Deeper Dive

Today, we’ll be discussing a business intelligence topic, looking at two of the most popular tools for analysts: Excel and Power BI. Welcome to another episode of Deeper Dive, a show that pulls back the curtain on important finance, banking and related topics, breaks down industry events and keeps you in the know. Excel is one of the most used and popular spreadsheet tools empowering data analysis and business intelligence. It is widely used in every industry by almost every team of analysts.

As Excel is broadly available, it is probably already familiar to you. Power BI, on the other hand, is a business intelligence tool that will allow you to create meaningful and visual stories with your data. It’s the most widely adopted business intelligence tool offering powerful functionality to import, transform, analyze and visualize data. Both of these Microsoft tools are popular and widely used by analysts.

Over the last few years, more and more users have started to migrate from Excel to Power BI to develop their business Intelligence reports, analyze their data and share with others in their team. One of the reasons for this trend is the similarities between these two tools. Those who are already familiar with analyzing data in Excel often find themselves comfortable right away in Power BI. Let’s review some of the similarities between these two tools to see why Power BI is a great choice for Excel analysts looking to supercharge their data analysis.

The first similarity between Power BI and Excel and also between almost all Microsoft products really is the user interface. Both tools use a ribbon at the top of the screen containing menus, buttons and other interactive components. If we take a look at a new Excel workbook, we have the ribbon across the top of the page. The home tab contains a lot of commonly used functionality with other tabs like formulas, data automate and developer, all containing logically grouped buttons and menus.

In Power BI, it is really similar. Multiple tabs in the ribbon, logically divided sections of buttons and functionality within these tabs. Some of the tabs even have the same name like home, insert, view, and of course, help. This provides an intuitive user experience making it easier to find functionality even if you haven’t seen it before.

The similarity of navigation of where to find things is a huge timesaver in the learning curve of new tools. This can allow you to really focus on more relevant aspects of Power BI earlier in your learning journey. One such aspect that is common across both tools is Power query, and that is the second similarity that will review. Power query is a data preparation and transformation tool inside of Excel and Power BI.

Let’s take a look first in Excel. We can open the Power Query editor in Excel by navigating to the data tab on the ribbon and then to Get & Transform section. From the Get Data button, we can select the launch Power Query Editor Option. Power Query comes with a graphical interface for getting data from sources and applying transformations.

Using Power Query you can perform the extract, transform and load, or ETL processing, of data. Power query can connect to a wide range of data sources and apply hundreds of different data transformations by previewing data and selecting transformations with the user interface. These data transformation capabilities are common across all data sources that we may use. If we open the Power Query editor in Power BI now, we can see that we have the same experience as Excel, interacting with a familiar set of tools the ribbon menus, buttons and other interactive components.

When using Power Query to access and transform data, you define a repeatable process called a query that can be easily refreshed in the future to get up to date data. Data transformation is a key part of any business intelligence project, and once we have used power query to do so in either Excel or Power BI, we typically load this transform data to be analyzed. How we analyze and interact with our data can differ between tools, but the foundation for this analysis is a data model and DAX measures, which is the third similarity we’ll look at between Excel and Power BI. Data modeling is the process of structuring data so that it is optimized for reporting, business intelligence, and analytics.

Data modeling translates data that has been captured and stored in different formats into a form that is easier to understand and quick to answer our reporting questions. Each data model will be different, as it should reflect the state of the business it is analyzing, as well as the needs of the specific report. In Power BI, we can see our report data model by navigating to the model view here. We can see the collection of tables and the relationships between them, forming the data model for this report.

If we head into Excel, we can see that Power Pivot is the data modeling tool inside of our Excel workbook. If we open up the Power Pivot editor, we can navigate to the model view, and this should look familiar. It is the same model view that we just saw in Power BI. After transforming and modeling data in our business intelligence tool of choice, a way of interacting with our data for exploring or sharing insights from our data with others is data visualization.

And that’s what we’re going to look at next. Creating and formatting visuals poses another similar experience between Excel and Power BI. In Excel, we can select the data in our worksheet that we want to visualize. Go to the ribbon to insert a visual and then select the visual that we want.

Let’s choose a waterfall chart. We usually want to change the formatting of the visual from the default options. This can help us to customize the insight we are trying to share. The commonly used formatting options appear right on the visual itself, using the icon here to access the on-object formatting.

I can use a few different options like adding or removing elements like legends or grid lines. To see the complete set of formatting options we can access, I can double click on a chart element to bring up the formatting pane. Here we can define things like the color of the columns in the visual to better communicate the key message. Let’s recreate this visual in Power BI to see how similar it is to creating it in Excel.

Using the same data model and Power BI, we can insert a visual from the ribbon. Let’s add a waterfall chart and we can start adding our data. From dim headers, let’s add category. And on our y-axis, let’s add our waterfall DAX measure.

We can start adjusting the formatting of our visuals now. The common visual formatting properties are found directly on the visual with on-object formatting, just like how we saw in Excel. To see all the options available to us, we can select more options to bring up the complete formatting pane. Here we can adjust things like title background and the color of the columns and the waterfall chart.

Let’s change these colors to better highlight the costs and expenses in the waterfall chart. As we can see, creating and formatting visuals has a similar experience in Excel and Power BI. We have looked at a lot of similar elements between Excel and Power BI for both business intelligence and data analysis. Let’s recap these similarities.

