Volatile markets, increasing complexity and a permanent crisis mode are challenging the insurance and risk industry more than ever. Marcus Selzer, Managing Director of Golden Sail and author, supports sales managers in precisely this area of tension.
In an interview with thebrokernews, the Golden Sail founder talks about leadership, decision-making under uncertainty and why cultural resilience is becoming a decisive competitive factor.
Marcus, you work in your company Golden Sail as a consultant and coach with managers in challenging transformation phases. You are also currently writing your book on the topic of “AI and mindset in sales” What do you currently see as the biggest challenge for decision-makers in the insurance and risk industry?
I see the biggest challenge not in the complexity of the markets, but in the emotional response to them. In my work with sales teams in the insurance industry, a pattern emerges: managers struggle less with strategic issues than with decision-making blocks, which are transferred directly to their sales teams.
An example. An account manager knew exactly that she should use AI tools for customer analysis. The data was there, the tools were implemented, the budget was available. But the fear of making mistakes, of losing control, of not being able to do things paralyzed her. For months.
The result: while colleagues in other companies were already selling with the help of AI, she stuck with Excel spreadsheets and gut feeling. Not out of incompetence. Out of emotional blockage.
This is not an isolated case. The technology is not the problem, nor is the strategy. It’s the psychology of the decision. The real challenge lies in managers and sales teams acting despite uncertainty and releasing the emotional patterns that slow them down at the crucial moment.
By definition, insurance companies are geared towards risk analysis and yet we still experience strategic surprises time and again. Where do you see the blind spots?
The biggest blind spot is not in the data, but in the decision-makers themselves. Insurance companies are world champions in analyzing external risks, but are often blind to the emotional patterns that drive their own decisions.
I observe three central blind spots.
Firstly: status quo bias. We are successful, so we don’t change anything. A medium-sized insurance company stuck to a tried-and-tested business model for years, even though the data clearly showed that the market was changing. Not out of ignorance. Out of fear of change.
Secondly, confirmation bias. We look for data that supports our opinion, but ignore warning signs. Managers do not analyze neutrally, they confirm their preconceptions. If I am convinced that AI has no place in personal selling, I find studies that prove it.
Thirdly: loss aversion. The fear of losing something is greater than the chance of gaining something. This leads to defensive strategies. Instead of aggressively tapping into new markets, insurance companies defend existing positions until it is too late.
The paradox is that these patterns are well researched scientifically, but are not recognized in your own company. When introducing the AI training arena, I regularly see managers discovering patterns in themselves that they had long since identified in their teams. The blind spot is that we see the risk in the market, but not in ourselves.
How is permanent uncertainty changing the way leadership is perceived and practiced today?
Managers no longer make decisions, but manage options. They keep all doors open for fear of choosing the wrong one.
An example from my practice. A team leader knew that his team should use the new AI-supported customer analyses in order to remain capable of acting even in a difficult market environment. But instead of making a clear decision, he organized meeting after meeting, gathered input and waited for the right time.
The result: his team lost six months. Not because of incompetence, but because his own insecurity paralyzed him.
What has changed? He has learned to deal with his own insecurity. In concrete terms, this means accepting uncertainty as the new normal, not fighting it. A quick decision with 70 percent certainty is better than a perfect decision in three months. And above all: self-management before team management. If you can’t lead yourself, you can’t lead a team.
The solution does not lie in more data or better processes. It lies in emotional clarity. Managers must learn to recognize and consciously control their own patterns. That is the core of my work. We don’t work on strategies, but on the mental blocks that prevent good strategies from being implemented.
Many insurance companies are very process-oriented. Where do you see the boundary between necessary structure and paralyzing bureaucracy?
The limit lies where processes no longer serve the purpose of security, but rather the avoidance of responsibility. This is not a structural issue, but a psychological one.
A concrete example: In one company I worked with, there is an approval process for customer quotes that requires six signatures. Six. The official justification: quality assurance, risk minimization, compliance. The actual function: nobody wants to be solely responsible. If a deal goes wrong, everyone can say: I only gave my OK, but so did the others.
The result: bids take three weeks instead of three days. During this time, the competition has long since closed.
So the crucial question is not: How many processes do we need? But rather: Do these processes serve the customer or our fear?
You can recognize necessary structure by the fact that it speeds up decisions, provides orientation in complex situations and creates clarity about responsibility. You can recognize paralyzing bureaucracy by the fact that it slows down decisions, obscures responsibility and serves to protect against errors instead of creating value.
