Due diligence in a dynamic environment
As banks pursue M&A deals as a growth driver, those deals will likely differ depending on the market cap of the acquiring entity. The largest financial institutions, for instance, may be most likely to acquire fintech and wealth management targets, while midsize banks may be more likely to pursue a merger of equals, enabling scale and access to new markets. Smaller regional and community banks will benefit from a focus on scaling or on developing or expanding niche capabilities to open up new opportunities and markets. They may also position themselves for a transaction with a larger institution.
For banks across all segments, remaining competitive will require preparations now for future transactions. Key steps in this preparation include:
- Conducting a data-driven assessment of markets and capabilities as well as strengths, weaknesses, opportunities and threats.
- Aligning the organization’s acquisition strategy and key performance indicators to broader corporate strategy.
- Defining strategic needs and getting C-suite buy-in to enable rapid decision making.
- Cultivating a list of targets that support their inorganic growth strategy (developed in the above three activities).
Preparing for due diligence—and being capable of executing due diligence quickly—is the next essential step. Organizations should assess and build their internal teams’ bench strength and work with a third party as needed to fulfill diligence requirements through a just-in-time sourcing model.
Other parts of the due diligence process include:
- Perform a competitive analysis using external benchmarks to evaluate financial, product and market opportunities and gaps.
- Analyze existing contracts and potential pitfalls, such as escalator clauses, volume discounts, duplicate contracts, termination clauses and poison pills.
- Manage risks including cyberattacks, operational risk and credit risk (from announcement through post-integration).
- Understand non negotiables.
Data-driven approaches
A data-driven methodology for each phase of a transaction—from conducting due diligence, to preparing for the acquisition transaction through integration—following close is critical to successful execution.
For banks that may be unsure where to start integrating data-driven capabilities into their M&A strategy, potential use cases to explore include:
- Assessing the organization’s post-integration, future state tech stack and optimizing it for immediate and future scale.
- Evaluating credit risk and stress testing scenarios post-acquisition.
- Automating the process of completing reviews of existing contracts to identify redundancies and synergies while assessing risks.
- Interrogating and assessing monetization opportunities for the acquired organizational data.
- Product mapping and competitive benchmarking to visualize what the integrated organization’s retail, commercial and investment portfolio will be post-integration.
Post-integration, financial institutions need to harness data and consider implementing artificial intelligence to continuously monitor the impact of the transaction against the metrics established for customers and employees pre-transaction. Another post-integration consideration is to establish support centers to address customer complaints and confusion, which are common following an integration. Institutions can use digital portals, chatbots and self-service options for customers seeking support as these solutions can increase initial customer retention and long-term growth.
For financial institutions that expect to be serially acquisitive, building a layer of operations—known as an integration factory—to effectively on-board subsequent targets will improve the efficiency of integrations. The factory capabilities should include an integration middleware service, common processes, dynamic playbooks and digital strategies.
As the industry’s appetite for acquisitions continues to increase, institutions best prepared to execute transactions will be positioned for high performance.
