C3 AI Securities Lending Optimization

Create a vendor selection project & run comparison reports
Click to express your interest in this report
Indication of coverage against your requirements
A subscription is required to activate this feature. Contact us for more info.
Celent have reviewed this profile and believe it to be accurate.


Transform Securities Lending with Machine Learning

C3 AI® Securities Lending Optimization applies advanced AI-machine learning techniques to help banks automate and optimize securities lending operations. Securities lending groups have historically relied on rules-based software to automatically approve borrower inquiries. Unfortunately, due to the high uncertainty inherent in securities lending, existing processes routinely reject thousands of executable borrower requests. C3 AI Securities Lending Optimization closes this gap.

Banks face significant uncertainty when deciding whether to facilitate a client’s request to borrow securities. The bank must quickly assess both how much they expect the borrower to trade and whether sufficient securities are available. Unfortunately, neither quantity is knowable. The quantity that the client will actually execute is not known until the end of the day and lender stock availability is not updated in real-time. Additionally, in most markets, the settlement date for trades is two days after the trade is executed, at which point, the availability of the security may have changed. C3 AI Securities Lending Optimization uses machine learning to quantify client and lender uncertainties then automatically approves all executable client inquiries, drastically increasing the number of transactions the banks are able to facilitate.

To do this, C3 AI Securities Lending Optimization centralizes data from many disparate source systems such as inquiries, settlements, lender availability, borrows, market data, third-party lending data, corporate actions, and earnings. then combines and manipulates this data in hundreds of out-of-the-box permutations that provide predictive signals to the machine learning models. Finally, C3 AI Securities Lending uses the outputs from the machine learning models to automatically determine optimal lending decisions.

Key Features

  • AI predictions for client and lender activity Use machine learning to cut through uncertainty relating to client trading and lender stock availability
  • Automatic, fast inquiry approvals Approve more inquiries more quickly while leveraging machine learning to ensure approvals are executable
  • Real-time monitoring and notifications View inventory, availability, inquiry, and execution metrics in real-time; get notified when certain metrics exceed thresholds
  • Stock details View real-time information by security and sector – including inquiries, availability, settlements, rate, market trades, corporate actions, and earnings
  • Complete client visibility Understand the client trading behavior across KPIs to enable improved customer support; get notified about shifts in customer trading behavior
  • Summary view View KPIs across the entire securities lending desk, enabling management to understand trends and track operations, revenues, and risk
  • Risk management Tune the approval system to enable more inquiries while choosing how much failed-settlement risk to mitigate
  • Unified data visibility See patterns for all relevant securities lending data—including inquiries, settlements, lender availability, borrows, and market data—in one place
  • Out-of-the-box analytics Extend and modify hundreds of out-of-the-box analytics to quickly develop a predictive machine learning model
  • Scale across geographies Easily scale to securities lending desks in other geographies, enabling consistent operations across the globe

Key Benefits

  • Faster inquiry approvals by reducing the need for manual review

  • Increase revenue by responding to more inquiries for hard-to-borrow securities that are more profitable for the desk

  • Improve client relationships by providing more complete, faster responses to client requests and by providing the client team with a complete view of client inquiries and trades

  • Greater visibility of risks and uncertainties by applying machine learning to predict uncertain quantities and alerting when KPIs cross certain thresholds

  • Enhance employee productivity by automating repetitive work such as manually reviewing and responding to inquiries, enabling employees to focus on value-added activities, and client interactions



Product/Service details