Raj Agrawal

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Seven Ways To Predict Indian Bank Trouble. All Seven Failed. So I Built Bank Docket

August 22, 2026 by Raj Agrawal Leave a Comment

In September 2019, PMC Bank customers were suddenly told they could take out only ₹1,000 from their own accounts. People lined up outside branches with their passbooks. Everyone asked the same thing: how did nobody see this coming?

That stuck with me. If the warning signs were public, maybe a computer could spot them early. So I decided to try.

The question

Can you tell which Indian bank will get into trouble, using only information that’s free online? By “trouble” I mean an RBI penalty, a SEBI order or a cyber security incident in the next two weeks.

What I did

I collected public information on 25 Indian banks, big and small: RBI notices, SEBI orders, stock exchange filings, court cases, enforcement agency news, cyber security alerts and news stories. That came to about 4,600 documents, each linked to its bank and its original source.

Then I tried seven ways to predict trouble:

  1. Counting. Are there more documents about a bank than usual?
  2. Counting by source. Are they coming from the regulator, the courts or the press?
  3. Counting by type. More penalties? More court cases? More complaints?
  4. Reading for meaning. A small AI reads the documents, and simple maths looks for warning signs in what it read.
  5. Word spotting. Do certain words show up before trouble?
  6. Learning from examples. Show the AI a few past cases and let it learn from them.
  7. Asking an AI. It reads a bank’s recent documents and answers yes or no: is trouble coming?

Before the final tests, I wrote down the rules and didn’t change them afterwards: what data to learn from, what data to test on, how to score, and when to stop. If nothing did clearly better than guessing, I would stop trying to predict and build something else. I did this so I couldn’t fool myself. When you really want to find a pattern, it’s easy to see one that isn’t there.

The results

None of the seven did better than guessing. Most did slightly worse. That one hurt a little.

Here are the scores, out of 100. Higher is better. Guessing already scores about 26, because trouble is rare. To count, a method needed 31.

MethodScore (out of 100)Result
Just guessing25.9The score to beat
Counting (all three ways)24.3Worse than guessing
Reading for meaning26.0Same as guessing
Word spotting25.9Same as guessing
Learning from examples24.5Worse than guessing
Asking an AI24.6Worse than guessing
Needed to pass31.0None came close

Even when I looked at one type of trouble at a time, nothing reached the bar. So I stopped.

I even tried giving the methods the news from the same day the trouble happened. They still couldn’t pick out the right banks.

Would a bigger AI have done better? Probably not. Two Bank of England researchers found that small AI models with simple maths usually beat big AI models when there are only a few examples to learn from, which is the case here.

In short

With public information alone, I couldn’t predict which Indian bank would get penalised in the next two weeks. Not by counting, not by reading, not with AI. Maybe someone will find a way one day. With this data, I couldn’t.

So I built Bank Docket

If I couldn’t predict trouble, I could at least keep a clear record of it. That’s Bank Docket: a free website that shows what regulators have done to each Indian bank, with a link to the source for everything.

It started as 25 banks for the experiment. Today it has:

  • 467 banks. Government, private, small finance and payments banks, plus hundreds of district and state cooperative banks. Cooperative banks are where depositors have been hurt most often.
  • Nearly 13,000 documents from the RBI, SEBI, CERT-In, the Enforcement Directorate, CBI, PIB, the courts and the stock exchanges. News stories are included too, kept separate from the official record.
  • A list of penalties going back to 2014. Each one has the date and a link to the original notice, and the amount when the regulator gives one.

What you can do with it:

  • Look up your bank. Is it under RBI restrictions? Is your money insured, and up to how much? What has the RBI done to it in the past year? Each answer links to the official source.
  • See official records first. Documents from regulators and courts come first. News stories are in a separate section, so you can tell what a regulator did from what a newspaper said.
  • Read what happened at PMC Bank, Yes Bank and Lakshmi Vilas Bank, step by step, from official records.
  • Compare up to four banks side by side, or print a one-page summary of any bank.
  • Follow a bank. Each bank has its own feed, so you can get updates when something new comes in.

The site updates every night. If a night gets missed, it goes back and picks up any RBI notices it missed. If a source stops updating, the site shows that too.

What it doesn’t do

It doesn’t score, rate or rank banks, and it doesn’t give money advice. That’s because of the experiment above. If the data can’t predict trouble, a score that looks like a prediction would only mislead people.

Bank Docket shows what happened, when it happened and where it’s written down. It shows how up to date its data is, and a limits page lists what it doesn’t cover yet.

Who it’s for

  • Depositors who want a quick, clear answer about their own bank.
  • Journalists who need a bank’s history with regulators, with sources, quickly.
  • Analysts, compliance teams and lenders looking into a bank before working with it.

