Finance Research - overview
IBM Research's Finance Research team is working to adapt core technology innovations, such as Secure and Elastic Microservices-based Hybrid Cloud Solutions, Artificial Intelligence (especially Machine Learning), Blockchain, Quantum Computing to the needs of banks, credit unions, industrial lenders, insurance companies, investment managers and those who regulate them. The group includes researchers located in Melbourne (Australia), Capetown (South Africa), Yorktown Heights (New York, USA), Tokyo (Japan), Zurich,(Switzerland), and Cambridge (Massachusetts, USA).
The Finance Industry is vital to IBM’s business around the world. Our research mission is to be a technology innovation leader in Financial Services and a preferred innovation partner for our clients by: Focusing on Innovations that are Transformative, at a Business Level, and validating this by collaboration with emerging and leading Financial Services organizations.
The scope of the Finance Industry Research includes the three industry vertical sectors – Banking, Financial Markets and Insurance, as well as supervisory agencies that oversee them.
Finance Industry research helps create the next generation Finance Industry technology platforms, enterprise applications and business networks in support of key industry transformations such as AI in Risk and Compliance, new information models that leverage non-traditional data to develop deep customer insights and experience, explore distributed ledgers, smart contracts and cybersecurity technologies in support of new financial services ecosystems, and next-generation scale-ready and secure architectures and cloud infrastructures for AI, Blockchain and Advanced Analytics.
Some of the focused on-going areas of research include
- Detect and pre-empt fraud and financial crimes through AI-based enhanced due diligence and advanced transactional fraud analytics. Addressing financial crimes is a top industry challenge that is inhibited by fragmented processes, data silos, and rule-based systems with 95%+ false positives.
- Deep entity analytics for transforming and automating back office risk & compliance processes to handle complex and dynamic regulatory regimen. Secular regulatory changes (PSD2, MIFID II, GDPR) are driving major changes in how financial services are designed, delivered and consumed.
- Financial markets predictive analytics, scenario planning and portfolio optimization using advanced AI and Quantum computing. Some of the largest Financial Institutions around the world are collaborating with IBM Research to explore quantum for competitive advantage.
- Using non-traditional data sources and recommendation systems for personalized digital client experience with precision targeting and provisioning of financial products and services. Recommendation systems are credited with significant e-commerce revenues; how can such a significant impact be generated for clients in the Finance Industry.
- Participating and piloting new industry ecosystem plays in Finance Industry leading to new market platforms anchored on innovations in Blockchain, IoT, Cybersecurity and AI technologies. Explosive growth of FinTech and new regulations (e.g. PSD2) are motivating new business models and ecosystems such as car e-wallets, supply chain and trade finance, connected insurance etc.
- Developing next-generation Finance Industry platforms with optimized AI, Blockchain and Cybersecurity capabilities. IBM's systems have an enduring presence in the industry with unsurpassed transaction management and security capabilities and the focus is to build on this to create the next-gen platforms that flexibly supports private, public and hybrid deployments.
A word about Artificial Intelligence: IBM helped found AI as a field in 1956 and continues to research and develop AI technologies and solutions, in concert with universities (MIT-IBM AI Lab) and industry partners (Partnership on AI), to unlock its potential and to deploy at scale in enterprises across industries. Finance Research is working with MIT and other universities with focus on enterprise AI in Financial Services that enable secure and trusted cloud platform and automate and streamline financial processes such as financial crimes compliance (KYC/AML), financial forecasting and credit risk management, and hyper-personalized digital experiences for customers.
Our four Research priority areas are:
Secure and Trusted Financial Services Computing Platform
General Purpose facilities for Cybersecurity, including Data Privacy, are available for the Hybrid-Cloud and Multi-Cloud era, but how they can be used in protecting extremely sensitive financial data given overlapping supervisory requirements in different nations is an important research area for our team. We also believe that query and update of large graphs will be important as we trace relationships between businesses, and impacts of legal, physical, and economic events upon the customers or potential customers of a Financial Services Enterprise. We have active work on technology that manages very large graphs as they are used in applications that utilize machine learning as well as classical analytics.
Streamline Financial Processes as Seen by Financial Sector Enterprises' Customers
Artificial Intelligence approaches can allow a much deeper level of anytime and anyplace service to customers of Financial Sector Enterprises. New approaches to using conversational and multi-model interactions that are suitable for access with customer devices (in their hands, in their living rooms, on their desks, in their vehicles, etc.) are included in our research scope. New approaches to increasing engagement and accuracy of financial advisors with individual customers are being development, building on the ability to extract meaning from textual documents. We also work on new kinds of predictive model execution, both using classical computing and using Quantum computing. In an ambitious project, we are providing new credit facilities to small vendors operating in local markets within Africa, with a goal of extremely simplicity.
Streamline Financial Processes inside the Enterprise and with Regulator Interaction
Risk Management is an imperative for Financial Sector Enterprises. Our research includes new ways to detect attempts at financial crime, and easier ways to share continuously-gathered information with supervisory agencies who want assurance of numerous kinds of compliance.
Financial Services Ecosystem Enablement (particularly using Blockchain)
While a few financial services organizations may seek to provide "all services" to "all providers", this does not allow specialization and can raise public anxiety about "too big". But collaborative execution of services for customers should be feasible, perhaps with less latency and more auditibility, using technologies such as Blockchain. We are working on approaches for different Financial Services Enterprises to describe "what we can do" "what we know" so that an adaptive network can support a service, building heavily on computer science ideas of services-with-APIs, business process design, management, and execution; while assuring that no party can "masquerade" as legitimate and see data, or acquire funds, that they are not entitled to.
Our most recent workshop presentations or conference papers are: