Accelerator #1 Data assets management
Major Swiss Bank
Challenge
- Difficulties maintaining code and monitoring data health
- Making assumptions leading to incorrect outputs
- Need to reimplement existing pieces of software
- Big overhead to integrate new data sources for each use-case
Solution
- Trusted, opinionated and reliable code assets that define guidelines and enforce compliance
- Code modules that allow downstream users to consume and interpret data assets
Impact
- Reduced time to onboard new data assets
- Reduced human errors thanks to guideline enforcement
- Increased transparency about availability and content of data assets
- Ensured common understanding of the data model, allowing to scale data asset development efforts
How AI Assists Portfolio Managers in Gaining Market Intelligence
International Financial Institution
Democratizing Market Intelligence: A GenAI-powered Assistant helping portfolio managers to review market reports, provides an interface for interaction with preferred reports, enables targeted queries and cross-referencing
Challenge
- Portfolio managers today navigate a sea of financial market reports, requiring advanced tools to effectively extract relevant information from a high volume of reports and data received daily from multiple sources
- Cross-Referencing of Market Insights from Diverse Financial Institutions for Portfolio Managers
- Categorize reports based on their content and relevance to specific investment strategies
- Time spent poring over reports detracts from strategic activities like identifying emerging trends, conducting in-depth research, and formulating sophisticated investment strategies
Solution
- Developed a chatbot powered by Generative AI augmented with the latest available market reports
- Intuitive UI enabling targeted queries on selected reports and cross-referencing insights between reports
- The ETL pipeline was implemented to ingest and process the market reports
Business Impact
- Portfolio managers are able to customize their queries and ask specific questions, even referencing multiple reports if needed
- Centralized access: Portfolio managers can interact with their preferred market reports through a single interface
- Facilitates cross-referencing: Solution allows easy comparison of information from multiple reports
- Key insights are presented concisely summarised, alleviating the volume of reports
Data Platform Audit
Swiss Private Bank
Assessing current custom-made data platform to make recommendations on the best approach and create valuable insights for future platform strategy
Challenge
- Client wanted to assess current capabilities and maturity of their custom-made data platform
- Need to compare current setup to potential future alternatives
- Required an assessment to decide on future platform strategy and to investigate recurring issues raised by users
Solution
- Delivered platform assessment across 4 dimensions:
- data platform tooling and process capabilities
- data analytics and science platform strategy
- data driven use-cases
- platform development
- Assessed strengths & weaknesses in depth and developed recommendations for Data Platform team
Business Impact
- Increased awareness on strengths and weaknesses of custom-made platform in different application scenarios
- Recommendations for a hybrid approach: custom-made ingestion and off-the-shelf platform for Analytics capabilities
- Decision basis for future platform strategy
Data Platform Suitability Assessment
Swiss Financial Services
Compared two existing data platforms (Cloudera & Foundry) to determine the suitability of each solution and define a future platform strategy
Problem
- Leading Swiss Financial Services wanted to compare scope and maturity of two of their deployed Big Data platforms (Cloudera and Palantir Foundry)
- Assessment required for compliance reasons and to decide on future platform strategy
Solution
- Compared platforms across 5 dimensions:
– data management and governance
– data engineering
– analytics & science
– security
– platform openness - Assessed strengths & weaknesses in depth and developed recommendations for CDO
Impact
- Increased awareness on strengths and weaknesses of deployed platforms in different application scenarios
- CDO achieved buy-in of compliance department
- Established a good decision basis for future platform strategy initiatives
DWH Assessment
Swiss Cantonal Office
Assessed the data security maturity of a cantonal tax office’s data warehouse and proposed a recommendation roadmap to prepare for a data security audit
Problem
- Tax office developed a Data Warehouse 5 years ago to run short analyses
- Organic, unstructured growth of the DWH led to struggles with data security topics
- Needed a security and maturity assessment for upcoming audit and optimization initiative
Solution
- Leveraged the NIST cybersecurity framework, focusing on security maturity, data lifecycle, connectivity diagram, roles & responsibilities as part of the assessment.
- Developed forward-looking recommendations for data privacy and secure company/team topics
Business Impact
- Delivered a roadmap with timely recommendations, highlighting key risks and ways to reduce them.