First, we looked at the user interface of both tools, highlighting the ribbon in particular. That made for an intuitive user experience to find functionality, even if we hadn’t worked in that specific tool before. This can allow us to move seamlessly between Excel to Power BI. Then we looked at the Power Query editor and how the extract, transform, and load functionality, as well as the interface, is exactly the same between Excel and Power BI.

Once we’ve learned Power query in one place, we can easily use our skills in the other tool. After transforming data, we can model it in either the workbook data model in Excel or report data model in Power BI. This was made simple using the similar experiences of the model view or Power Pivot editor. Finally, to share our work, we visualized our data.

We built the same waterfall chart in both Excel and Power BI and saw how we can format our visual with on-object formatting as well as the full formatting pane. That’s it for this episode of Deeper Dive. Thanks for watching and we’ll see you next time.

Remote work has transformed the way many organizations are operating today. In this Deeper Dive, we take a closer look at what it takes to successfully manage hybrid teams comprised of some remote and some in-office employees.

This week, we’re shifting our focus again to talk about leadership, a critical discipline that stretches across nearly every type of business. Today, we’re gonna talk about managing hybrid work teams.

Welcome to another episode of Deepodai. A weekly show that pulls back the curtain on important finance, banking, and related topics, breaks down industry events, and keeps you in the know. We all know that remote workers transform the organizational environment. And while some companies brought everyone back to an office environment after pandemic lockdowns, Many organizations took the opportunity to downsize their office space and introduce new flexible working policies. A hybrid or remote work environment has presented companies with a host of new challenges.

One of the most significant challenges that companies operating a hybrid work environment will encounter is communication.

Even before companies adopted remote or hybrid working policies, communication was always one of their biggest challenges. Challenges impacting employee productivity and engagement.

In today’s episode, we’re gonna dig deeper into communication challenges faced by companies working in a hybrid space, and will identify specific strategies and approach that you may want to use to reduce the element of disconnect that your employees may encounter. Before we start to explore the challenges of communication for a hybrid team, Let’s look at what we actually mean by the term hybrid team.

Generally, hybrid teams are teams where you have staff who may be located at any on time in either the office location or a remote location.

That remote location may be their home, or there may be also staff who are located in either a satellite office or even in a different time zone.

At the heart of managing a hybrid team, is the awareness that office based staff and remote staff may have very different work experiences, and this can be a source of tension in the team.

You want to avoid a them versus us mentality and take actions that ensure you are being inclusive of all team members. Regardless of where they work. Do you have an imbalance or a preference for how you communicate?

So much of how we do business supported by the informal relationships and the communication that we have in the workplace. For example, informal communication takes place during and outside meetings, the conversations you have on the way to the meeting may be going up in the elevator first thing in the morning.

Remote staff have less opportunity to participate in informal communications that take place either during or outside meetings.

For those of your team working remotely or out of a different office, they may feel more isolated and have less connection than what you would normally have found in the more traditional work place setting. Whereas those staff who are mostly working in the office, they will have more opportunities to create those personal connections. With both leaders and coworkers.

Through those informal water cooler or lunch chats, and even sitting next to someone in the shared office space does provide the opportunity for informal conversation about non work topics as well as perhaps projects that you’re both working on. To ensure that your remote workers are not feeling excluded or else on the opportunity to build connection with others.

Think about how you can create some virtual connections beyond the regular meetings and check ins. Encourage other ways for staff to get to know one another, through examples such as virtual coffee breaks, maybe trivia nights. Randomized employee introductions, and other more employee focused celebrations.

As a leader of a hybrid team, You want to ensure that all your team members are included in communication methods.

So the aim is to normalize inclusive communication.

Here are four different ways where you can do that. Firstly, evaluate your various team communication methods to see how well they support everyone regardless of their location. And remember, individuals who work in different time zones need to have meeting arrangements that take into account their hours of work, which may not mean hosting team meetings at the same time each week. Particularly if they’re outside of normal business hours for some employees.

Consider rotating meeting times so you’re not burdening the remote employees with too many eye early or late sessions.

Secondly, think about different communication patterns. Consider what technology will ensure that your with everyone equally.

For example, if you’re having a meeting where there are more office based staff present than remote staff, ensure that you include your remote people fully by asking them questions before you ask your office based people. The third approach is to design a more one on one communication strategy for each member of your team based on their pre ask them what they need. What would they prefer? How can you support them in your communication?

And finally, fourth approach, consider how you can support informal communication.

You know, we’ve talked about the water cooler talk. Consider how you can support that among your What can you give permission on? Maybe lead by example with your behaviors and actions around setting up the informal communications.

As a leader, you are very influential. Your team take their lead from you. They notice what you do and what you don’t do. Here’s the opportunity where you can really lead by example in being inclusive with communication.

I hope that you’ve found this episode CFI’s deeper dive, interesting and informative.

If you want more information on how to manage teams in more detail, particularly high Brid teams, I highly recommend that you take CFI’s course on leading high performing teams. Thank you for listening, and we’ll see next time.

The Johari Model is based on the premise that communication and trust in a team are enhanced when people are open and disclose important information about themselves and how they work—as well as when people actively seek feedback from others.

This week, we’re shifting our focus again a bit to talk about leadership, a critical discipline that stretches across nearly every type of business.

