AYOD3JI

Professional Accountant | Business & Data Analytics | Academic advisory and consulting.

[AYOD3JI @vincyble]

Our sight senses are same but our cognition makes the difference.
Our sense of hearing ain't different but we hear what he choose to hear.
There is more to us as human but the answer lies within.

[AYOD3JI @vincyble]

@EmekaAmakeze @jon_d_doe E go enter the next book fictitiously 😂

[AYOD3JI @vincyble]

@HRRonald001 Interested

[AYOD3JI @vincyble]

@table_shaker_ @DowloaderBot

[AYOD3JI @vincyble]

@Nedu_brazil01 @DowloaderBot

[AYOD3JI @vincyble]

@victorogb @PoojaMedia It's not enough reason for such performance, my bro.
It was more of a technical error than the FA's fault.

[AYOD3JI @vincyble]

@MrCharlesky Interested

[AYOD3JI @vincyble]

@BenoHr80463 Interested

[Queen Hadassah❤😌🎀 @queenhadassah24]

Nudity isn’t a flex
Modesty is 🔥 🔥
Modesty isn’t shabby 🥹

[AYOD3JI @vincyble]

@Ahmed___khaan @VidDownBOT

[Akíntúndé Babátúndé @olorunwababs]

AI, Africa, and the politics of repair

I joined a panel at LSE today on “Who Writes the Algorithm: AI, Africa and the Politics of Repair.” Good conversation. But I left feeling we are still not stating the harder implications clearly enough.

Who writes the algorithm matters. But the more structural question is: whose knowledge was the system built on? Because the algorithm is not just code. It is the outcome of training data, and that data reflects specific histories, geographies, and power structures.
Africa has over 2,000 languages, most of these are absent from the datasets underpinning today’s AI compared to western data. What these systems know about Africa was learned largely through external narratives and external priorities. That is not a technical gap but a structural one.

Three things stayed with me from the conversation.
Africa plays a central role in the AI value chain through mineral extraction but captures very little downstream value. African journalism , rigorous, fact-checked, locally grounded, is training AI systems while major licensing deals flow almost exclusively to Western media institutions. And millions across the continent are forming their understanding of AI through constrained, outdated interfaces — shaping not just usage but governance conversations.

One tension worth naming is that much of Africa’s AI governance work is funded, directly or indirectly, by the companies those frameworks are meant to hold accountable. That helps explain why policy conversations emphasise opportunity while staying quiet on extraction and dependency.

Repair, if we take it seriously, is not inclusion or capacity building. It is about ownership, governance, and distribution. It means Africa moving from being a source of raw materials and raw data to being a site of decision-making and value creation.

That is what the politics of repair actually demands.

I will write a more expanded article on this in the coming days.

[AYOD3JI @vincyble]

@Johnsontaiwo_ ROADMAP

[AYOD3JI @vincyble]

@olalakes911 @Hardheyjhoke @BSAT_Properties omo owa....that should be Ijesha.
omo owa, omo obokun

[AYOD3JI @vincyble]

@shimataver @ElizMatinz @boniface_jrn Still on netflix

[AYOD3JI @vincyble]

@shimataver @boniface_jrn First watched this movie 2018 or thereof.
I've watched it at every opportunity I get.
Can nvr get tired of the movie

[AYOD3JI @vincyble]

@Johnsontaiwo_ ROADMAP

[Johnson Taiwo 🇬🇧 @Johnsontaiwo_]

If you're a Data Analyst, Risk Analyst, or aspiring FinTech Analyst who wants to move from reporting dashboards to making financial decisions, read this:

Dashboards are not enough.
Modern financial institutions promote analysts who can:
• Quantify credit risk
• Detect fraud trade-offs
• Model expected loss
• Optimise portfolio returns
• Allocate capital responsibly
Most analysts learn tools.
Very few learn capital thinking.

So I built the FinTech Capital Intelligence Blueprint to move you from metric reporting to capital decision intelligence.

A system with two parts:
>> 1. Finance & FinTech Analytics Learning Framework
Learn how institutions actually operate:
• Financial system mechanics
• FinTech unit economics under risk
• Governance & regulatory thinking
• Capital allocation logic
• Executive financial communication

>>2. The 12-Week Practical FinTech Analytics Roadmap
Build 10 real-world projects:
• BNPL unit economics
• Payments revenue intelligence
• Credit risk modelling
• Fraud optimisation
• Portfolio stress testing
• Capital allocation simulation
• LTV & churn economics
• AML optimisation
• Credit limit strategy
• Revenue forecasting

This is not decorative analytics.
This is institutional-level financial thinking.
If you want the roadmap:

1️⃣ Like
2️⃣ Repost
3️⃣ Comment ROADMAP
4️⃣ ‼️Send me a DM, and I’ll share it.

[AYOD3JI @vincyble]

@report_with_ai Digital Forensics

[AYOD3JI @vincyble]

@hannytalker Milk

[AYOD3JI @vincyble]

@SHEAYI @xdownloaderbot

[EKÙN II🐯🐅(Tiger de 2nd) @ekun_II]

I will say this again, don’t do life alone!!! As a man, have a band of boys or men of common values and like minds!!! Especially Nigerian men, na Naija boys get update for hand oo!!