The solution does not lie in less structure, but in psychological security. If mistakes are allowed, fewer safeguarding processes are needed. If responsibility is clear, fewer signatures are needed. And this is where the management task comes into play: creating role models. Managers who make their own mistakes transparent allow the team to make mistakes too.
You often talk about clarity and attitude in sales management. What does this mean in concrete terms in an environment of regulatory and economic constraints?
Clarity arises not despite, but through constraints. That sounds paradoxical, but it is one of my key observations when working with sales teams.
Regulation, compliance and budget requirements are not excuses, but guard rails. The question is: Do I use them as a justification for standing still or as a guide for confident decisions?
A concrete example from the AI training arena: We regularly simulate difficult sales conversations, for example when a customer demands a discount that you are not allowed to give, or when a product does not perfectly match the customer’s needs.
The salespeople who perform best have a clear attitude: I am free within these guard rails and I sell confidently within them. They don’t say: I’m not allowed to do that. They say: I can’t offer that, but here’s what I can do for you. That is a fundamental difference in your inner attitude.
The salespeople who struggle, who experience the constraints as a threat, lose the conversation. Not because of the constraints, but because of their inner attitude towards them. The customer senses this immediately.
And this is where the real leadership task lies: being a role model in dealing with constraints. If the manager struggles themselves, this is transferred directly to the team. If they navigate confidently, the team does too. In concrete terms, this means: don’t complain about constraints, use them. Teams need to understand why constraints exist. Not to like them, but to accept them. And leeway must be clearly defined. Clear lines reduce uncertainty.
Risk management is traditionally driven by numbers and models. What role do emotional intelligence and self-management play in this context?
Risk management without emotional intelligence is like selling without customer understanding. The models are only as good as the people who interpret them.
In my work with risk managers, I have come to a startling realization: the best decision-makers are not the ones who analyze the most data. They are the ones who know their own emotional patterns.
Example. A risk manager has recognized that he is prone to loss aversion. This means that he weights potential losses more heavily than potential gains. In risk models, this leads to defensive recommendations, even if the data would suggest an offensive strategy.
Since realizing this, he asks himself three questions before every big decision: What fear is driving me right now? What is the worst-case scenario, and is it really that bad? What would I advise if it wasn’t my responsibility? The result: his decisions have become more courageous. But not riskier.
Emotional intelligence in risk management specifically means: self-reflection before making a decision. What emotional patterns influence me? Then: recognizing emotional patterns in the team. Where do we systematically avoid? Where do we overestimate ourselves? And finally: creating safe practice areas. Mistakes must be allowed, otherwise decisions will only be made defensively.
That’s why I now consciously use the AI training arena. Not to train sales techniques, but to make emotional patterns visible under stress. If a salesperson comes under pressure in an AI conversation, they react in exactly the same way as a real customer. Only without the risk. They see: Aha, if the customer raises objections, I become insecure and give in.
That is the game changer. AI as a mirror for emotional intelligence, not as a substitute.
How can insurance executives make better decisions when data and forecasts are becoming increasingly uncertain?
The quality of a decision depends less on the data and more on the inner clarity of the decision-maker.
An example: An account manager had 95% data quality for an important product launch. All the figures were there, all the scenarios had been calculated, all the risks had been assessed. And yet she still made a bad decision. Why? Because she was driven by unconscious patterns: Fear of making mistakes, desire for perfection, confirmation bias.
Your colleague made a better decision with 60 percent data quality because he knew his own patterns and consciously took countermeasures. He knew: I tend to be optimistic, so I actively look for counterarguments. The result: a balanced, courageous decision.
So the question is not: How do I get more data? But rather: How do I make clear decisions despite uncertainty?
My framework for this: mental inventory. What do I really fear? If you know the emotional level, you can separate it from the factual level. Then: play through the worst-case scenario. It is usually manageable. If the worst-case scenario is acceptable, the decision is easier. Thirdly: quick decision, quick correction. Better 70 percent today than 90 percent in three months. Markets don’t wait. And finally: AI as a sparring partner. Run through scenarios before things get serious.
In the AI training arena, we simulate exactly that: decisions under pressure, without perfect data. Salespeople practise remaining confident despite uncertainty. Better decisions don’t come from more data, but from more self-knowledge.
To what extent does the handling of risk at management level differ from that at operational level and how can this gap be closed?
