The Smarter Way To Improve Your Financial Health

How good are you with money? Let’s take a small quiz.

1.  Suppose you had Rs. 1,000 in a savings account and the interest rate was 4% per year. After five years, how much do you think you would have in the account if you left the money to grow? A) more than Rs. 1,040; B) exactly Rs. 1,040; C) less than Rs. 1,040; D) do not know; E) refuse to answer.

2.  Imagine that the interest rate on your savings account is 4% per year and inflation is 6% per year. After one year, would you be able to buy A) more than, B) exactly the same as, or C) less than today with the money in this account? D) do not know; E) refuse to answer.

3.  Do you think that the following statement is true or false? “Buying a single company stock usually provides a safer return than a stock mutual fund.” A) true; B) false; C) do not know; D) refuse to answer.

The correct answers are 1-A; 2-C; and 3-B.

I am sure you did quite well, and if so, then you belong to a small minority of people who answered all the questions correctly. In countries with strong economies, the numbers are grim: 79 percent of Swedes, 75 percent of Italians, 73 percent of Japanese, and 69 percent of French could not respond correctly to all three questions.

These findings were published by two economists, Annamaria Lusardi and Olivia Mitchell. These ‘big three’ financial literacy questions (the original questions have $ instead of Rs. and different numbers), created by these two economists, have been used in several countries to measure financial knowledge and the results have consistently shown that financial illiteracy is a global problem, that financial literacy peaks in the middle age and women consistently score lower than men. The underlying concepts of the power of compounding, loss of purchasing power of a currency and risk diversification in financial assets are some of the foundational knowledge required to be good with money. And for most people, such knowledge remains non-existent.

We start with a disregard for the future. When we’re are young, we love to spend and splurge, given our new-found financial freedom. Savings are usually meagre at this stage, and we don’t think about retirement. When we start thinking about it, it is usually late, and we are in for a shock. It looks like an uphill battle to meet the financial goals of kid’s education, marriage, holidays, house and retirement.

Many advisors, financial institutions and government organizations, over several decades, have tried to promote a behaviour of savings over spending and promote investing in the right assets, but the results have fallen way short of expectations. It is indeed a hard problem to solve since humans are influenced by a host of cognitive biases which prevent them from maintaining a proper financial health. People get sucked into what is urgent (bill payment, account transfers, transaction inquiry) and miss out on what is important (spending analysis, budget management, financial planning, retirement planning). This also happens because people don’t know how to handle their long-term financial goals.

Most bank websites have tools like budgeting, spending analysis and aggregation of income and expenses across multiple accounts. These tools normally have a dashboard and drill down functionalities, but they are not predictive or prescriptive. That is, they only tell you what has happened, not what will happen or what you should do. Interests in these tools have never been high since people have to spend cognitive energy to learn and use them. People have limited or no knowledge about how to lead a financially healthy life, and when their brains are tasked to use tools which are not intuitive or convenient, they tend to drop the ball.

Imagine a software that told you that your bill is due today or that you have already overspent on entertainment for the month or that you need to invest Rs. 5,000 per month more in an mutual fund if you want to enjoy that European vacation you have planned. Such guidance is painfully needed. And it cannot be delivered on a mass scale by humans working in a bank or a financial services company. Not only that is financially unviable, such a channel is driven by incentives and therefore not bereft of biases.

One of the growing uses of machine learning is in financial advisory. Data models can look at past transaction data from bank accounts and credit cards and predict with high accuracy what can happen in the near future.

Consider this question: how much can you safely save today from the money available in your bank account, without disrupting the rest of the month? Not surprisingly, you will find it very difficult to answer. That’s because it is non-trivial question. To answer it, you must know how much you have in your account now, calculate what are the expenses you are likely to incur in the rest of the month, are there any unplanned expenses you need to worry about, are there any lumpsum payments which need to be paid out and so on.

Give this problem to a computer and it can solve it in no time. All that it needs are transaction data from your accounts. Mix this up with social data and you improve the prediction power. Powerful models start telling you how to improve your financial health by telling you how to save, where to spend, which products are not right for you and which ones are, which financial goals should you start right away and what’s the best investment plan to reach that goal. This is what being good with money is all about. And it can be achieved by the click of a button on the app on your mobile or your desktop.

This is in line with the current trends of predictive, prescriptive and omni-channel experience which we see with Amazon or Google. Amazon gives suggestions basis our historical data and by analyzing what ‘people like me’ are doing. Google can tell us everything from when our meeting is going to start to which route is the best one to take to what the weather will be when we reach there. Customers have started to expect the same personalization, prediction and convenience when it comes to their banks or financial institutions.

The good news is that many leading banks are using data models and machine learning to diagnose (how am I doing), predict (what will happen to me) and prescribe (what should I do) customers towards a better financial future. Check out your bank’s mobile app and you may be in for a pleasant surprise. If you don’t find these features, then it’s time to switch. 

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About the author

Anindya Karmakar has led multiple initiatives at the cutting edge of digital connectivity, IoT, robotics, AI, analytics, paperless branch and remote advisory. He is passionate about the digital revolution which is underway. He simplifies and de-clutters digital jargons and concepts and presents them in layman's language.

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The views and opinions expressed or implied herein are my own and do not reflect those of my employer, who shall not be liable for any action that may result as a consequence of my views and opinions. The pictures used have been taken from the open internet and I don't claim any credit for them. If you would like them to be removed, contact me.