Welcome to another episode of Deeper Dive, a weekly show that pulls back the curtain on important finance, banking, and related topics, breaks down industry events and keeps you in the know. Today we’re going to talk about the Johari window.

Have you ever been part of a team whose team members were all open and honest with each other? If so, then chances are that you worked extremely effectively together. You and your colleagues likely knew everyone’s strengths and weaknesses and enjoyed high levels of trust.

Such a positive working environment would help to create a high performing and close, tight knit unit.

The Johari window is a model that was created by psychologists Joseph Luft and Harrington Lingam to help people better understand their relationship with themselves and others.

This model is based on two ideas.

You can build trust with others by disclosing information about yourself, and with the help of feedback from other people you can learn more about yourself.

So each person is represented by the Johari model through four quadrants or window panes, and each of the window panes signifies personal information, feelings, motivation, and whether that information is known or unknown to either yourself or others.

And these are known as the public domain, the blind spot, the hidden region, or the unknown.

Most people use this model to develop self-awareness, but you can also use it to increase your leadership effectiveness, as well as using it as a personal development tool and to build better workplace relationships.

The ideal Johari window for a person has a large public domain, and the aim is to increase the size of this public domain through self-disclosure, shared discovery and feedback.

This is because, in general, the more that people know about themselves and one another, the more productive, cooperative, and trusting they will be when they’re working together.

A large public domain shows that you’re aware of your abilities, your feelings and behaviors, and that the people around you understand you well, thus improving your personal effectiveness.

So how can you put more information into that public domain?

Well, one thing you can do is let people know how you like to work, how you make decisions.

Is there a time of the day when you like to work uninterrupted, for example.

Think about information that you think others might find helpful to know about you so they can work more effectively with you and so that they can feel more comfortable communicating and interacting with you.

A colleague of mine in a company I used to work for recognized that he had a tendency to keep his thoughts and feelings hidden. He was quite a private person and kept to himself. However, he recognized that this did create a barrier between himself and his team.

So learning more about the impact of the Johari window, he decided to start opening up and start to share more about himself, what his values were, what his aspirations were. And this self-disclosure, this opening up created more trust between himself and his team, and as a result, their productivity and their effectiveness increased.

So let’s explore some benefits that the Johari window brings to leaders, enabling them to enhance their leadership effectiveness. The

first area is self-awareness. So the Johari window enables leaders to develop a clearer picture of their own strengths, their weaknesses and their blindspots.

By reflecting on their own behavior and seeking feedback from others, leaders can expand their self-awareness.

This increased self-awareness helps leaders to recognize and to leverage their strengths, while also addressing areas for improvement.

By understanding their impact on others, leaders can adjust their behavior and make more informed decisions.

So I had not been aware that my facial expression and body language sometimes send a different message to my team members than the one I’d intended. And this was a blind spot for me. So, for example, when I was thinking intently about something, I would frown. And this facial expression led my colleagues and direct reports to think that I was irritated with them or cross, and as a result they would hesitate to ask me a question.

So using the Johari window model to ask for feedback, I asked my colleagues to let me know when they were confused by my facial expression. Was I frowning? What was it telling them? So that I could adjust that or at least explain in the moment.

This self-awareness meant that I became much more conscious of my body language and my facial expression when I was thinking intently about something, and particularly if I was in a group where others might misinterpret this expression.

This improved my interactions with my colleagues as a result. The second area is building trust.

So trust is very much at the foundation of successful leadership. And the Johari window provides leaders with a framework to build trust by creating an open and honest dialog.

As leaders share more about themselves, including their values, their intentions and their fears, team members feel more connected and comfortable.

This mutual sharing deepens trust and encourages team members to reciprocate by sharing their own perspectives and experiences.

So the third benefit that we’re looking at here is increased self-confidence.

So the Johari window enables leaders to gain a clearer understanding of their strengths and capabilities. And as leaders become aware of the hidden talents and receive feedback on positive attributes, the self-confidence grows.

This increased self-confidence allows leaders to take risks and inspires their teams to achieve ambitious goals. The final benefit we’re going to look at today is conflict resolution. By encouraging open communication and understanding different perspectives, the Johari window supports leaders in addressing and resolving conflicts effectively.

By exploring and embracing the Johari window model, leaders can tap into their full potential. They can promote open and honest dialog and create a culture of transparency, trust and collaboration.

These benefits extend beyond individual leadership effectiveness and positively impact team dynamics, employee engagement and overall business outcomes.

The model promotes empathy and active listening, allowing leaders to find common ground, facilitate compromise and build stronger relationships within their teams.

I hope that you found this episode of CFI’s Deeper Dive interesting and informative,

and if you want to explore how to use the Johari window in more detail, I highly recommend that you take CFI’s course on leading with emotional intelligence and self-awareness.

You can also explore conflict resolution in CFI’s course on having a difficult conversation and managing conflict.

Thank you very much for listening. We’ll see you next time.

Explore the importance of both positive and constructive feedback, dig into the E2C2 framework, and more.

This week, we’re shifting our focus a bit to talk about leadership, a critical discipline that stretches across nearly every type of business today. Specifically, we’re here to talk about a subject that gives many leaders pause for thought, giving feedback.