The gap is often not caused by different risk perceptions, but by a lack of internal sales skills. Managers are unable to sell their strategy because they are not convinced of it themselves.
A concrete example. A managing director decides that the sales team should use AI-supported customer analyses in future. From his point of view, the risk is calculable: if 20 percent of salespeople use the tool and generate 10 percent more sales, the investment pays off.
At an operational level, the risk is different: I have to learn a new tool, give up my tried and tested methods, possibly embarrass myself, and in the end it may not work. The perceived risk is personal, not abstract.
So the gap lies in the translation. Management thinks in terms of scenarios and probabilities. Operational level thinks in terms of personal consequences.
How can this gap be closed?
Firstly, management must learn to sell internally. A strategy is only as good as its salesmanship. Don’t just present figures, tell stories. Don’t just point out opportunities, take fears seriously.
Secondly, the operational level needs safe practice areas. People need the opportunity to try out new methods without risk.
Thirdly: Transparency about personal consequences. Instead of saying: We are introducing AI because it is more efficient, we should say: We are introducing AI so that you can concentrate on the complex conversations that you love.
And fourthly: create quick wins. Small, measurable successes are more convincing than grand visions. The gap between management and operational level is not a question of data or processes, but of communication and trust.
Culture is often underestimated as a “soft factor”. What specific risks arise when corporate culture is neglected?
Neglected culture leads to an invisible risk that does not appear in any risk report: Sales Inhibition.
If the culture is not right, teams no longer sell actively, but reactively. They wait for inquiries instead of acquiring them. They avoid difficult conversations. They miss out on opportunities.
I just come back to the current experiences from the AI training arena, because the following pattern often emerges there: Company A with a strong error culture uses the arena intensively, experiments, also practices unpleasant sales conversations, learns quickly. Company B with a culture of fear hardly uses the arena, is afraid that managers will see their mistakes and only practices safe scenarios.
The result: Company A doubles its acquisition success rate in just three months. Company B invests thousands of francs in a tool that is not used.
Even more drastic: In company B, the first good salespeople leave the company. Why? Because they sense that innovation is not wanted, only claimed. They realize that their company is standing still and that this will quickly become a competitive disadvantage.
So what specific risks arise?
Sales inhibition: teams sell below their potential.
Silent resignation: The best people leave.
Innovation paralysis: New ideas are not implemented.
Invisible costs: Duplication of work, friction losses, demotivation.
And: Customers feel it. Companies without a good culture lose orders.
Culture is therefore not a soft factor, but a hard sales lever. And: culture does not start in HR, but in the role model function of management. When managers themselves make mistakes transparently, they allow their team to make mistakes too. Neglected culture costs turnover, talent and innovative strength.
Many insurers are under pressure to innovate and cut costs at the same time. How can this tension be used productively?
This tension is often homemade. It arises from decision-making blocks: We want innovation, but are afraid of making mistakes. This is not a budget issue, but a mindset issue.
A concrete example: a medium-sized insurer had the following problem: management demanded innovation, but at the same time every mistake was sanctioned. The result: no one dared to really innovate. Instead, safe projects were implemented that improved the status quo but did not create anything new.
The solution does not lie in more budget or less cost pressure, but in clarity about priorities.
Firstly: Decide what is really important. Not everything at the same time. Either I invest in innovation, in which case I have to cut costs elsewhere. Or I focus on efficiency, in which case I can’t be disruptive at the same time. Wanting to do both leads to paralysis.
Secondly, plan a failure budget. If innovation is required, part of the budget must be explicitly planned for experiments that are allowed to fail. If eight out of ten projects fail, but two break through, that is a success.
Thirdly: small experiments, rapid iteration. Instead of investing millions in large transformation projects, insurers should start with pilot projects. One team, two months, clear success criteria. If it works, scale it up. If not, end it quickly.
Fourthly: Use cost pressure as a driver for focus. Cost pressure forces prioritization. What is really important? Which processes can we leave out? Paradoxically, cost pressure often leads to better decisions because it forces us to ask clear questions. The tension between innovation and costs is productive if it is used instead of lamented.
What does resilience mean for organizations whose business model is based on stability and reliability?
Resilience starts with each individual employee. A resilient company needs resilient salespeople who keep going even after rejections, resilient managers who radiate clarity even in crises, resilient teams who don’t give up even after setbacks.