- Stakeholders were well-informed and DWH prepared for the upcoming audit
Building an HR Data Science Use Case Roadmap
Swiss Private Bank
Identified and prioritized high-potential HR Data Science use cases resulting in Senior Leadership buy-in to embark on their AI journey with a clear roadmap.
Problem
- Client has embarked on an AI & Data Science journey but is lacking a clear approach to identity and implement high-potential use cases
- Limited knowledge about AI and its capabilities in Human Resources
- Interested in delivering quick-wins to prove value to HR Department and Senior Leadership
Solution
- Identified a long list of 33 potential HR use cases across the employee journey through research and interviews
- Conducted in-depth assessment of Top 6 high-potential use cases in terms of business impact and feasibility, summarised in a ranking
- Built roadmap of use cases with effort estimation and required infrastructure & data
Impact
- Delivered clear HR Data Science roadmap which resulted in Senior Leadership buy-in
- Prioritized list of use cases with highest impact and feasibility was piloted and industrialized which successfully delivered quick-wins and proved value in continuing the HR Data Science journey
Early Warning Indicators
Major Swiss Bank
Identifying clients that are most likely to have financial problems through an automatic model based on warning indicators to alert credit officers earlier
Challenge
- Credit officers need to assess and manage financial risk for their respective portfolios
- The amount of data collected each day by the risk department and its velocity make it hard to properly monitor and manage risks for every client
Solution
- Help the credit officers to identify and focus on clients that are more likely to have financial problems in the future
- Leveraged Foundry as a data platform and defined early warning indicators – rule base alerts triggered by specific events
- Unit8 implemented those alerts on parameters such as late leasing payments or overdrafts
Business Impact
- Significant simplification of the assessment and monitoring that credit officers need to conduct
- Clear email based alerts that can be easily and quickly reviewed
Client Surveillance
Major Swiss Bank
Identifying clients that are most likely to have financial problems through an automatic model based on warning indicators to alert credit officers earlier
Challenge
- Regulations require the client to setup surveillance for money laundering and illegal activities
- Disparate data sources and formats, and varying regulations between countries
- Inability to monitor client behaviour to spot illegal activities
Solution
- Leveraging a previous project Unit8 conducted (Single Client View), built a generic framework enabling data scientists to easily define surveillance scenarios to monitor potential high-risk client activities
- Pipeline specifically designed to scale to millions of customers tracking billions of equity positions globally
Business Impact
- Greatly reduced amount of time needed to define surveillance scenarios, from weeks to minutes
- Reduced resources required and build-time of pipelines by more than 50%
- Improved reliability of scenarios
- Decreased manpower necessary to conduct surveillance audit by a factor of 20
Single Client ViewDashboard
Major Swiss Bank
Creating a single client view for an international Swiss bank allowing them to track and compute total risk exposure, and meet AML compliance regulations
Challenge
- Siloed data across multiple systems
- Inability to calculate risk exposure
- Lack of unified view of their clients
- Limited ability to meet compliance regulations
- Sub-optimal conditions to apply proper AML
Solution
- Aggregated, cross-referenced and combined data from hundreds of disparate data sources
- Used ML to automatically surface high-risk clients
- Implemented a scalable solution to account for future needs
Business Impact
- Achieved single client view, increasing visibility
- Able to calculate overall risk exposure
- Compliance with AML regulations
- Already stopped previously undetected terrorism-financing activities
Collateral Insight
Major Swiss Bank
Creating a new data pipeline for collateral risk calculations to improve the quality of data information and reporting for end users
Challenge
- Risk calculations on collaterals provided daily to end-users through dashboard
- Need to leverage this risk calculation data model for reporting purposes
- Difficult to identify which data would be required for reporting, and to accurately provide it through previously-built pipeline that wasn’t sustainable
Solution
- Initial discussion to fully understand data sources and existing data flows
- Created new pipeline to extend the already existing data model by including specific information
- Identifying- and providing solutions to issues in the current codebase which introduce data quality issues
- Provide guidelines to prevent similar issues from reoccurring
Business Impact
- Improved data quality of the reports by onboarding the data on the main data processing platform through the newly built pipeline
- Enabled client team to improve and learn by giving tips and providing guidelines
- Reduced disk spillage per TB of data from 50GB to less than 100MB