Welcome to another episode of Deepdive. A weekly show that pulls back the curtain on important finance, banking, and related topics, breaks down industry events, and keeps you in the So what is feedback? Well, feedback in the workplace is any information regarding performance, skills, or the ability to work within a team. Its purpose is to enable understanding and promote actions that either correct, ineffective, or poor performance, or maintain and strengthen a or standard of behavior.

This is important as it enhances personal and professional growth in individuals.

Feedback can be positive or negative. It can help to break bad habits, reinforce positive behavior, and enables teams to work more effective together.

So what are the benefits of delivering feedback?

Well, delivered effectively, feedback can improve employee morale and engagement It can reduce confusion regarding expectations and current performance.

How many times have you needed to give constructive feedback to a report, and they seemed to leave with the impression that there was nothing that needed changing.

Feedback can also provide a new perspective, and it gives valuable insight to the person receiving feedback.

It can also positively impact an individual’s behavior.

So feedback is an opportunity to give information to another person that makes it clear what your expectations are and what you need from them. Feedback promotes honesty and trust, and a regular feedback conversation between a manager and a direct report can build trust if it’s given in the right way. So how can you make giving feedback a more comfortable experience?

Both for you and the person you’re delivering the feedback to. There’s a great tool that can help you to remember the key points and to keep your focus in the conversation on track.

Is called e two, c two, and that’s evidence, effect, change or continue, and commitment So the first E is evidence.

You need to ensure your feedback is based on fact.

So generalities are not effective. And in some cases, they can actually be very damaging.

It’s important that you’re actually very specific in the information you are giving to someone.

It should relate to what you can see or hear about that person’s behavior rather than making assumptions and interpretations.

For example, if you’re delivering feedback about specific errors in a report, then you need to be able to present that information and show the errors.

So let’s look at an example. You have an employee Joe who is constantly late for work, and you need to have a conversation with him about this. You want to provide evidence. So in this case, refer to the actual days that Joe was late and by how many minutes, So for example, you were late on Monday, Wednesday, and Friday last week.

You didn’t log on until half an hour after you were due to start. I have the timesheets here that recorded that. The second e is effect. You need to ensure that you can communicate the impact or the effect of it is that you are talking to your employee about.

So effective feedback needs to focus on the outcome, the impact of the behavior or the action.

For example, when you don’t deliver your work on time because you cannot find the materials, it impacts the team’s work.

Effective feedback should be about what the individual did rather than who the individual is.

So saying you are so disorganized, is not helpful, and is very personal. It will result in the person feeling defensive.

So stating it instead as I don’t see you planning your work in a way that enables you to deliver your work on time. It’s more constructive and helps the person see the situation in a way that they can relate to. So thinking back to what we would say to our employee, Joe, about the effect of his lateness, You could say. When you’re late for work, Joe, it puts additional pressure on the team. It means other people cannot log off from their shift, and finish their work as they are waiting for you. The first c is change or continue.

The feedback should be about things that a person can change and improve on rather than something that’s outside of their control. So it needs to be relevant to the individual job so they can actually make the connection between their performance and the outcome on their ability to complete the work. Feedback needs to be constructive. It needs to be focused on how performance can be improved. What needs to be different? What needs to change, what will it look like?

Getting an individual input to what needs to change is a key aspect to seeing improvements individuals are much more likely to follow through on changes that they themselves have identified.

And remember that feedback can also be positive.

What do you want the person to continue doing because it made such an effective outcome?

What behaviors did you see that impressed you?

In our example with Joe, his ability to start work on time is within his control. But he probably has to make some other changes, like setting his alarm earlier, or not planning activities before work, that means he can’t be ready on time. So you might ask him, Joe, what can you change or do that will mean you can start work on time. Let’s talk about that.

The second c is commitment.

When you are identifying changes with an individual, you are identifying things that will be different because of the conversation.

And therefore, you need to document it, including getting the individual’s agreement or commitment to what was discussed, the actions to be taken, and the timing of any follow-up reviews. This is also important in case it leads to any performance management or disciplinary actions.

So let’s look at how this part of the conversation might go with Joe.

So, Joe, we’ve identified some great changes that you’ve committed to which should mean you can start work on time. Can I get your commitment that you will now make those changes? And we will see your timekeeping improve.

Using a feedback tool like e two c two gives you a structure for the conversation, like the one we’ve just described with Joe. This helps you to stay on track.

I hope that you found this episode of CFI’s deeper dive interesting and informative.

If you want to explore how to give feedback in more detail, I highly recommend that you take CFI’s course on giving effective feedback.

Thank you very much for listening. We’ll see you next time.

AI is the hottest topic in tech right now—but what impact are tools like ChatGPT having in the finance industry? How are they making day-to-day work more efficient? What type of regulations might be needed? Check out this episode of Deeper Dive to learn more.

Hi and welcome to CFI’s Deeper Dive.

The weekly show where we delve into the fascinating world of financial markets,

providing you with the invaluable insights you need to stay ahead of the curve.

Now, in 2023, it’s been impossible to overlook

the profound impact of artificial intelligence.

With the release of Chat GPT-3 and then -4,

A.I. has become the focus of our news and we’ve been drawn

to its potential applications on our daily lives.

So what exactly is artificial intelligence?

And why has it become the dominant topic that everyone is talking about?

And critically,

what does it mean for professionals in the financial services industry?

