Our behavioural framework
How we study present bias in saving, run experiments, and turn messy behaviour into simple prompts, rules, and tables you can actually use.
Scan and translate research
We begin by reviewing behavioural finance and psychology research on present bias, time inconsistency, and related concepts. Our team maps key findings into simple patterns, then checks them against real life in India, including irregular income, festivals, and family pressures, to see which ideas matter most for everyday saving decisions.
Map real decisions
Next, we run interviews and short surveys with volunteers who walk us through
their recent saving history. We compare their planned actions with what actually
happened at key moments like salary credit, big sales, or emergencies, and
identify where present bias and stress shifted choices toward immediate comfort.
Design targeted tools
Using those patterns, we design lightweight tools such as prompts, rules, and comparison tables. Each tool targets a specific decision point, aims to be usable in minutes on a phone, and is written in plain language so it can be adapted to different financial setups and personal constraints.
Test in messy reality
We then run small field experiments with volunteers over weeks or months. We
track how often tools are used, when they are skipped, and how people describe
the experience. We are less interested in perfect adherence and more focused on
whether the tools still work when life gets busy or stressful.
Refine and document
After each test, we analyse patterns in use, drop tools that create friction, and refine language or timing for those that show promise. We document both successes and failures, and we explicitly state that past performance does not guarantee future results, and that results may vary by person and context.
Bundle into practical flows
Finally, we package the surviving tools into simple flows you can follow: map
your patterns, choose one change, run a short experiment, review, then adjust.
These flows are meant to support conversations with trusted professionals, not
replace personalised advice or local regulatory guidance.
How you apply the framework in practice
Map your real saving behaviour honestly
Choose one focused experiment to run
Review outcomes with clear reflection
Build a living system that evolves with you
Why a behavioural framework beats willpower alone
Traditional advice assumes discipline. Our framework assumes present bias, limited attention, and noisy lives, then builds around those constraints instead of denying them.
Old approaches to saving told people to “be disciplined” and assume a straight line from intention to action. Our methodology starts from a less flattering but more accurate view: present bias is strong, attention is limited, and life in India is noisy. We build and test small behavioural tweaks that work with these constraints, then keep only those that still function when motivation drops and days get messy. Results may vary for each person.
Experiment then refine
We run small experiments, compare options side by side, and keep what works in messy real life, not just what sounds elegant in theory or slides.
Systems, not slogans
We focus on automatic rules, prompts, and checklists that fire at the right time, reducing the need for constant self control or detailed planning.
Time based evidence
We track behaviour in weeks and months, not hours, so we see whether small changes actually survive stress, festivals, and shifting incomes.
How our methodology actually works
We built our approach by borrowing from behavioural finance, psychology, and field research, then stripping out jargon until only practical steps remained. The goal is simple: help people in India see where present bias tilts their saving decisions, and offer small, testable tools that can survive real life without promising any specific outcome. Below is how we turn research into something you can actually use.
Grounded in research
We start with peer reviewed work on present bias, time inconsistency, and related concepts from behavioural finance and psychology. Our team then cross checks those ideas against local realities in India, such as irregular income, festival seasons, and family expectations. Instead of copying experiments directly, we translate them into plain language patterns and ask a simple question: where does this show up in everyday saving decisions.
Built on real stories
We run structured interviews and surveys with volunteers who are willing to talk through their actual saving history, not just ideal plans. We look for gaps between what they said they would do and what they actually did at key moments, such as salary day or big sales. These stories reveal how present bias, stress, and social pressure interact, and they give us concrete decision points to target with prompts or rules.
Tested with small experiments
For each pattern we identify, we design small tools: short checklists, automatic style rules, and simple comparison tables. We test them with volunteers over several weeks, tracking how often they are used, when they are ignored, and whether they reduce regret or last minute stress. Tools that demand too much effort or attention get cut or simplified, no matter how clever they looked on paper.
Documented with clear limits
We then document what worked, what failed, and where results were mixed. Instead of hiding messy outcomes, we surface them in case style stories and notes on limitations. We remind users that past performance does not guarantee future results, and that results may vary based on context, motivation, and external events they cannot control.
Turned into usable flows
Finally, we package the surviving tools into clear flows: map your patterns, pick one rule, run a short experiment, review, and adjust. This keeps the methodology accessible without turning it into a rigid programme. You can use parts of it alone or bring the structures into conversations with trusted professionals who know your full situation.