detentions becoming commonplace. Targeting exiles: Authoritarian states collaborate to pressure Western countries into freezing assets and extraditing dissidents living abroad. While the FATF has made eff...

Artificial intelligence (AI) is transforming the banking industry, not just in customer-facing applications but also behind the scenes in operational risk management. While traditional methods focus on compliance and rule-based systems, AI offers a new frontier for proactive risk mitigation and intelligent response. This article explores five unconventional approaches that leverage AI's power to create a more dynamic and comprehensive risk management strategy: 1. The Conversational Comrade: AI Chatbots for Incident Response Imagine a tireless assistant, always available to guide staff through the initial stages of a security incident. AI-powered chatbots can be trained on historical data, regulations, and best practices to become valuable assets during critical moments. These chatbots can triage incoming reports, categorize them by severity, and offer step-by-step guidance on initial response protocols. Furthermore, they can facilitate root cause analysis by asking focused question...

Every organization, from a bustling startup to a well-established corporation, navigates a sea of uncertainty. This uncertainty manifests as risk, the potential for events to disrupt operations and impact success. But not all risks are created equal. Understanding the difference between operational risk and strategic risk is crucial for effective risk management. Operational Risk: The Engine Room Imagine the engine room of a ship. Here, a network of pipes, valves, and machinery keeps the vessel moving. Operational risks are like leaks, malfunctions, or human error in the engine room. They arise from the day-to-day functions of a business and can disrupt its core operations. Examples: System failures (IT outages, power disruptions) Human error (accidents, negligence) Compliance issues (regulatory violations) Third-party disruptions (supplier delays, transportation problems) Natural disasters (floods, fires) Operational risks tend to be more frequent but have a lower impact on the organi...

Artificial intelligence (AI) is revolutionizing businesses, but along with the benefits come significant risks. Here are 8 top risks to consider before diving into the world of AI: 1. Biased Algorithms, Unequal Outcomes: AI systems learn from data, and biased data leads to biased algorithms. This can perpetuate discrimination in areas like hiring, loan approvals, or criminal justice. How it Happens: Biased training data can reflect societal prejudices or incomplete information. For example, an AI resume screener trained on past hires might favor resumes with keywords used by a specific demographic. Mitigate it: Scrutinize training data for bias, ensure diversity in data sets, and implement human oversight in critical decision-making processes. Tell-Tale Signs: Unexplained disparities in AI outputs across different demographics. 2. Job Automation Anxiety: AI can automate tasks, leading to job displacement. While new jobs will be created, there's a fear of a skills gap leaving so...