I’m Ryan Spendelow, Vice President of Content here at CFI.

And in this week’s Deeper Dive episode, we will explore

the potential impact of A.I.

and how it relates to you.

Let’s start

by clarifying what we mean by artificial intelligence.

A.I. refers to the use of computer systems or machines

that are capable of performing tasks that typically require human intelligence.

These systems rely on algorithms designed

to replicate the workings of our brains, enabling A.I.

to acquire knowledge, recognize patterns,

make decisions, interpret data and images.

The ability of A.I.

to process vast amounts of data, to automate tasks,

provide accurate predictions, and enhance decision making processes,

make it immensely valuable in the finance industry.

However, it’s useful to note that A.I. is actually an umbrella term

that encompasses different types of technology.

So let’s dig a little deeper.

At the forefront, we have narrow A.I., also known as weak A.I.,

which excels at performing specific tasks.

Narrow A.I.

has already permeated our daily lives.

If you’ve played chess against a computer or interacted

with Alexa to manage your Amazon account or used facial recognition

just to unlock your smartphone, you’ve experienced narrow A.I.

first hand.

Many financial institutions use narrow A.I.

systems for fraud detection purposes.

These systems analyze transaction data,

spending patterns, user behavior to identify and flag

potentially fraudulent activities, reducing the risk of financial losses.

At the other end of the spectrum, we have general A.I.

also referred to as strong A.I.

or artificial general intelligence AGI.

General A.I.

possesses the ability to perform any intellectual task that

a human can accomplish.

It can understand and learn from diverse datasets.

It can solve complex problems.

It can exhibit creativity, adapt to new situations,

and effectively communicate in natural language.

Although General AI currently exists as a hypothetical concept,

its realization would undoubtedly have profound impacts on various domains.

It could revolutionize scientific research,

enhance health care diagnostics, and certainly assist in financial analysis

by offering insights and recommendations based on its profound understanding

and analysis of extensive datasets.

Interestingly, many experts believe that Chat GPT represents

a significant step towards general A.I..

But before we delve deeper into Chat GPT, let’s clarify some A.I.

relevant terminology.

There are different types of A.I., each with its unique applications

and characteristics.

Expert systems

are computer based systems that utilizes knowledge and reasoning

to simulate the decision making abilities of human experts in a specific domain.

A finance domain example is a credit scoring system.

Robotics refers to the application of mechanical devices,

often equipped with artificial intelligence

that are designed to perform various tasks

autonomously without human guidance.

While not exactly mechanical in nature,

robotic advisors or robo advisors use algorithms

and A.I. to provide automated investment advice.

Natural Language Processing or NLP

is a field of artificial intelligence that focuses on enabling computers

to understand and interpret and generate human language

in a way which is meaningful and useful.

NLP techniques

can be used to analyze and interpret public sentiments from news articles

and social media posts, providing financial analysts

with more data points from which to make investment decisions.

Compuer vision is where computers are able to understand

and interpret visual information from images or videos.

Financial institutions deal with large volumes of paper documents

such as invoices, receipts, statements,

computer vision technology can be employed to automate

the extraction of relevant information from these documents

reducing manual effort and increasing efficiency.

Machine learning is a branch of artificial intelligence

that enables computers to learn from data and improve performance

on specific tasks, but without being explicitly programed.

Chat GPT is an example of a machine learning tool.

It’s based on computer systems called neural networks,

a subset of machine learning, which creates networks of nodes loosely

modeled on the neurons in the brain to simulate the way the brain functions.

Chat GPT is trained on massive amounts of data

to generate human like responses to natural language queries.

This training on massive amounts of data is called deep learning.

This type of A.I.

is already extensively used in finance.

Machine learning algorithms can be used to support automated trading strategies.

It can be used to detect fraud in real time

by analyzing transaction data,

user behavior and historical patterns.

Machine learning is also used to analyze

and assess risk factors and optimize risk models.

Aiding portfolio management,

asset allocation and risk prediction.

Okay,

now we know what A.I. is and we are familiar with

some different ways A.I. is being applied in finance,

I want to shift the discussion.

Chat GPT’s arrival and the multitude of other A.I. tools that have been launched

in the last 12 months has been nothing short of seismic.

It’s impossible to escape the headlines, such

as being the fastest growing app ever.

To the growing impact it’s having on the stock prices of tech firms

that are investing in this type of technology.

To the broader debate around the ethics of such technology.

To the way it’s going to impact the world around us.

And when it comes to the arrival of potentially transformative technology,

people will both be excited and anxious at the same time.

With A.I., the balance between excitement and anxiety is more towards

the anxiety side of the spectrum for many people.

This differs from other recent

technological milestones like the Internet or smartphones.

And what’s driving this anxiety?

Well, for finance professionals,

one major source of anxiety is the fear that A.I. will lead

to finance roles being replaced en masse by A.I..

And this is totally understandable, given

all the headlines around A.I..

However, there are some pretty major hurdles that A.I. must pass

before we get to the stage of mass job losses for finance professionals.

A.I. will need to be regulated

and the EU has already proposed laws on the use of A.I. in banking.

There are ethical issues. there are reliability issues.

And the security issues around A.I.

will all need to be resolved.

And the resolution of these issues will probably need to evolve into global A.I.

frameworks.