Insurance companies tend to understand resilience as an organizational concept: We need backup systems, emergency plans, redundancies. This is important, but it falls short. The real resilience lies in people’s ability to deal with uncertainty, pressure and setbacks.
An example from a colleague: During the pandemic, there were two companies that reacted very differently. Company A had perfect processes, emergency plans and technology. But the sales teams collapsed because they were not emotionally prepared for the uncertainty. Many fell into a state of shock and waited instead of taking action.
Company B had less perfect processes, but a culture that promoted individual resilience. Salespeople were used to dealing with uncertainty, making quick decisions and experimenting. They adapted to the new reality within weeks. The result: Company B grew during the pandemic.
What does that mean in concrete terms? Resilience can be trained. How do you train resilience? By exposing people to safe stress. Practicing difficult sales conversations and objections, feeling the pressure. In this way, salespeople learn to remain confident despite stress. It’s like mental strength training.
Resilience requires psychological security. People are only resilient if they know that mistakes are allowed. Resilience requires self-knowledge. If you know your own patterns, you can consciously take countermeasures. And: resilience is not hardness, but adaptability.
Do you see a change in the way managers see themselves, for example away from being an expert and towards being an enabler?
Absolutely. The shift is from I know to I enable. But many fail because they can’t let go. That is also an emotional blockade.
In the past, managers were successful because they were the best experts. The best actuary became head of department. The best salesperson became a sales manager. The logic: whoever knows the most can lead the best. That no longer works.
Why not? Complexity exceeds individual expertise. No single person can keep track of all the issues today. AI, regulation, new sales channels, customer needs – it’s too much for one person. Teams are more diverse and autonomous. The best salespeople no longer want to be told how to sell. They want guidance, but not micromanagement. And: knowledge becomes outdated more quickly. What worked five years ago may no longer work today.
The new role of the manager is enabler: creating framework conditions in which teams can be successful. Provide resources. Provide orientation. Creating psychological security.
But here comes the problem: many managers are unable to let go. Loss of identity: If I’m no longer an expert, who am I? Fear of control: If I no longer control everything, things will go wrong. Loss of status: If I no longer have the answers, nobody respects me anymore.
These fears are real, and they cause managers to fall back into old patterns. They micromanage, they want to make all the decisions themselves. As a result, teams become less independent, innovation is slowed down and the best talent leaves.
How can change succeed? Develop a new identity. Managers must learn that their value lies not in their knowledge, but in their ability to make others successful. The change from expert to enabler is necessary, but emotionally challenging.
What typical errors in thinking do you encounter among managers when it comes to strategic risks?
I have dealt intensively with mental blocks among managers, including during the research for my book on AI and sales psychology, which will be published in March. I encounter three thinking errors particularly frequently.
The first: loss aversion. We hold on to declining products because we don’t want to admit that they are dead. One example: an insurance company held on to a pension product for five years, even though all the data was against it. The market was changing, customers wanted flexible solutions and the competition had long been ahead. Why did they hold on? The managing director had personally developed the product fifteen years ago. It was his baby. Giving it up would have meant negating his own life’s work. Loss of identity was more painful than loss of sales.
The second: confirmation bias. We look for data that supports our opinion, but ignore warning signs. An example: A team leader wanted to introduce an AI tool in sales. She was convinced. So she only asked her tech-savvy colleagues for their opinion. They all said: great idea. Then she rolled out the tool to the entire team and eighty percent boycotted it. Why? Because she had never asked the skeptics. She had only heard what she wanted to hear. That cost six months and tens of thousands of francs.
The third: sunk-cost fallacy. We have already invested so much, now we can’t go back. One example: an insurer invested 2 million in new sales software. After a year, it was clear that it wouldn’t work. But instead of terminating the project, the management invested another 500,000 francs in optimization. Why? We have already invested so much, now we have to see it through. The result: after three years, the project was quietly buried. Total investment: 4 million. Benefit: Zero.
Why do these thinking errors happen? They are not cognitive, but emotional. They are based on fear, insecurity and learned patterns. And that is precisely why these mistakes cannot be solved with classic strategy workshops. They need psychological work, self-reflection and safe spaces. The biggest risks are not caused by wrong strategies, but by emotional patterns that prevent rational decisions.
How can coaching approaches help to overcome silo thinking and decision-making fears in large insurance organizations?
With the Sales Unlock Method, we systematically work on the emotional blockages behind silo thinking. The method is based on 20 years of sales practice and is at the heart of my work.
