The SupTech Launchpad is an accelerator for financial authorities and technology vendors to co-create and deploy cutting-edge, scalable suptech applications. To facilitate and de-risk this collaboration, our team helps detail the technical specifications, designs and implements agile procurement of the vendors, and provides project management support and hands-on technical assistance including security testing.
Through the Launchpad competitions, vendors are awarded the funds to develop and test working prototype solutions in partnership with the agencies.
If you are a vendor, by joining the Lab’s Launchpad you will also:
- Receive tailored coaching
- Be invited to the Lab’s pitch day to connect with funders and to a demo day to present their products to potential clients
- Be listed in the Lab’s online Vendor Database.
- Be mentioned in a case study published by the University of Cambridge to share lessons from the project
- Engage with the suptech community through the Lab’s hackathons and techsprints
- Be introduced to the global community of regulators and supervisors, investors, academics and development partners that are collaborating with the Cambridge SupTech Lab during other events hosted by the Cambridge Centre for Alternative Finance (CCAF).
If you are a financial authority interested in prototyping new suptech applications through the Launchpad, you can do so by either joining our CB&E programmes or our Technical Assistance. The SupTech Launchpad largely builds on the experience of the RegTech for Regulators Accelerator (R2A), which has successfully developed ground-breaking solutions introducing an agile approach to the collaboration between financial authorities and technologists.
working Prototypes for consumer protection supervision
FINANCIAL CONSUMER PROTECTION SUITE WITH WEB SCRAPER AND ML-BASED ANALYSIS
Financial authorities: Bangko Sentral ng Pilipinas (Central Bank of the Philippines) and Securities and Exchange Commissions of the Philippines
Vendor: Winnow Technologies
Sponsor: The Bill & Melinda Gates Foundation
This working prototype application enables financial authorities to collect and process consumer protection data from web and social media channels, thereby extending their consumer protection data collection capabilities and complementing the ability for customers of financial services to raise explicit complaints brought up in prior chatbot deployments.
It is an advanced analytics tool capable of processing streams of web and social media channels and linking with entities and trends in historical complaints data, using machine learning (ML) to provide a comprehensive view of the market in the interest of consumer protection initiatives for two financial authorities.
- Democratise financial consumer protection making available to users a new channel accessible through any mobile device.
- Filter the number of inquiries and complaint tickets that the supervisors need to manage.
- Reduce the time to process and resolve the complaints.
- Increase consumer literacy as users can more easily access information on financial services and products pushed by the authorities, thus make faster and well-informed decisions on products and services offered by financial institutions.
- Increase customers satisfaction on the complaint-handling mechanism, easily accessible status updates, improved resolution, fast turn-around time. In turn, this increases user’s trust in the formal financial sector.
NEXT-GENERATION AI-POWERED CHATBOT SUPPORTED COMPLAINTS MANAGEMENT SYSTEM
Financial authorities: Otoritas Jasa Keuangan (Financial Services Authority of Indonesia) and Bank of Ghana
Vendor: Proto.io and Winnow Technologies
Sponsor: Asian Development Bank and The Bill & Melinda Gates Foundation
This working prototype application augments existing chatbot deployments by providing an advanced analytics interface, powered by a data warehouse to centrally store data from complaints sources and other collection channels, and enable cross-silo actionability by supervisors.
These chatbot upgrades bring natural language processing (NLP) and other artificial intelligence technologies into the collection process for financial authorities in two countries, along with a data warehouse and dashboard solution that draws from historical complaints data to surface trends that can be useful across departments.
- Integrate market conduct perspective in the prudential supervision framework.
- Leverage the data collected from the user to ensure the complaint is solved.
- Extract insights to assess financial service providers’ compliance with market conduct regulation.
- Extract insights to enhance financial inclusion policies and market conduct regulation.
- Reduce cost and time spent on handling customers’ queries and complaints.
- Handle large volume of queries and complaints simultaneously.
- Automate data processing enabling easy tracking of complaints and improve resolution and customer experience with limited supervisory resources.
FINANCIAL MARKET MONITORING VIA SOCIAL MEDIA AND WEB EXTRACTION
Financial authority: Superintendencia de Banca, Seguros y Administradoras Privadas de Fondos de Pensiones of Peru
Vendor: Financial Network Analytics (FNA)
Contract value: $100,000
Sponsor: The Bill & Melinda Gates Foundation
This working prototype application introduces advanced monitoring tools via social media and other channels, building on initial efforts already in place at the agency. When an issue relating to a supervised entity or activity is raised and resolved via a consumer complaint, inspection, or otherwise, that is not always the end of the story. Further monitoring ensures the issue remains resolved.
These advanced market monitoring tools extend the existing capability of the authority, going beyond basic sentiment analysis to surface trends, anomalies and other patterns in the data that is relevant to monitoring of entities and activities flagged through other processes.
- Unlock better risk management: social media monitoring provides real-time information about market conditions and emerging consumer risks, allowing the agency to make informed decisions and manage risk effectively.
- Bridge the gap between reactive response and preventive action with proactive monitoring to ensure potential risks are identified, analysed, and acted upon before they escalate.
- Constant real-time updates about the general population’s sentiment, specific products, issues or entities enables financial leaders to predict potential misconduct and timely intervene (e.g., through on-site examinations) when risks are greater or more imminent.
- Continuous influx of data provides early warning signals of potential financial misbehaviour.
- Choose vendor selection model that best fits project’s need
- Vendor selection through global competition
- Vendor due diligence and contracting
- Use the “lean” approach to accelerate testing and development
- Apply “rapid learnings” from each iteration to progressively refine the project
- Frequent iterations with checks-in with supervisory agency and course corrections
- Prototype tested
- Capacity building for supervisory agency to maintain the application (if required)
- Implementation of change management plan
Web-Based Market Monitoring
Developed in collaboration with Superintendencia de Banca, Seguros y Administradoras Privadas de Fondos de Pensiones of Peru
AI Powered Consumer Protection Suite
Developed in collaboration with Bangko Sentral ng Pilipinas (Central Bank of the Philippines) and Securities and Exchange Commissions of the Philippines
Next-Gen Chatbot and Analytics
Developed in collaboration with Otoritas Jasa Keuangan (Financial Services Authority of Indonesia) and Bank of Ghana