However, this is not to say that A.I.

as a tool for people working in finance, isn’t here to stay.

It is.

And so this does raise the question: what can we do as finance professionals

to ensure we stay relevant in an industry which has so many use cases for A.I.

and likely will be even more impacted by A.I.

in the coming years?

Well, let’s start with five

things that A.I. can’t do or can’t do very well.

A.I. models lack common sense and critical thinking skills.

A.I. models struggle to understand context.

A.I. models do not empathize well with people’s emotions and feelings.

A.I. models are not creative or imaginative

as pre-trained models like Chat GPT

combine existing knowledge,

although they can generate innovative ways of expressing this knowledge.

Finally, A.I. models

do not possess real time learning capabilities, limiting their ability

to adapt quickly and dynamically to rapidly changing environments.

An appreciation of these shortcomings will help answer our question

on what we can do as professionals to stay relevant in an A.I. world.

Firstly, take the time to become more technology literate.

This will increase your chance of being successful

in using, understanding and navigating A.I. technologies

effectively and responsibly.

My next tip is: while technology like Chat GPT is great

for certain tasks, such as summarizing large amounts of data,

what it doesn’t do so well is critical thinking and problem solving.

Working on your critical thinking and problem

solving skills will enable you to leverage A.I.

as a tool and elevate you beyond what A.I.

can currently do.

Improving these skills involves being able

to make decisions based on evidence and logic.

You can improve your critical thinking skills:

ask questions, actively listen,

practice considering other points of view and learn to investigate issues.

You can also improve your

problem solving skills: practice defining problems,

try to generate new solutions by being creative and thinking outside the box,

and after solving a problem, take time

to reflect on the process and the outcomes.

My third tip: take time to develop

your emotional intelligence skills.

EQ skills such as self-awareness, empathy and social awareness are valuable

in professional settings as they contribute to effective communication,

relationship building, decision making, and your overall well-being.

Finally, try to become more resilient and agile.

While these have become buzzwords in today’s corporate culture,

they do play a critical role for success in an A.I. dominated world.

Resilience is your ability to bounce back, adapt and recover

from setbacks, challenges, or stressful situations.

Agility at work refers to your ability to adapt, respond

and thrive in rapidly changing or unpredictable circumstances.

By cultivating your resilience and your agility,

you can position yourself as a valuable contributor in a workplace driven by A.I..

You can harness the benefits of A.I. technology while leveraging

your unique human capabilities such as critical thinking,

emotional intelligence, creativity and problem solving.

So, A.I. is here to stay, and we may have to adapt to stay relevant.

Are you ready for the challenge?

As we start the month of May and summer approaches in the northern hemisphere, many capital markets participants start thinking ahead to summer holidays and you begin to hear the phrase “sell in May and go away” being uttered on trading floors across investment banks around the world. So what exactly does “Sell in May and go away” entail and is there any reason to heed that advice?

As we start the month of May and summer approaches in the Northern Hemisphere. Many capital market participants start thinking ahead to summer holidays and you begin to hear the phrase sell in May and go away being uttered on trading floors across investment banks around the world. So what exactly does sell in May and go away entail? And is there any reason to heed that advice?

I’m Andrew Loo, Vice President of Capital Markets here at CFI. And in this week’s Deeper Dive, let’s look a bit deeper into this phenomenon Sell in May and go away is a well-known adage in the financial world, which suggests that investors should sell their stocks in May and buy them back later in the year. This strategy is based on the historical trend that stock markets tend to underperform during the summer months, typically between May and September. While returns of the fall and winter tend to be higher, As a matter of fact, this term has been used for many decades.

Originating in London’s financial district, among the stockbrokers and bankers, the original phrase was Sell in May and go away. Come back on scene ledgers day. A horse race held in Doncaster dating back to the 1700s that’s held in September of every year in the U.S., Traders have adopted a similar strategy that spans the time between Memorial Day and may and Labor Day in September.

So let’s talk about why traders on both sides of the Atlantic believe this phenomenon to be true. The first and most often quoted theory is that with summer holidays in many parts of the world, both by side investors and sell side traders take their well-deserved breaks to be with their families, resulting in less market liquidity and overall lower trading activity. That certainly holds true from an eye test on this Refinitiv chart. We’re looking at the daily traded volume for all U.S. equity market exchange traded instruments, which are mostly stocks without fail.

The lowest volumes always happened in the summer. However, as the market moves to more program trading called algorithmic or algo trading for short, the fact is that traders and fund managers being in the office may not be as important as it once was. You can see that the volumes may drop in the summers, but over the last few years, the low points called valleys are getting higher and higher. Another theory is that companies may be less active in terms of news, announcements and other reports over the summer months, which also means less volatility.

However, a quick check of the VIX index by the CBOE, a major leading indicator of market volatility, doesn’t seem to indicate much seasonality in thinking about it logically. Companies announce quarterly earnings throughout the summer, so there really shouldn’t be much of a difference. However, notwithstanding these two theories, since 1945, the S&P and its predecessor index posted a cumulative six month average gain of 6.7% in the period between November to April, compared to an average gain of only around 2% between May and October.