The basic principle: silo thinking is not a structural problem, but a fear problem. People build silos because they are afraid of losing control, of visibility, of responsibility.
A concrete example. A team leader was asked to work more closely with Product Development. She said: Yes, we’ll do it. But nothing happened in practice. Why not? When working with her, it turned out that she was afraid that Product Development would discover how little she knew about technical details. She had positioned herself as a sales expert. If she were to admit now that she didn’t know the products in detail, she would lose face. So she stayed in her silo. Not out of ill will. Out of fear.
What can you do specifically to overcome silo thinking?
Firstly: blockade identification. Ask yourself or your managers: What am I really afraid of if I share my knowledge? What is the worst consequence? The team leader from my example realized: Nothing. On the contrary, product development would be able to support them better if they knew where their knowledge gaps were. The fear was unfounded, but real. Naming them was the first step towards a solution.
Secondly, create safe practice rooms. Enable teams to practice cross-departmental scenarios without losing face. In tools such as the AI training arena, for example, salespeople can practise with an AI avatar that simulates a product manager. They ask questions, listen and get to know the perspective of the other department. And they realize: They have pressure too. They are not my opponents. This builds empathy without the need for a team-building exercise.
Thirdly: Establish new patterns through small successes. Start with an experiment that can work. The team leader invited a product manager to a customer meeting. They prepared the meeting together. The product manager was able to answer technical questions and she led the conversation. The result: the customer was delighted. She realized: Working together makes me stronger, not weaker. This one positive experience changed her behavior. Within six months, the silo dissolved.
Silo thinking and decision-making fears are not resolved through organizational charts or processes, but through trust. And trust comes from experience, not PowerPoint.
Finally, what skills will managers in the insurance and risk industry need to develop over the next five years?
Based on my coaching experience and research over the last 12 months, I have developed a roadmap. From this I derive five critical competencies.
Firstly: Emotional self-management. If you can’t lead yourself, you can’t lead teams. The insurance companies that will win in the coming years will have managers who know and can manage their own emotional patterns. In practical terms, this means regular self-reflection, a culture of feedback and a willingness to make your own mistakes transparent. Why is this critical? Because uncertainty is increasing, and only managers who can deal with their own uncertainty will be able to steer teams through crises.
Secondly: AI fluency. Not being able to program, but understanding what AI can and cannot do. Managers do not have to become data scientists, but they must develop AI competence. Practical: Experiment with AI tools, not just talk about them. Understand where AI helps and where it hurts. Don’t be afraid of technology. Why is this critical? Because AI will change every aspect of the insurance industry over the next five years.
Thirdly: internal sales competence. Strategy is only as good as its salesmanship. Managers must learn to sell visions, strategies and changes in such a way that teams follow. This means: storytelling, emotional appeal, dialog. Why is this critical? Because the best strategy is useless if it is not implemented.
Fourthly: resilience training. Continuous practice instead of one-off training sessions. The future belongs to managers who cultivate continuous learning. Small, regular practice sessions. Feedback loops after every important meeting. Experiment, make mistakes, learn, repeat. Why is this critical? Because markets are changing faster than ever before.
Fifth: Ethical judgment. AI raises new ethical questions. Managers must take a stand: What is allowed? What is right? Where do we set boundaries? Practical: Clear guidelines for AI use, transparent communication, willingness to decide against efficiency if it is ethically necessary. Why is this critical? Because customers, employees and regulators expect an attitude.
The skills of the future are no longer primarily technical, but human. The good news is that all of these skills can be learned. The bad news: Only if you start. My advice: Start today. Small. Reflect on a conversation. Try out an AI tool. Make a decision transparent. And the next one tomorrow. The biggest mistake is not being too slow. The biggest mistake is not starting at all.
The questions were asked by Binci Heeb.
Marcus Selzer is Managing Director of Golden Sail Consulting, developer of the Sales Unlock Method®, systemic coach and NLP Master with 20 years of sales and coaching experience. He helps sales teams in insurance and financial services to remove the mental blocks that prevent sales success. As an author, he combines three subject areas: personal clarity (mindset novel), practical sales psychology and mindset in AI transformation. Career: Since 2019: Managing Director of Golden Sail Consulting GmbH. 2015-2018: Key Account Manager, Allianz Worldwide Partners. 2002-2015: Various sales and management roles, Allianz Suisse.
Read also: Hallucinating AI: Significant risks for insurers and risk managers
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