Financial services

Personnel is policy, in our view. We expect the Trump Administration’s financial services nominees to pursue a traditional Republican agenda of reducing regulatory burdens and stimulating economic growth.

New agency leaders will be able to modify or halt rulemaking that has not been finalized before they take over, such as Basel III Endgame. Any new rulemaking will likely reduce existing requirements; amend rules promulgated by the Biden Administration; and implement more transparent policies around innovative products, such as digital assets or crypto.

New agency leadership will also be able to alter the regulatory landscape through changes to supervisory priorities and enforcement policies. For example, there will likely be a shift away from the Biden Administration’s attention to climate risk management and the CFPB’s aggressive rule making activities.

The expectation of a less onerous regulatory landscape may lead to more mergers, spinoffs and private equity exits. This shift will likely support more investment capital to be diverted away from risk and toward modernization or growth-related initiatives.

Lastly, tax changes could be significant. Trump has proposed cutting the corporate income tax rate to 15% from 21% and he’s called for making permanent estate tax provisions in the Tax Cuts and Jobs Act, which are set to expire at the end of 2025.

Learn more

Private credit is driving change across the financial services markets. Both traditional and alternative asset managers are building capital flywheels and innovating new investment structures while developing scalable operating platforms. Banks are upgrading lending strategies, servicing capabilities, custody and trust services to serve and work with credit platforms. Leaders must navigate complex corporate frameworks, including refining tax efficiency and mitigation of risks to safeguard long-term profitability. Insurers are placing capital in credit strategies, investing in internal credit capabilities while also working with credit investment firms. And capital allocators, including institutional and retail advisors, are directing larger amounts to this increasingly diverse asset class.

Regardless of institution or investment type, new and differentiated technology, industry-leading operations, tax structures and valued strategic relationships will be the avenues for capitalizing on the private credit growth opportunity. Private credit is poised to be central to capital markets in the years ahead, requiring all lenders and borrowers to evaluate how these factors impact their strategy.

Explore further

The impact of generative AI is expansive; however we have seen significant impact concentrated with AI native start-ups and large financial institutions. For example, we have seen a revival in the fintech space with AI native businesses focused on solving old problems with new platforms and business models. Similarly, AI is driving efficiencies in business functions like tax by enhancing compliance, optimizing reporting and identifying potential saving opportunities. We have seen many of the largest financial institutions experimenting with several common use cases. This experimentation has helped them build confidence with new technologies and refine their risk. While AI native start-ups and large financial institutions continue to progress their strategies, there is a risk that firms who continue to evaluate their entry strategy will noticeably begin to fall behind starting in 2025.

Among our clients, we have seen four common use cases emerge across the industry:

• Smarter investment research: New tools designed to help financial advisors formulate an optimal portfolio to match their client’s financial goals or enhancing traders’ scenario analyses covering positioning, sizing and hedging. Customer service: Call center employees are regularly summarizing client calls using voice – text – summarization capabilities and generating efficiency in posting call logs to CRM tools.
• Software development life cycle: Developers collaborate with autonomous AI agents that convert business stories into user stories, test cases, wireframes and code with previously unprecedented speed resulting in efficiency gains expected to conservatively exceed 30%.
• Document extraction: Whether the document is a scanned piece of paper, digitized legal contract or an electronic copy of a new government regulation, AI’s ability to make sense of unstructured data is greatly reducing manual summarization. We believe that in an industry still plagued with paper disclosures, legal requirements and other contracts, this use case will be a game changer for most firms once fully adopted.