The S&P 500 also only typically generates positive returns roughly two thirds of the time from May to October, while that percentage rises to 77% from the period from November to April. Does this mean investors should blindly follow this old adage? Well, we think it’s perhaps better not to think of this phenomenon as a fixed rule, but a trend that tends to happen over the summer months in 2023. Blindly following this trend might be even more dangerous than most, given the numerous potential risk factors that exist this year In potentially negative market themes, we continue to have the geopolitical overhang from the Russia and Ukraine war, as well as the regional banking crisis that’s slowly unraveling in America.

Whether it’s an issue such as duration, mismatching, like we saw it as VB illiquid lending to crypto based businesses like we saw at Signature Bank and liquidity concerns like we saw in First Republic just this past week. It seems so far that the FDIC and the U.S. government have been able to control the fallout. Now, there are also positive global market themes as well, namely the potential slowing down of Fed rate hikes as the Fed and other global central banks seem to be gaining an upper hand in their inflation fight. There are also some pleasant surprises in global earnings for many companies, such as Apple’s recent announcement last week on strong iPhone sales, as well as potential market moving announcements coming from Amazon Alphabet and JPMorgan Chase, who rescued the aforementioned First Republic Bank.

So what should you do? An investment strategy always starts with the risk tolerance and time horizon considerations. If you are able to weather some potential volatility and have a longer term investment horizon, then perhaps the smartest play is to just simply stay invested as market beat on Nasdaq JD.com recently rose sell in May is an exercise in market timing and of selling on a certain month is all it takes to be successful.

Why wouldn’t everyone simply just do it now? If you’re being paid to actively trade and you’re interested in learning about how the beliefs of large amounts of investors might turn things into reality, I would highly recommend you look at as a course on behavioral finance, which talks about the psychology that drives capital markets. If you’re interested in furthering your trading skills, we also have specialized courses such as our new Equity Trading Fundamentals Course, which offers a hands on simulation component as well. I hope you found this episode of CDFIs Deeper Dive, interesting and informative.

Thank you all for listening and we’ll see you on the next CFI Deeper dive.

Today’s episode takes a close look at the similarities, differences and use cases for two often-confused terms — business intelligence and data science.

Just this past Sunday, several members of the OPEC+ cartel announced that it will voluntarily cut a further combined 1.16 million barrels per day of production, starting in May and lasting until the end of 2023.

In this episode of CFI Deeper Dive, we’ll go over some background information on Credit Suisse, the timeline of key events that lead to them being sold to UBS, and how the new UBS is setup in a strategically important position to change the landscape of one of the fastest growing sectors in finance.

Today, we talk about something that’s been making headlines lately—Additional Tier 1 (AT1) bonds.

The big news in the financial markets this week has been the closure of Silicon Valley Bank (SVB).

Today we talk about the implications of the U.S. debt ceiling.

Today we talk about commercial banks, and how they’ve been making lots of money as of late.

Today we talk about the FOMC and the Fed meeting minutes.

Today we talk about the U.S. CPI results and inflation.

February

This week while in line to buy a coffee, I couldn’t help by overhearing people ahead of me talk about ‘where’s this recession? When is it going to happen? That’s all people keep talking about, but I don’t get it’.

Today we talk about Jerome Powell’s tone at the most recent U.S. Federal Reserve meeting where interest rates were hiked by 25 basis points.

February 9, 2023

Hello, and welcome back to CFI Deeper Dive—a weekly show where CFI dives into the concepts behind financial market events to help you stay ahead of the curve.

Just last week, the Federal Reserve hiked interest rates by 25 basis points resulting in a target range of 4.5%-4.75%, the highest since October 2007.

Jerome Powell spoke with an optimistic tone and said: “We can now say I think for the first time that the disinflationary process has started” (source). It’s important to note that the Fed still plans to hike rates in the future, with the market pricing in a 98.5% chance of a 25 basis point hike.

Here we can see a notable jump in the S&P 500, and AGG following the meeting. AGG is the ticker for the iShares Core U.S. Aggregate Bond ETF which holds a variety of different fixed-income offerings. What’s interesting is that both the S&P and AGG rallied from the Fed meeting, but typically stocks and bonds are inversely correlated.

In this CFI Deeper Dive, we’ll discuss how the market has reacted in the past to an optimistic Fed tone, and also why bonds have done well while risk assets rallied.

In 1996, when Federal Reserve Chairman Alan Greenspan took an optimistic tone about the U.S. economy, it took several years for the central bank to transition to a more neutral policy outlook.

This was in part due to the strong economic growth and low unemployment that the U.S. was experiencing at the time. However, as the economy started to cool and the housing market showed signs of stress, the Federal Reserve shifted its tone to a more neutral one and eventually started to raise interest rates to keep inflation under control.

The next chairman of the Federal Reserve in 2006 was Ben Bernanke. When he took an optimistic tone on the U.S. economy and indicated that the central bank would continue to raise interest rates, the stock market reacted positively. This was in part due to investors seeing strong economic growth and low unemployment as a sign of a healthy economy recovering from the financial crisis. It took several years for the central bank to transition to a more neutral policy outlook.

Another example was in 2014 when Federal Reserve Chairman Janet Yellen was appointed. During her tenure, she took an optimistic tone about the U.S. economy and signaled that the central bank would start to wind down its massive bond-buying program. The stock market reacted positively to this news, as investors saw it as a sign that the U.S. economy was on a path to recovery and that the central bank was confident in its ability to manage monetary policy.

