Plunging interest rates are compelling insurers to extend their portfolios beyond traditional fixed-income investments into broader asset classes to squeeze out better returns.
These include complex derivatives, bank and commercial loans, and alternatives such as limited partnerships and private equity.
Additionally, the expansion of insurance industry M&A activity has driven traditional investment operations into new global markets, further increasing middle- and back-office accounting, operational and reporting complexities.
"Plunging interest rates are compelling insurers to extend their portfolios
beyond traditional fixed-income."
As a result, insurers are beginning to decouple middle and back-office processes from custody services, selecting new technology and solutions providers.
Key to the selection process is the vendor’s ability to deliver substantial efficiency improvements and cost reduction through next-generation AI technologies while delivering deep domain expertise in more complex asset classes.
Diversified investing requires sophisticated middle- and back-office technology to handle the complex processing of trades, cash transactions, compliance, collateral management, corporate actions, investment accounting updates and daily reconciliations.
Traditional middle- and back-office systems are driven primarily by hard-coded rules and processes.
"Innovative solutions with embedded AI tools learn from user behaviour
and intelligently automate critical tasks."
These systems lack the intelligent technologies to streamline repetitive tasks such as counterparty reconciliation, exception management or the remediation of breaks or errors.
Innovative solutions with embedded AI tools learn from user behaviour and intelligently automate critical tasks and processes.
Such tools include machine learning (ML), intelligent workflow automation (IWA), predictive analytics (PA), natural language processing (NLP) and others.
In cases of complex reconciliation, embedded machine learning capabilities continuously learn and adapt matching rules and tolerance thresholds across multiple counterparties.
Furthermore, machine learning capabilities, when coupled with IWA tools, can help efficiently identify and remediate breaks and exceptions.
"A machine learning model can identify a cash transaction
break with a custodian counterparty."
For example, a machine learning model can identify a cash transaction break with a custodian counterparty on a fixed income instrument.
Then, through the use of IWA, values can be automatically researched, compared and updated to resolve discrepancies, notify custodians, and update accounting records accordingly.
Next-generation platforms include embedded predictive analytics to suggest or auto-populate data fields, values and associated confidence levels based on past transactions, current portfolio holdings or user entries.
Advanced analytics can also help bring context to variances in financial performance related to earned income or yield swings from one reporting period to the next.
"Advanced analytics can also help bring context to
variances in financial performance."
Similarly, NLP can automate, read, parse, and process document-based data associated with bank loans and alternative investments.
The automation can handle complex structures such as limited partnerships, where an agent bank issues event notices such as paydowns or rate resets in non-standardised PDF, Word or fax formats.
Asset diversification, through both organic growth and M&A activity, forces insurers to manage multiple, disparate systems for investment operations and accounting.
These systems typically serve specific asset classes and require complex wiring to consolidate investment data to enable straight-through processing. Such setups have resulted in considerable operational inefficiency and poor data quality.
"Asset diversification forces insurers to manage multiple, disparate
systems for investment operations and accounting."
Next-generation, unified solutions with broad asset type coverage and leverage AI and other innovative tools are poised to improve operational efficiency, insights and data quality.
Consolidation of data sets and operational and accounting processes on a single platform give insurers the ability to reduce and automate reconciliation activities, eliminate manual workarounds, and strengthen risk management across the entire investment portfolio.
The expansion of insurance investment activities into broader global markets creates new accounting challenges, as insurers comply with additional local market accounting and other regulatory requirements.
New solutions that support an unlimited number of accounting bases and rule sets, together with flexible data access and reporting capabilities, offer a critical advantage.
While innovative middle and back-office solutions are positioned to change the playing field for insurers dramatically, selection of the right technology and business services partner is equally important.
"Innovative middle and back-office solutions are positioned
to change the playing field for insurers dramatically."
A thoughtful evaluation of each provider’s domain expertise, global and local service capabilities and solution deployment options will ensure the right technology and the right service partner are selected.
Vendors with the resources and commitment to invest in the development of functionally rich, technically innovative products offer insurers the best option to future-proof their investment operations for years to come.
