When most people think about turning around a distressed bank, they picture cuts, closures, and quick fixes. But according to Gada ElKenani, founder of Xeper Strategic Partners and Building Better Banks, that approach misses the bigger picture.
In this conversation with FinTech Times, she explains how community banks can be rebuilt for long-term sustainability by combining regulatory discipline, selective technology adoption, and a capital deployment model designed for transparency and growth.
Gada has spent more than 30 years in banking, and her current work focuses on structuring and restructuring distressed community banks, along with middle market lending and corporate finance restructuring. This post unpacks the thinking behind her bridge, build, offload model, why regulators are central to the turnaround process, and why technology and AI only work when human oversight stays in the loop.
Why Distressed Bank Turnarounds Need a Different Playbook
Traditional turnaround thinking often starts with cost-cutting. That may improve the numbers quickly, but it can also leave the core business weaker than before. Gada’s approach is different because it’s built around sustainability, not just short-term efficiency. She describes her background as one shaped by disciplined banking programs that exposed her to retail, wholesale, compliance, product, and portfolio management. That breadth matters because distressed banks are rarely broken in only one place. Often, the problem is a combination of regulatory issues, legacy systems, weak loan quality, and an operating model that no longer fits the market. What stands out in her approach is the focus on building back capability, not just removing expense. Instead of treating the bank like a one-time cleanup project, she treats it like a long-term operating business that needs the right structure to recover. This matters because a bank is not a one-off asset. It serves a community, handles regulated activity, and depends on trust. If you only cut costs without fixing the underlying issues, you may improve the quarterly story while damaging the bank’s long-term viability.
The Regulatory Fix Comes First – Not Last
One of the clearest themes in the interview is that regulatory repair is the starting point, not an afterthought. Gada is blunt about this: if the AML, KYC, compliance, and risk issues are not addressed first, the bank will keep carrying them forward like unresolved debt. That creates practical roadblocks. A bank with unresolved compliance problems may struggle to open new branches, pursue acquisitions, or regain confidence from investors and counterparties. Regulatory issues don’t just create paperwork – they limit strategic options. Gada also pushes back on the idea that regulators are an obstacle. In her view, they’re part of the solution. Working with regulators creates efficiency, while avoiding or delaying the issues only creates bottlenecks later. What “fixing compliance” really means The areas that need attention include:
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AML and KYC controls
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Customer onboarding
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Interest rate risk management
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Concentration risk
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Reporting and remediation processes
These are not cosmetic improvements. They are the foundation that allows a distressed bank to move again. If the controls are weak, nothing else scales properly. She also emphasizes forensic analysis of the financials. That combination – regulatory review plus detailed balance sheet analysis – gives investors a clearer view of what needs to be fixed, how much capital is needed, and what the turnaround should look like.
Why Capital Should Be Deployed in Phases
Another major difference in Gada’s model is the way capital is deployed. Rather than putting a large amount of cash into a troubled institution all at once, she advocates for a disciplined, objective-based approach. That structure serves two purposes. First, it gives investors transparency. When money is tied to specific milestones, everyone can see what the capital is meant to achieve and whether the bank is progressing. Second, it reduces the risk of masking deeper problems. If you inject too much too quickly, you may create the appearance of progress without fixing the operating issues underneath. These banks are supposed to be long-term, sustainable, and anchored in their communities. This is not a “flip it fast” strategy. It’s about taking market share back, improving profitability, and creating a stable institution that can keep serving customers. The valuation effect of getting the sequence right Gada explains that distressed banks can be bought at very low tangible book value – sometimes at deep discounts relative to assets. But if the turnaround is done well, the bank’s tangible book can rise significantly. That happens when the bank:
- grows assets intelligently
- improves efficiency
- upgrades technology without overextending
- adds profitable households and lending relationships
- resolves regulatory and operational friction
The result is not just a cleaner bank, but a more valuable one. The valuation multiple can improve because the institution is no longer just surviving – it has a credible growth path. This is also why the investor base matters. Family offices and institutional investors generally want discipline, visibility, and downside protection. Gada’s model is designed to meet those expectations while still allowing the bank to recover properly.