It’s free and you don’t need an account. Sign up on the site to hear when bank alerts launch.

Prove me wrong

I’d be glad to be wrong about this. If you have an idea I didn’t try, a better way to define “trouble” or data I didn’t have, I’d love to hear it, and I’ll test it the same way.

Filed Under: Technology Tagged With: banking, data, india, machine-learning, rbi

Artificial Intelligence And The Art Of Killing

August 6, 2015 by Raj Agrawal Leave a Comment

Just few weeks ago, a robot killed a factory worker. The factory was that of Volkswagen, one of the worlds biggest auto manufacturers. The worker was installing the stationary robot, when it suddenly hit and crushed him. The worker died in the hospital, and now the authorities are clueless about who they should blame.

It’s said that Artificial Intelligence will be the undoing of man; that it is the hell we will create for ourselves. In this incident, the robot might have had a defect since they are not programmed to take decisions on who should live and who should die, but it serves as a perfect example for the naysayers. Everybody fears a terminator like future, where we are fighting for our very survival.

Artificial Intelligence - Asesinato de Francisco Guerrero
You don’t want a robot to be doing this. Would you? – (Analogy borrowed from ‘The Mexican Ripper’ by artist José Guadalupe Posada).

It is a rational train of thought. We create Artificial intelligence that assumes superiority over humans and assumes that we have outlived our usefulness, it launches war on us. And human kind is exterminated. I say rational not because it does not sound extremely stupid.

Elon musk thoroughly condemns Artificial intelligence. He does not cite concrete reasons for the same, but he firmly maintains the opinion. If somebody hits me by mistake while travelling on the road, I will feel a momentary surge of anger, but I will try to understand why the other person hit me. In any scenario, being the kind of person I am, I would rather not retaliate even though the other person might have done it on purpose. I want my peace of mind, and what is right and what is wrong does not concern me for such a trivial matter. Making a machine understand this is almost impossible, or at least it seems the case.
Angels and Demons; the world is made up of them. In reality it’s gray, but that’s how we generally perceive people. Darkness is evil, and the bearer of evil is the devil.

It would boil down to whether the person is right or wrong. With this in mind, one question comes to mind – how would Artificial Intelligence determine whether the person is right or wrong? One way would be to check if the person under observation has done something questionable, when compared against a list of ideal behaviours that a human being must display. Another thing to consider is the impact or his/her irregular behaviour. That is how we would think; although in our case its second nature to analyse things, so we end up not asking questions. The movies tell us that at some point in a future we may or may not be able to foresee. Artificial intelligence is going to decide that it needs to rule the world, and machines will start killing people.

Can we perhaps avoid this situation? If I make a self sustaining Artificial Intelligence machine, i’ll override some of its behaviours. First of all, there should never be a society where machines and humans co-exist as equals, simply because the purpose of us creating Artificial Intelligence is so that they can help us survive, not to establish their own civilisation. And so even if we give them the power to analyse and gather knowledge, their ultimate goal should always be that of satisfying our interests. That sounds tyrannical, but that is the only way to avoid a possible future disaster.

Paradoxes are fascinating. ‘This statement is false’ is a positive assertion which equates to true, but which contradicts the context of the statement. We can process paradoxes because we accept that two contradictory statements can exist in a similar way that contradictions exist in our daily lives. We can be good and bad at the same time, and this experience teaches us to accept conflicting views. Artificial Intelligence will merely convert statements into equations to understand them, and when it encounters something like ‘statement = false = true’, it fails. How it will react to this scenario is unpredictable.

I believe we are doing Artificial Intelligence the wrong way. Instead of getting them closer to human thinking, we should give each one of them a specialisation, and have them explore the possibilities of that specialisation. Google is already doing that with their self driven cars. I can imagine a future where a car will drive along a coast line by itself without anyone just to the enjoy the view. We can have Artificial Intelligence work on solving big world problems like pollution, poverty, crime, corruption, disease, global warming or have them working on future possibilities in Space exploration, medicine, alternate resources of fuel and food. If we try to make them exactly like human beings, we might not utilise their potential, because humans have the tendency to degrade through the way they think. Instead make them focus on one particular thing, and have them become smarter and become experts and innovators at that. This way, they might actually turn out to be a boon for society, and not the death of it as we’re predicting so conveniently now.

Filed Under: Technology Tagged With: artificial intelligence

Smartphones Have Feelings

July 4, 2015 by Raj Agrawal Leave a Comment

Decades ago, cellular phones were like obedient canines. They were faithful. They would run out of juice when you don’t feed them and would light up when they see you. When I had a simple Nokia phone, I was happy. It did not misbehave with me, and was generally predictable. Its state depended on how I treated it. I could soak it in water, and it would dry up and start working in a few hours. My uncle dropped his 3310, and it was as if something gradually grazed it; not even one bit of hurt.

