Use AI to revolutionize banks' risk management and decision-making
Join our challenge to revolutionize banks' risk management! We are seeking innovative solutions that integrate Large Language Models with traditional quantitative analytics to predict financial risks with greater accuracy. Unleash your creativity and redefine banking risk assessment!
Who can participate?
Start-ups, (technology) companies, researchers, labs, newly founded tech teams and all other AI innovators
#AIRiskPrediction #FinancialAnalytics #AIinBanking
✅ Completed 🏁 Winner 51nodes & AssetFloow
🏆 Prize Funded co-creation, strategic partnerships & long-term integration
🌎 Scope Global
❓Questions Feel free to join our Q&A Calls
👥 Looking for a team? Join our Team Matching Channel
Below you will find some examples of information, i.e. publications from BayernLBs research department. They are an initial overview of publications that may help you gain an understanding of the output the tool should support to generate. Of course, this is only non-binding information and not investment recommendations for private investors.
- Perspectives (German)/ Perspectives (English): a monthly publication that looks at the most important events and how they influence the forecasts of BayernLB's Economics Department
- Blickpunkt EZB (Focus on the ECB)/ Blickpunkt FED (Focus on the Fed): These are published after the central bank meetings to report on the results
- Blickpunkt Immobilien (Focus Real Estate): Update on events in the real estate market
- Sektoranalyse (Sector analysis): Irregular reports on economic/technological news in specific sectors
- Länderanalyse (Country analysis): Annual update and risk assessment on specific economies (political, economic, financial conditions)
- Morning Notes: Daily update of financial market data; mainly intended to show which indicators BayernLB Research is following
- Rates & SSA Report: Analysis of movements on the bond markets
- Credit Chartbook: Several charts on current events in the corporate credit market
In the following you will find some sources that can be used as inspiration for such a tool. Note: This list is NOT exhaustive but serves as a starting point for your consideration!
The items on the list below should give some inspiration, guideline which quantitative data could be used for this challenge. It is neither expected that all items below should be included, nor is the list complete.
Equity/ Stock Market
- Euro Stoxx 50
- DAX
- Dow Jones
- S&P 500
- Nikkei
- FTSE
FX-Rates
USD vs. EUR, CHF, JPY, GBP.
Interest Rates
- Key ECB rates: Key ECB interest rates (europa.eu)
- Euribor 3M, 6M
- Swapcurves
- Yields of Government Bonds
Credit Indices
- iTraxx FIs 5Y
- iTraxx Corporates (US, EU) 5Y
Commodity Prices
- Oil WTI
- Gold
- Bitcoin
- Energy Prices
Macroeconomic Data
GDP, Inflation, Unemployment Rate, etc. for various countries.
- ECB Data Portal: Macroeconomic and sectoral indicators | ECB Data Portal (europa.eu)
- OECD Main Economic Indicators (MEI) - OECD
- Top 10 U.S. Economic Indicators (investopedia.com)
- World Bank Data: Indicators | Data (worldbank.org)
Real Estate Market
- The Economist house-price indices
- System of indicators for the German residential property market | Deutsche Bundesbank
- Prices - Housing prices - OECD Data
- Global Real Estate Transparency Index 2022 (jll.de)
For qualitative data written news article from high quality journals, newspapers should be used, such as:
- TIME Magazine
- Newsweek Magazine
- Politico Magazine
- New York Times
- Wall Street Journal
- Washington Post
- BBC
- The Economist
- Financial Times
- FORBES magazine
- Bloomberg BusinessWeek
- The Guardian
- In Germany: Süddeutsche Zeitung, Handelsblatt, FAZ, Zeit
It is not encouraged to use social media news data like X/Twitter, Facebook, Instagram.