Technology and AI Are Useful – But They Are Not the Solution by Themselves
Gada is supportive of technology, but she is clear about its limits. In banking, technology is not a silver bullet. If the underlying data is wrong, or the customer application is incomplete, the output will still be wrong – just faster. Automation can improve efficiency, but it cannot replace judgment. If a customer misunderstands a form or enters incorrect information, the system may process the error as if it were accurate. That can lead to bad decisions and missed opportunities. Her point is that efficiency and accuracy need to work together. Technology helps scale the process, but humans still need to oversee input quality, review outcomes, and catch the edge cases that software may miss. Where technology helps most The greatest near-term opportunity for technology is on the retail side, where banks can:
- retain and grow their existing book of business
- improve profitability per household
- cross-sell relevant products
- support financial literacy
- reach small business, middle market, and consumer segments more effectively
That’s a practical use case. It’s not technology for its own sake. It’s technology designed to strengthen the core relationship between bank and customer. On the wholesale and C&I side, things get more complex. Every deal is different, structures change, and credit policy has to match the risk profile. That means AI and automation need much more customization before they can function well in that environment.
The Bridge, Build, Offload Model Explained
The final major theme is Gada’s proprietary bridge, build, offload model. She describes it as a disciplined framework that has been tested across sectors and helps shape how distressed assets are approached. At a high level, the model works like this:1. Bridge This is the discovery and connection phase. The bank or business is assessed from multiple angles:
- infrastructure
- policies
- regulations
- legacy systems
- technology stack
- capital access
- partnership opportunities
- M&A and exit pathways
The goal is to understand what exists, what is broken, and what external support is needed.2. Build Once the gaps are clear, the next step is to build the foundation. That means improving the areas that can increase EBITDA, strengthen operations, and create a healthier business model. In a bank turnaround, this may include regulatory remediation, technology upgrades, and portfolio improvements.3. Offload The final step is about creating the right exit strategy or transition. Once the institution is stronger, the model allows for a clearer path toward monetization, partnership, sale, or another strategic outcome. This framework is attractive because it forces discipline. It doesn’t let the turnaround become vague or open-ended. It asks the right question at every stage:
What are we bridging to, what are we building, and what is the endgame?
Why this model may scale Gada believes the model has value beyond a single bank or transaction because it helps community banks stay viable in a landscape where many are disappearing or being absorbed. That’s especially relevant in a market shaped by regional consolidation, large-bank dominance, and recent high-profile bank failures. She also sees the model as a form of stress testing. If the strategy is built to anticipate downturns and protect against economic shocks, it can help institutions navigate both micro and macro turbulence more effectively. The bigger implication is that bank turnarounds do not have to be chaotic. With the right structure, they can be methodical, transparent, and resilient.
What Bank Leaders and Investors Can Learn From This Approach
Gada’s perspective offers a useful reminder: turnaround work is not just about fixing a balance sheet. It’s about rebuilding the conditions for trust, growth, and longevity. If you’re a bank leader, the lesson is that you need to treat regulation, technology, and capital as connected systems, not separate projects. If you’re an investor, the lesson is that discipline matters more than speed. And if you’re watching the future of community banking, the message is that the institutions most likely to survive will be the ones that combine human judgment with operational rigor.
Frequently Asked Questions
What is a bridge, build, offload model? It’s a turnaround framework that starts with assessing and connecting the right resources, then building the operational foundation, and finally moving toward an exit or monetization strategy. In Gada’s version, it’s designed to create discipline in distressed banking turnarounds. Why is regulation so important in distressed banks? Because unresolved compliance issues can block growth, acquisitions, branch expansion, and investor confidence. Gada argues that regulatory remediation has to come first if a bank wants to recover sustainably. Can AI fully automate bank turnaround decisions? Not safely, according to Gada. AI can improve efficiency, but human oversight is still needed to catch input errors, contextual issues, and deal-specific complexities. Why not just cut costs to fix a distressed bank? Cost cuts alone may improve margins temporarily, but they don’t necessarily fix compliance, technology, or customer profitability. Gada’s approach focuses on rebuilding a bank so it can grow again.
The full episode is available on YouTube:
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