As we can see, the transition period from an optimistic to a neutral policy outlook has taken a few years in the past. Based off what happened in the past, it’s possible that the U.S. Fed will maintain a positive outlook on the economy for the foreseeable future.

It’s important to note though that changes in global economic conditions, geopolitical events, and monetary policy decisions can quickly change this timeline. Even things like corporate earnings could impact markets, and in turn the Fed’s economic outlook.

Contrary to common belief, it’s also worth noting that while stocks and bonds are typically negatively correlated with each other, this relationship does not always hold.

This relationship occasionally breaks down during periods of market volatility or economic uncertainty driven by changes in market sentiment, economic outlook, and monetary policy. Jerome Powell’s optimistic tone must be seen through this lens – resulting in capital inflows into both the stock and bond markets.

If you’re interested in learning more about economic events, monetary policy, and central banks, I would highly recommend you take our free course called Economics for Capital Markets: https://corporatefinanceinstitute.com/course/economics-for-capital-markets/

Thank you for watching, and we’ll see you on the next CFI Deeper Dive.

Today we talk about iBuying, and how this new technology is changing the way people buy and sell homes.

February 2, 2023

Hello, and welcome back to CFI Deeper Dive.

A weekly show where CFI dives into the concepts behind the financial market events to help you stay ahead of the curve.

One of the interesting themes from COVID-19 and the resulting shutdown was the housing market, and specifically what was happening in the U.S. markets. Whether it was the stimulus that the government was providing or whether workers found that they could work-from-anywhere or whether we had very accommodative interest rates and high inflation fears, home prices surged in the U.S. (find Refinitiv median home price chart). However, since the end of the pandemic, employers are starting to mandate employees go back to the office, mortgage rates have climbed and the stimulus tap has been turned off, which has led many market watchers to worry about housing prices in the U.S. (show article headlines from Refinitiv).

Recently, market watchers have turned their attention to how iBuyers have skewed that market even more and how this may result in increased risk to the market. For those of you who aren’t familiar with the term, iBuying and iBuyers are relatively new to the world of real estate. But they are making a big impact on how people buy and sell homes. iBuying stands for “instant buying” and refers to the process of using technology to quickly and efficiently purchase homes without the need for traditional real estate agents or intermediaries. iBuyers are companies that use iBuying technology to make these purchases, typically larger real estate companies. And behind those companies are large private equity backers and other institutional investors.

So what do you know about iBuyers? Stay tuned as we take a deeper dive into the world of iBuying.

Firstly, iBuying is great for sellers looking for a fast, convenient, and hassle-free way to sell their homes. They may be facing financial difficulties, need to sell their home quickly for personal reasons, or simply prefer the speed and efficiency of iBuying. With iBuying, you can receive an offer for your home within 24 hours, and the sale can be completed in as little as a few days. In contrast, traditional home sales can take several months to complete, and homeowners must pay commission fees.

Additionally, if you have an older home that may require costly repairs or renovations, iBuying may also be a good option, as iBuyers typically purchase homes as-is.

The process of iBuying is simple and straightforward. First, a seller provides information about their property to the iBuyer. This information may include the address, square footage, number of bedrooms and bathrooms, and recent sales prices of similar homes in the area. The iBuyer then uses algorithms and data analysis to determine the value of the home and make an instant offer to the seller. If the seller accepts the offer, the iBuyer arranges for the purchase, typically with cash, and takes care of all the necessary paperwork and closing costs.

Although iBuying seems like a great idea, the predatory nature of the business model may have contributed to rising house prices. iBuyers like Zillow, Redfin and Opendoor distorted the market with their piles of cash and forced out buyers and smaller investors.

Also, iBuyers purchasing and selling these houses in bulk have some control over setting the market price to make a spread. For example, if Zillow purchased a large amount of houses for $500k each and then bought a few more for $550k, they could set the selling price for $550k or higher.

All this sounds like a great business model during an uptrend in housing prices, but as the housing market has fallen, the opposite also holds true.

In addition to this risk for PE and VC backers of the iBuyers, there is also the risk of further contagion to the capital markets. When an iBuyer purchases a home, it typically holds onto the property for a period of time before reselling it. During this period, the iBuyer can create securities backed by the real estate assets it holds, and then sell these securities to investors. The creation of securitized products results in new sources of funding for the iBuyer, which in turn can be used to purchase more homes. This creates a self-sustaining cycle, where the iBuyer can use the funds generated from the sale of securities to purchase more homes, and then create more securities, and so on.

However, investors in these capital market instruments are exposed to the risk of declining housing prices as the asset values backing their investment could deteriorate, as well as increased risk of defaults of the borrower. Existing home sales in the US, shown by the blue line, are down over 11% in 2022 from the peak in 2022 and while the Fed continues to hike, shown by the white line, mortgage rates look set to continue going up.

So clearly the risk has increased and the iBuyers are feeling the pain (Reference to your story on RealSure). We won’t know if this may lead to larger issues like those that the U.S. subprime housing crisis created in 2009 but remember that while capital markets may not always repeat the same past mistakes, they do often rhyme…

If you’re interested in learning more about the securitization process and its role in the world of finance, make sure to check out our course called Securitized Products (Part 1): https://corporatefinanceinstitute.com/course/securitized-products-part-1/

Thank you for listening, and we’ll see you on the next CFI Deeper Dive.