Portfolio Monitoring and Reporting
Major Swiss Bank
Refactoring an entire codebase making the pipeline run time 7x faster, allowing quicker new feature development, and increasing data quality for analysis
Challenge
- The “Portfolio Monitoring and Reporting” project provides multiple dashboard for risk managers to assess their risk
- Over several years of development, the codebase has become entangled and slow which was blocking the delivery of new features
Solution
- Analysed, simplified and refactored the entire codebase to better future-proof the project
- Solution leveraged was the Unified Foundry Ontology (UFO) that we had previously developed
- Pure foundry solution combined with Unit8’s programming expertise and best practices
Business Impact
- Increased code quality and resolved bugs that accounted for millions of CHF in exposure reporting deviations
- Reduction of pipeline execution time from 10h to 90 min, resulting in fresher data available for analysis
- Allowed smoother onboarding of 200+ users
- Established scrum and coding best practices
Analytics Platform Setup on AWS
Trading Company
Aggregating all marketing data into a single view matching leads to customers to gain a better understanding of marketing campaigns performance and costs
Challenge
- CRM data spread across entities with little to no aggregation at a group, vertical or customer level
- Lack of data integration meant no overall visibility on factors influencing consumer behaviour
- Inability to check marketing investment effectiveness in customer acquisition and retention
Solution
- Created a data pipeline in AWS to aggregate al marketing campaigns, leads, and customer data into a single source of truth (Data Mart) on AWS
- Pipeline cleans data and builds a unified view matching leads with customers
Business Impact
- KPI tracking per advertising platform, campaign and ad spot (e.g. cost per lead, transformation rate, ROI, etc.)
- Transition to a data driven marketing plan rather than based on “gut-feeling” and beliefs
Exploratory Knowledge Graph
Swiss Private Bank
Building up a Neo4j Graph solution to help different divisions map relationships and interactions between people, companies, accounts and assets
Challenge
- Talend ETL and SQL queries resulted in high manual overhead and could not properly maintain relationships between different parties and accounts
- Looking for a more business friendly interface for their bankers
Solution
- Built up a Neo4j environment
- Created a necessary data schema and ingested required datasets
- Leveraged the newly created Neo4j environment to create two required views:
Party
Account
Business Impact
- Self service interface with granular access rules to allow different departments (wealth management, risk, fraud, etc.) to perform their own queries
- Ensured regulatory compliance regarding particular sanctions
Rogue Traders Monitoring
Major Swiss Bank
Developing an ML model to identify potential rogue traders and flag them to minimise risk of financial losses and lower need for regulatory cash reserves
Challenge
- Inability to monitor and identify traders whose behaviour differs from what is expected, resulting in potential monetary and reputational risks for the client
Solution
- Integrated trading data from several sources into a single platform
Deployed ML techniques to identify potential rogue traders based on their trading behaviour - Configured an alerting system to flag traders with an elevated risk of rogue trading
Impact
- Able to quickly identify risky traders based on their trading activities, which would have been impossible to do manually
- Minimised rogue trading risk and potential financial losses, lowering the need for regulatory cash reserves
Platform Performance Optimisation
Major Swiss Bank
Optimising platform performance with a set of tools and best-practices combined with coaching, resulting in lower costs and smoother user experience
Challenge
- Platform adoption skyrocketed and rate of increase is higher than what new hardware added is capable of handling
- Usage expected to keep climbing as more projects are being onboarded, leading to further cost increase and performance degradation
Solution
- Established performance metrics baseline
- Coached client’s engineers to enable them to improve platform performance
- Created tooling and reports to pinpoint performance problems and allow self-service improvements
Impact
- Reduction in new hardware addition and maintenance costs
- Increase in platform performance resulting in smoother user experience
Commodity Trade Finance (CTF) Dashboard
Major Swiss Bank
Creating a dashboard unifying all trading information resulting in a more holistic understanding for credit risk officers and substantial risk reduction
Challenge
- Credit risk officers struggle to understand precisely who they are trading with, what kind of goods are traded, and what are the exposure concentrations
Solution
- Created a dashboard presenting an interactive view of the CTF portfolio and its clients to mitigate risks and recognize business opportunities
- Entity resolution (based on free text sources) to provide a unified view of all external parties involved in the transactions
Impact
