Leave Encashment Tax: In Service vs When You Leave

The four limits on exit

Section 19(1), Table Sl. 14 of the Income-tax Act, 2025_Bill.pdf) exempts leave encashment received "on superannuation or otherwise". The exempt amount is the minimum of:

The part above the lowest limb is taxable as salary in the tax year you receive it.

A worked exit in tax year 2026-27

All figures are hypothetical. You leave on 31 January 2027 after six years' service.

• Leave balance: 75 days. Your employer credits 20 days a year, below the 30-day cap in limb (a), so the whole balance counts.
• Average monthly salary over the previous 10 months: ₹90,000. "Salary" here should follow the definition payroll applies for this exemption. We have not verified that definition, so treat ₹90,000 as the figure your payroll confirms.
• Per-day value: ₹90,000 ÷ 30 = ₹3,000. That conversion is an assumption for the example; use the method in your leave policy.
• Encashment actually paid: 75 × ₹3,000 = ₹2,25,000.

The lowest of (a), (b) and (d) is ₹2,25,000. So the exempt amount is ₹2,25,000 if L is at least that, and L otherwise. Either way nothing is taxable above ₹2,25,000, because that is all you received.

When limb (d) is lower

Some employers pay encashment on basic pay rather than on the salary figure used in limb (a). If basic is ₹45,000, the payment is 75 × ₹1,500 = ₹1,12,500. Limb (d) is then the lowest, and you are exempt on everything you received, subject to L. The exemption never exceeds what was paid.

When the 30-day cap bites

If your employer credited, say, 36 days a year, limb (a) counts entitlement at no more than 30 days for each year of service. Leave credited above that rate may still be paid under your policy, but the extra days do not raise limb (a). The script applies only a simple ceiling of 30 days per year to the balance; follow payroll's working if your leave history is more complicated.

# Hypothetical leave encashment on leaving. Section 19(1), Table Sl. 14.
def exempt_on_exit(balance_days, years, avg_salary, per_day_value,
                   actually_paid, notified_limit=None):
    countable = min(balance_days, 30 * years)   # simple 30-days-a-year ceiling
    limbs = {
        "a_cash_equivalent": countable * per_day_value,
        "b_ten_months": 10 * avg_salary,
        "d_received": actually_paid,
    }
    if notified_limit is not None:
        limbs["c_notified"] = notified_limit
    exempt = min(limbs.values())
    return limbs, exempt, actually_paid - exempt

print(exempt_on_exit(75, 6, 90000, 3000, 225000))
print(exempt_on_exit(75, 6, 90000, 3000, 112500))
# Put your verified notified limit in place of None to include limb (c).

The notified limit is left as None on purpose. When you have the current figure, pass it in, and the function will include it in the minimum.

Encashing in service instead

Now suppose that a year earlier you encashed 15 days while still employed, at the same ₹3,000 a day, for ₹45,000. That is salary. If your other salary put you in the 20% slab under the new regime, the tax was 20% plus 4% cess on ₹45,000, or ₹9,360. The rates are on the department's slab page.

Keeping the days may save tax, but only if your policy allows carrying them forward and your exit falls within the four limits. If your policy caps the balance, days above it may lapse, and then encashing in service is the only way to be paid for them.

Which regime this is under

The new-regime exclusions in section 202(2) that we reviewed remove, among others, the rent allowance and leave travel concession exemptions. They do not list Table Sl. 14. Confirm with your payroll how they treat it for your regime before relying on the exemption.

Where it shows up

Leave encashment on exit usually appears in your full and final settlement. Auditing a full and final settlement checks that line against the rest. Gratuity has its own separate exemption and minimum calculation; the gratuity half-month formula works it through.

Turning a statutory rule into a function with explicit inputs, and leaving an unknown as a parameter rather than guessing, is basic analytical hygiene. It is practised throughout our Data Science programme, taught live online with optional in-person labs at our Noida centre.