Joseph Omokafe

Data Analyst || Educator || Open to internship program || problem solving and critical thinking || 14th Nacos president Tasued chapter

[Joseph Omokafe @ExcellenceJose4]

@iam_daniiell Thank you

[Joseph Omokafe @ExcellenceJose4]

@JA_Olaoye This make more sense, and it will expose one into how logistics, terminal, port data look like, this will make one to see a close real life data is and how important the end product of the analysis matters to decision making.
Good boss

[Joseph Omokafe @ExcellenceJose4]

@Kirby_Sand Hey @Kirby_Sand i just fill it the application right now

[Joseph Omokafe @ExcellenceJose4]

@starboy_abefe Sharp
You get am

[Joseph Omokafe @ExcellenceJose4]

@DuruOzii Internship

[Joseph Omokafe @ExcellenceJose4]

@starboy_abefe Any average person going into tech will say I want to learn "data analysis", I was training a student in where I work, she told her dad, we are not doing anything, when I am busy teaching her the maths and stats in depth, she says na dashboard be koko.
The thing off me.

[Joseph Omokafe @ExcellenceJose4]

@Rita_tyna @DabereNnamani @som_nnamani @ezekiel_aleke
#fraud #detection #analysis

[Joseph Omokafe @ExcellenceJose4]

🚨 $2.83M lost to fraud — and the real story is in the data.
I built a full fraud transaction dashboard for a bank project, and the numbers are stark.
Here's what the data revealed:
📊 8.01% fraud rate — up month-over-month, with fraud losses climbing 9.74%

[Joseph Omokafe @ExcellenceJose4]

The dashboard surfaces these patterns across credit tiers, channels, regions, and transaction types enabling the fraud team to move from reactive investigation to proactive targeting. What fraud metric do you find most underused in financial services dashboards? Drop it below. 👇

[Joseph Omokafe @ExcellenceJose4]

@JA_Olaoye A freelance work

[Joseph Omokafe @ExcellenceJose4]

@JA_Olaoye Am here

[Joseph Omokafe @ExcellenceJose4]

@OnwuzirikeP2 @Rita_tyna @JA_Olaoye @ezekiel_aleke Alright thank you

[Joseph Omokafe @ExcellenceJose4]

Working on the Fraud analysis dataset, I hit a stumbling block, noticed that the churn rate is 70.2% and the loyal rate is 98.6%. so I check my query to view a single customer details and I saw only him is "At risk" and "Loyal".

@Rita_tyna @JA_Olaoye @ezekiel_aleke

[Joseph Omokafe @ExcellenceJose4]

@OnwuzirikeP2 @Rita_tyna @JA_Olaoye @ezekiel_aleke Yes
Though i use the Python to update the table to have 1 and 0, easier to get fraud count, which I load the table into MySQL

[Joseph Omokafe @ExcellenceJose4]

@JA_Olaoye It was the second query, I use to check individual customers churn status where all have several different churn status

[Joseph Omokafe @ExcellenceJose4]

@JA_Olaoye Haaaa
What to do na.
Is to export it

[Joseph Omokafe @ExcellenceJose4]

@JA_Olaoye Hi