Alvarez & Marsal’s Post

Modern digital banking journeys combined with cost-effective digital operations need to be enabled by new credit risk models. My colleagues Marius and Zeeshan share their thoughts on the challenges and opportunities in the industry. Dr. Zeeshan Mansoor Marius Messer

The traditional risk assessment model is no longer effective. Long-hour analysis, heavy human labor and costs. A future-proof bank is the one that leverages AI to streamline this process. #AI #banking #aibusiness

How to reduce financial modeling costs by 35% - A case study for a corporate bank 👇🏻 Businesses in the Banking sector always want to have a model for credit risk assessment that reduces the costs involved in the process. Here's how we solve the problem! #AI #Aibusiness #GenerativeAi #Aitech

Join the ongoing discussion on GenAI. Steve Bishop recently spoke to Banking Risk and Regulation about how GenAI risk intersects with operational risk and how ORX is supporting financial firms with this topic. Read the full article here: https://lnkd.in/gjHyhgbR 🔓 𝗠𝗲𝗺𝗯𝗲𝗿𝘀 𝗰𝗮𝗻 𝗴𝗲𝘁 𝗮𝗰𝗰𝗲𝘀𝘀 𝘁𝗼 𝗼𝘂𝗿 𝗚𝗲𝗻𝗔𝗜 𝗿𝗲𝗽𝗼𝗿𝘁 𝗵𝗲𝗿𝗲:  https://lnkd.in/e_Z8euS2 #ORX #ORXCyber #AI #Financialservices

Last chance to register for American Fintech Council's upcoming webinar on the Power of AI-Driven RegTech. SRA Watchtower's Edward Vincent will be joining this expert panel to talk about risk management, compliance, regulatory reporting and more in terms of AI and RegTech. Register here > https://lnkd.in/eHkFHA9b. #ai #FINANCIALSERVICES #Banking #RegTech #RiskManagement

The Finance Ministry on Thursday held a workshop for CEOs and MDs of 12 public sector banks and other financial institutions to provide them with insights into the best practices for AI adoption and risk mitigation in the banking sector. https://lnkd.in/dkDtahg9

On the future of IRB (internal rating based) models our expert group has recently published two articles on new developments in 1) internal model based supervision and 2) the field of IRB models. https://lnkd.in/eE6jXczW https://lnkd.in/e6ZCc6st - Key message is the need of simplifying the exitsing model landscapes. While immediately after Basel II, most of us were conviced that “more is better” i.e. banks should try to cover as much as possible of their credit exposure with internal models, this view has been revised with the insights of dozens of model investigations. - in particular for small portfolios and portfolios with limited data. - The second article also gives a glimpse on the difficulties and potential pitfalls of including Covid 19 period data series. On a sidenote, I am of the opinion, this is a theme being relevant to be considered also in a broader context beyond IRB - a core equation often forgotten in all currently overheated discussions on AI and fancy models in risk management: Biased data + great model = Greatly biased outcome.

Plain speak about what's what so far with AI, including the "reality stat" that only 6% of organisations have so far got to an agreed strategy. A good quick read courtesy of Richard Fayers and @Global Banking & Finance Review.

In this video, Craig Sanders with Moss Adams discusses: ➡ Liquidity Management ➡ Regulatory and Compliance Risk ➡ Fee Income Challenges ➡ Artificial Intelligence Oversight Watch now! https://lnkd.in/e9zyv7Ey #risk #regulation #AI #compliance #banking

💬 “A fear of “disrupting the status quo” is blocking innovation at mid-sized UK banks, a damning survey reveals.” Interesting insights about fear of change causing stagnation in business practices in the banking sector from John Crowley at Banking Risk and Regulation. Read the full article here: https://lnkd.in/euKznGTj #ProcessMining #AI #Innovation