A smartphone on the other hand, is like your first newborn child. It may not always be responsive and requires more juice than you can provide. But it learns like a child. These days a phone can surprise you in ways you would not imagine. If I check the score of some game played between two random teams in my phone browser, it shows me results of other games, in hope that I would appreciate it. It can automatically arrange stuff for you, and keep your memory intact. It lets you do much more than a normal phone allows you to, and has become more than just a fancy commodity you just cannot do without.

Smartphones have feelings
A smartphone that feels.

A friend of mine argues that smartness requires one to think by themselves. As such, phones being called smart is a joke. Phones only do what you tell them to. Even when they tend to do things you are not expecting, all of it has been programmed, and they are doing nothing on their own accord. Autofocus, predictive search, predictive results, behavioural understanding, and suggestions based on behavioural understanding are all part of what the phone has been designed to do. Where is the so called smartness then?

By definition, smartness is having or showing intelligence, which is the ability to acquire, understand and use knowledge. Human beings are able to process data into information, store it, and use it at a later time. It can be as simple as your wife remembering what you said 5 years ago on a boring day, at an inconsequential time, and then bringing it back in a conversation to awe and frustrate you, or it can be as complex as learning chemistry for the first time. Computers however, have to be fed data and have to be told how to use it. The only work they can do by themselves is to store the given data and retrieve it back.

Can you teach a computer how to think? This question has always boggled me. As a human being who knows that the computer is a machine, it sounds ridiculous. But as a computer programmer, it’s a world brimming with possibility. There are mainly two aspects to this, teaching a computer how to save the data in a meaningful manner based on the type of data supplied, and having it retrieve the data based on the type of query supplied. The secret ingredient in all of this is having the computer memorize this lesson of saving and retrieving data in a specific manner, and having it apply the same the next time you want the said data. So in a way, you’re incepting a behaviour in a computer’s memory. Without getting into too much detail, let’s just say that Artificial Intelligence has all of this covered. And although full fledged AI has its own separate branch, the basics of AI are used in almost all software applications these days.

The funny thing is this is exactly how we teach our children. We teach them behaviors; we just don’t have to code them in their minds. There is that extra effort involved with computers. But the bigger claim still holds; you can emulate smartness in a computer, and you can give it the ability to understand and record certain behaviours and then use them appropriately based on choices, which themselves can be programmed into its memory.

Recently, I had booked a flight from Bombay to Bangalore from a popular online booking service. They sent me an email to my gmail account. The minute I opened the mail, my phone processed it without me even having to tell it about the flight. On the day of the flight, I got an automatic reminder 3 hours prior about the pending flight. As I was reaching the airport, I got a reminder about which flight terminal the flight was leaving from, how the weather was, and if the flight was on time. In this entire process, never even once did I had to intimate anything to my phone, and it still had the courtesy of reminding me.

So suppose your context is a conversation about catching up with someone the next day at 9; if you long tap the home key, Google now will analyse the context and “smartly” ask you if you need a reminder next day at 8. Incidentally, that is also what your brain would do; register a mental reminder automatically. There are many such examples where this new feature might prove extremely handy. Technology is progressing at a rapid pace, and phones are becoming “smarter”.

Can Smartphones really have feelings? That’s akin to the ‘Android and the future of the human race’ debate. And it’s questionable to how useful will it be, if smartphones have feelings. If your smartphone could replace your friend in the future, is it a good or bad thing? In my opinion, the day man stops socialising in favour of gadgets, that will signal the end of humanity. That is one of the reasons why AI looms as a possible threat for our future. But, at the same time, I would like to end this article with the following transcript –

  • *Dial a call to Raj*
  • *Phone answers*
  • Phone – I’m sorry, but Raj is either away or busy right now. Is it okay if I give him a missed call alert and tell him to contact you later?
  • Caller – No, I need to speak with him now.
  • Phone – Oh, is it urgent?
  • Caller – Yes.
  • phone – Okay. I’ll keep ringing in order for him to notice that it might be important. At the same time i’ll message one of his colleagues and inform him to remind you.
  • Caller – Okay.
  • Phone – Is it a medical emergency?
  • Caller – No it’s something personal.
  • Phone – I’m only a phone after all. You can either leave a voice message or a text message about it. That ways he’ll see it faster.
  • Caller – No thanks. I want to speak with him personally.
  • Phone – Okay sure. Bye.

Filed Under: Technology Tagged With: intelligence

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