- More holistic understanding of CTF business across departments
- Substantial risk reduction through better understanding of exposures
Client Surveillance
Large Swiss bank
Defining and implementing a surveillance framework to identify illegal client behaviour resulting in greatly improved ability to meet surveillance requirements
Challenge
- Regulations require the client to setup surveillance for money laundering and illegal activities
- Disparate data sources, and diversity in regulations between countries
- Inability to monitor client behaviour to spot illegal activities
Solution
- Leveraging a previous project Unit8 conducted (Single Client View), built a generic framework enabling data scientists to easily define surveillance scenarios to monitor potential high-risk client activities
Impact
- Greatly reduced amount of time needed to define surveillance scenarios, from weeks to minutes
- Reduced resources required and build-time of pipelines by more than 50%
- Improved reliability of scenarios
Residual value prediction
German automotive
Problem
- Car manufacturer holds large global leasing portfolio that has to be periodically evaluated
- Current valuation predictions are inaccurate
Solution
- Based on a large volume of past transactions (12 years) and cars parameters (model, mileage, options), etc. predict accurately the residual value of the car
Impact
- Accuracy of the valuation improved by $100M’s (from large overall base value)
Churn prevention
Major Swiss bank
Problem
- Significant churn in existing customer base which limits overall growth ambitions in saturated Swiss market
- Large number of customer data available, which was not systematically analysed
- Client advisors often surprised if customers leave
Solution
- Early warning system was created based on a machine learning model to identify customers at risk of leaving or withdrawing a large part of their assets (attrition risk)
- System based on regular monitoring of client behaviour (e.g. transaction behaviour, the intensity of engagement) to predict the attrition risk
- A customer group specific retention approach was developed to pro-actively contact customers with high attrition risk
Impact
- It could be proven that the machine learning model identifies the right customers at risk
- Retention approach has proven to be highly effective since the churn rate of customers at risk could be significantly reduced
- Client experienced strong business benefits, since revenue outflows due to customer churn could be reduced
Financial health watchlist
Swiss Financial Institution
Developing a centralised solvency and risk assessment model to create risk exposure reports automatically and improve data quality
Challenge
- Difficulty to predict total exposure to financial losses resulting from companies at risk of becoming insolvent
- Current risk reports are generated manually and data quality is not guaranteed
Solution
- Central gathering and processing of the relevant partner data allowing for central risk modelling and data quality checks
- Automatic creation of monthly risk reports based on the curated data
Impact
- Improved risk management capabilities through information centralisation and standardisation
- Improvement in data quality and report generation
- Possibility to create reports dynamically to visualise more aspects than before
User behaviour monitoring
Major Swiss bank
Problem
- Impared visibility of user activity and behaviour allows for malicious behaviour to be undetected for a long period of time
- Compliance group in a global private bank decides to monitor user activity on the central data platform
Solution
- Introduction of dynamic altering and anomaly detection system including enhanced signal information via integration of new sources of data (HR data, badge swipes, VPN logs, … )
Impact
- Greatly improved security, audit and monitoring capabilities of the platform team
- Decreased risk of malicious behaviour remaining undetected
Financial transactions monitoring
Global Swiss Pharma producer
Problem
- Customer struggled with detecting anomalous financial transactions – the current process is labour intense and error prone due to mass volume of the transactions and amount of false positive alerts
Solution
- Unsupervised machine learning system to automatically flag anomalous transactions together with prioritisation based on severity and an explanation why a given transaction can be an anomaly
Impact
- Lower need for manual interaction
- More accurate transactions monitoring
- Quicker time to act on an alert
Single Client View
International Swiss Bank
Creating a single client view for an international Swiss bank allowing them to track and compute total risk exposure, and meet compliance regulations
Challenge
- Siloed data across multiple systems
- Inability to calculate risk exposure
- Limited ability to meet compliance regulations
- Sub-optimal conditions to apply proper AML
Solution
- Aggregated, cross-referenced and combined data from hundreds of disparate data sources
- Used ML to automatically surface high-risk clients
- Implemented a scalable solution to account for future needs
Impact
- Achieved single client view, increasing visibility
- Able to calculate overall risk exposure
- Compliance regulations can be met